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Author SHA1 Message Date
Quentin Dufour a259f820a4 wip apple+windows 2023-04-10 16:36:38 +02:00
598 changed files with 23671 additions and 124018 deletions
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---
kind: pipeline
name: default
node:
nix-daemon: 1
steps:
- name: check formatting
image: nixpkgs/nix:nixos-22.05
commands:
- nix-shell --attr rust --run "cargo fmt -- --check"
- name: build
image: nixpkgs/nix:nixos-22.05
commands:
- nix-build --no-build-output --attr clippy.amd64 --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
- name: unit + func tests
image: nixpkgs/nix:nixos-22.05
environment:
GARAGE_TEST_INTEGRATION_EXE: result-bin/bin/garage
commands:
- nix-build --no-build-output --attr clippy.amd64 --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
- nix-build --no-build-output --attr test.amd64
- ./result/bin/garage_db-*
- ./result/bin/garage_api-*
- ./result/bin/garage_model-*
- ./result/bin/garage_rpc-*
- ./result/bin/garage_table-*
- ./result/bin/garage_util-*
- ./result/bin/garage_web-*
- ./result/bin/garage-*
- ./result/bin/integration-*
- rm result
- name: integration tests
image: nixpkgs/nix:nixos-22.05
commands:
- nix-build --no-build-output --attr clippy.amd64 --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
- nix-shell --attr integration --run ./script/test-smoke.sh || (cat /tmp/garage.log; false)
trigger:
event:
- custom
- push
- pull_request
- tag
- cron
---
kind: pipeline
type: docker
name: release-linux-amd64
node:
nix-daemon: 1
steps:
- name: build
image: nixpkgs/nix:nixos-22.05
commands:
- nix-build --no-build-output --attr pkgs.amd64.release --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
- nix-shell --attr rust --run "./script/not-dynamic.sh result-bin/bin/garage"
- name: integration
image: nixpkgs/nix:nixos-22.05
commands:
- nix-shell --attr integration --run ./script/test-smoke.sh || (cat /tmp/garage.log; false)
- name: push static binary
image: nixpkgs/nix:nixos-22.05
environment:
AWS_ACCESS_KEY_ID:
from_secret: garagehq_aws_access_key_id
AWS_SECRET_ACCESS_KEY:
from_secret: garagehq_aws_secret_access_key
TARGET: "x86_64-unknown-linux-musl"
commands:
- nix-shell --attr release --run "to_s3"
- name: docker build and publish
image: nixpkgs/nix:nixos-22.05
environment:
DOCKER_AUTH:
from_secret: docker_auth
DOCKER_PLATFORM: "linux/amd64"
CONTAINER_NAME: "dxflrs/amd64_garage"
HOME: "/kaniko"
commands:
- mkdir -p /kaniko/.docker
- echo $DOCKER_AUTH > /kaniko/.docker/config.json
- export CONTAINER_TAG=${DRONE_TAG:-$DRONE_COMMIT}
- nix-shell --attr release --run "to_docker"
trigger:
event:
- promote
- cron
---
kind: pipeline
type: docker
name: release-linux-i386
node:
nix-daemon: 1
steps:
- name: build
image: nixpkgs/nix:nixos-22.05
commands:
- nix-build --no-build-output --attr pkgs.i386.release --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
- nix-shell --attr rust --run "./script/not-dynamic.sh result-bin/bin/garage"
- name: integration
image: nixpkgs/nix:nixos-22.05
commands:
- nix-shell --attr integration --run ./script/test-smoke.sh || (cat /tmp/garage.log; false)
- name: push static binary
image: nixpkgs/nix:nixos-22.05
environment:
AWS_ACCESS_KEY_ID:
from_secret: garagehq_aws_access_key_id
AWS_SECRET_ACCESS_KEY:
from_secret: garagehq_aws_secret_access_key
TARGET: "i686-unknown-linux-musl"
commands:
- nix-shell --attr release --run "to_s3"
- name: docker build and publish
image: nixpkgs/nix:nixos-22.05
environment:
DOCKER_AUTH:
from_secret: docker_auth
DOCKER_PLATFORM: "linux/386"
CONTAINER_NAME: "dxflrs/386_garage"
HOME: "/kaniko"
commands:
- mkdir -p /kaniko/.docker
- echo $DOCKER_AUTH > /kaniko/.docker/config.json
- export CONTAINER_TAG=${DRONE_TAG:-$DRONE_COMMIT}
- nix-shell --attr release --run "to_docker"
trigger:
event:
- promote
- cron
---
kind: pipeline
type: docker
name: release-linux-arm64
node:
nix-daemon: 1
steps:
- name: build
image: nixpkgs/nix:nixos-22.05
commands:
- nix-build --no-build-output --attr pkgs.arm64.release --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
- nix-shell --attr rust --run "./script/not-dynamic.sh result-bin/bin/garage"
- name: push static binary
image: nixpkgs/nix:nixos-22.05
environment:
AWS_ACCESS_KEY_ID:
from_secret: garagehq_aws_access_key_id
AWS_SECRET_ACCESS_KEY:
from_secret: garagehq_aws_secret_access_key
TARGET: "aarch64-unknown-linux-musl"
commands:
- nix-shell --attr release --run "to_s3"
- name: docker build and publish
image: nixpkgs/nix:nixos-22.05
environment:
DOCKER_AUTH:
from_secret: docker_auth
DOCKER_PLATFORM: "linux/arm64"
CONTAINER_NAME: "dxflrs/arm64_garage"
HOME: "/kaniko"
commands:
- mkdir -p /kaniko/.docker
- echo $DOCKER_AUTH > /kaniko/.docker/config.json
- export CONTAINER_TAG=${DRONE_TAG:-$DRONE_COMMIT}
- nix-shell --attr release --run "to_docker"
trigger:
event:
- promote
- cron
---
kind: pipeline
type: docker
name: release-linux-arm
node:
nix-daemon: 1
steps:
- name: build
image: nixpkgs/nix:nixos-22.05
commands:
- nix-build --no-build-output --attr pkgs.arm.release --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
- nix-shell --attr rust --run "./script/not-dynamic.sh result-bin/bin/garage"
- name: push static binary
image: nixpkgs/nix:nixos-22.05
environment:
AWS_ACCESS_KEY_ID:
from_secret: garagehq_aws_access_key_id
AWS_SECRET_ACCESS_KEY:
from_secret: garagehq_aws_secret_access_key
TARGET: "armv6l-unknown-linux-musleabihf"
commands:
- nix-shell --attr release --run "to_s3"
- name: docker build and publish
image: nixpkgs/nix:nixos-22.05
environment:
DOCKER_AUTH:
from_secret: docker_auth
DOCKER_PLATFORM: "linux/arm"
CONTAINER_NAME: "dxflrs/arm_garage"
HOME: "/kaniko"
commands:
- mkdir -p /kaniko/.docker
- echo $DOCKER_AUTH > /kaniko/.docker/config.json
- export CONTAINER_TAG=${DRONE_TAG:-$DRONE_COMMIT}
- nix-shell --attr release --run "to_docker"
trigger:
event:
- promote
- cron
---
kind: pipeline
type: docker
name: refresh-release-page
node:
nix-daemon: 1
steps:
- name: multiarch-docker
image: nixpkgs/nix:nixos-22.05
environment:
DOCKER_AUTH:
from_secret: docker_auth
HOME: "/root"
commands:
- mkdir -p /root/.docker
- echo $DOCKER_AUTH > /root/.docker/config.json
- export CONTAINER_TAG=${DRONE_TAG:-$DRONE_COMMIT}
- nix-shell --attr release --run "multiarch_docker"
- name: refresh-index
image: nixpkgs/nix:nixos-22.05
environment:
AWS_ACCESS_KEY_ID:
from_secret: garagehq_aws_access_key_id
AWS_SECRET_ACCESS_KEY:
from_secret: garagehq_aws_secret_access_key
commands:
- mkdir -p /etc/nix && cp nix/nix.conf /etc/nix/nix.conf
- nix-shell --attr release --run "refresh_index"
depends_on:
- release-linux-amd64
- release-linux-i386
- release-linux-arm64
- release-linux-arm
trigger:
event:
- promote
- cron
---
kind: signature
hmac: ac09a5a8c82502f67271f93afa1e1e21ce66383b8e24a6deb26b285cc1c378ba
...
-55
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@@ -1,55 +0,0 @@
labels:
nix: "enabled"
when:
- event:
- tag
- pull_request
- deployment
- cron
- manual
- event: push
branch: main-*
steps:
- name: check formatting
image: nixpkgs/nix:nixos-24.05
commands:
- nix-build -j4 --attr flakePackages.fmt
- name: check typos
image: nixpkgs/nix:nixos-24.05
commands:
- nix-shell --attr ci --run typos
- name: check lints with clippy
image: nixpkgs/nix:nixos-24.05
commands:
- nix-build -j4 --attr flakePackages.clippy
- name: build
image: nixpkgs/nix:nixos-24.05
commands:
- nix-build -j4 --attr flakePackages.dev
- name: unit + func tests (lmdb)
image: nixpkgs/nix:nixos-24.05
commands:
- nix-build -j4 --attr flakePackages.tests-lmdb
- name: unit + func tests (sqlite)
image: nixpkgs/nix:nixos-24.05
commands:
- nix-build -j4 --attr flakePackages.tests-sqlite
- name: unit + func tests (fjall)
image: nixpkgs/nix:nixos-24.05
commands:
- nix-build -j4 --attr flakePackages.tests-fjall
- name: integration tests
image: nixpkgs/nix:nixos-24.05
commands:
- nix-build -j4 --attr flakePackages.dev
- nix-shell --attr ci --run ./script/test-smoke.sh || (cat /tmp/garage.log; false)
depends_on: [ build ]
-33
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@@ -1,33 +0,0 @@
labels:
nix: "enabled"
when:
event:
- deployment
- cron
depends_on:
- release
steps:
- name: refresh-index
image: nixpkgs/nix:nixos-24.05
environment:
AWS_ACCESS_KEY_ID:
from_secret: garagehq_aws_access_key_id
AWS_SECRET_ACCESS_KEY:
from_secret: garagehq_aws_secret_access_key
commands:
- mkdir -p /etc/nix && cp nix/nix.conf /etc/nix/nix.conf
- nix-shell --attr ci --run "refresh_index"
- name: multiarch-docker
image: nixpkgs/nix:nixos-24.05
environment:
DOCKER_AUTH:
from_secret: docker_auth
commands:
- mkdir -p /root/.docker
- echo $DOCKER_AUTH > /root/.docker/config.json
- export CONTAINER_TAG=${CI_COMMIT_TAG:-$CI_COMMIT_SHA}
- nix-shell --attr ci --run "multiarch_docker"
-79
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@@ -1,79 +0,0 @@
labels:
nix: "enabled"
when:
event:
- deployment
- cron
matrix:
include:
- ARCH: amd64
TARGET: x86_64-unknown-linux-musl
- ARCH: i386
TARGET: i686-unknown-linux-musl
- ARCH: arm64
TARGET: aarch64-unknown-linux-musl
- ARCH: arm
TARGET: armv6l-unknown-linux-musleabihf
steps:
- name: build
image: nixpkgs/nix:nixos-24.05
commands:
- nix-build --attr releasePackages.${ARCH} --argstr git_version ${CI_COMMIT_TAG:-$CI_COMMIT_SHA}
- name: check is static binary
image: nixpkgs/nix:nixos-24.05
commands:
- nix-shell --attr ci --run "./script/not-dynamic.sh result/bin/garage"
- name: integration tests
image: nixpkgs/nix:nixos-24.05
commands:
- nix-shell --attr ci --run ./script/test-smoke.sh || (cat /tmp/garage.log; false)
when:
- matrix:
ARCH: amd64
- matrix:
ARCH: i386
- name: upgrade tests from v1.0.0
image: nixpkgs/nix:nixos-24.05
commands:
- nix-shell --attr ci --run "./script/test-upgrade.sh v1.0.0 x86_64-unknown-linux-musl" || (cat /tmp/garage.log; false)
when:
- matrix:
ARCH: amd64
- name: upgrade tests from v0.8.4
image: nixpkgs/nix:nixos-24.05
commands:
- nix-shell --attr ci --run "./script/test-upgrade.sh v0.8.4 x86_64-unknown-linux-musl" || (cat /tmp/garage.log; false)
when:
- matrix:
ARCH: amd64
- name: push static binary
image: nixpkgs/nix:nixos-24.05
environment:
TARGET: "${TARGET}"
AWS_ACCESS_KEY_ID:
from_secret: garagehq_aws_access_key_id
AWS_SECRET_ACCESS_KEY:
from_secret: garagehq_aws_secret_access_key
commands:
- nix-shell --attr ci --run "to_s3"
- name: docker build and publish
image: nixpkgs/nix:nixos-24.05
environment:
DOCKER_PLATFORM: "linux/${ARCH}"
CONTAINER_NAME: "dxflrs/${ARCH}_garage"
DOCKER_AUTH:
from_secret: docker_auth
commands:
- mkdir -p /root/.docker
- echo $DOCKER_AUTH > /root/.docker/config.json
- export CONTAINER_TAG=${CI_COMMIT_TAG:-$CI_COMMIT_SHA}
- nix-shell --attr ci --run "to_docker"
-231
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@@ -1,231 +0,0 @@
# Contributing to Garage
## Policy on AI
To ensure the quality of the codebase and documentation, the use of AI,
including LLMs and coding agents, is strictly restricted in the following way:
- AI **must not** be used to write documentation
- **Do not** use AI to write bug reports, commit descriptions and pull request
messages
- **Do not** use AI agents to make contributions to Garage, all contributions
must be led by a human that know what they are doing at all times
- AI **may** be used for some tedious code generation tasks, limited to very
mechanical translations from API docs or boilerplate writing. The code
generated must be so simple as to make it clear that it cannot be covered by
copyright.
You are free to make use of AI privately to explore the codebase and solve
conceptual problems, but please restrain from copying the output from an LLM
anywhere in your code or on the issue tracker, or from letting an agent edit
the codebase directly.
## Asking questions
Read the documentation before asking questions.
Do not use the issue tracker to ask questions about Garage.
Questions asked on the issue tracker will be closed.
Ask questions on the Matrix channel `#garage:deuxfleurs.fr` so that any
community member can see your question and help you out.
If you need in-depth support from the Garage developers specifically, write to
`garagehq@deuxfleurs.fr`. Even if you do so, we do not commit to giving you an
answer.
## Reporting bugs
When writing a bug report, use this checklist:
- For bugs that can be reproduced:
- confirm that you are using the latest version of Garage and that the bug still exists in this version
- set the log level to debug using the `RUST_LOG=garage=debug` environment variable and reproduce the bug to get more verbose logs
- Check whether there is already an open issue in the bug tracker. If so, your bug report is still valuable but please add it as a comment to the existing issue instead of opening a new one.
- Collect as much information as possible:
- logs of the Garage daemon at the time the issue happened, including logs that show what was happening before the issue occurred
- the output of `garage status`
- the output of `garage stats -a`
- the output of `garage layout history`
- Write a detailed bug report, including:
- a description of your cluster (number of nodes, hardware, operating system, networking, etc)
- a detailed description of what you did that led to the issue, including any code or command line that invoked a Garage API
- what you were expecting
- what actually happened, and how that's different from what you expected
- the information collected previously
- if possible, simple steps to help the developers reproduce the issue locally
Bug reports that are imprecise or otherwise unactionable will be closed.
## Suggesting new features
Garage can be improved in many ways, but just suggesting a new feature does not mean we will implement it.
Feature requests that may lead to an actual implementation are feature requests that:
- are precise and actionable, i.e. include a precise description of the expected behavior and any necessary architectural details required for the implementation
- are motivated by actual need from a variety of users
Moreover, a certain number of features are defined as out-of-scope for Garage, including but not limited to:
- extensions to the S3 API that are not present on AWS
- features that require the implementation of a consensus algorithm
- more generally, features that are incompatible with the architecture of Garage and its goal of staying simple
Only feature requests in one of the following category may stay open in the issue tracker:
- features that the Garage team wants to work on
- features that are being actively worked on by an external contributor which is clearly identified
- features that are easy to implement and could be an easy task for a new contributor that wants to get to know the codebase
All other feature requests will be closed after a few months of inactivity, so as to keep the number of open issues to a manageable level.
Feature requests that are clearly out of scope will be closed directly.
## Improving the documentation
An easy way to contribute to Garage which also adds a lot of value is to
improve the documentation. Make sure to write in clear technical English, and
write unambiguously. Documentation contributions are very appreciated if they
are well-written.
## For developers
We welcome code contributions to Garage that adhere to our standards for quality:
- Changes should be reviewed from a functional perspective to ensure that they work well with the existing codebase and do not introduce bugs or subtle issues.
- You must have tested your contribution to make sure that it does what it says. The amount of testing required is proportional to the complexity of the change introduced.
- Any new feature must be properly documented following existing practices (see below).
- Unit tests should be included when relevant.
- Contributions should pass basic lints for syntactic quality (`cargo fmt`, `cargo clippy`, `typos`).
- Contributions should pass our CI test suite.
- No user-facing breaking changes may be introduced between major releases.
- No internal data model change may be introduced between major releases, to
ensure that Garage daemons with different minor/patch versions numbers can
work together in a cluster. For major releases, a proper migration path
should be implemented and tested thoroughly.
Please follow up on your work when changes are requested, to avoid stale PRs.
Do not take it personally if a Garage developer pushes directly to your branch
to modify your contribution, as this might be necessary to get it merged
faster.
### Properly documenting your contribution
#### Configuration options
New configuration options should be documented in
`doc/book/reference-manual/configuration.md`. The documentation for a
configuration option should be exhaustive. For instance, for choice options all
choices should be listed explicitly with a precise description of their
meaning.
In terms of syntax, all configuration options should appear in three places:
- in the example at the top, with an example value
- in the index of all configuration options which is sorted by alphabetical order
- in its dedicated subsection with full reference text
#### CLI commands and command flags
CLI commands are self-documented using the doc commends in the codebase.
Make sure to write clear and precise comments for all options you are adding.
#### S3 features
If you implement new S3 features, make sure to update the compatibility matrix in `doc/book/reference-manual/s3-compatibility.md`.
#### Admin API
The admin API has an OpenAPI specification that is automatically generated
using Utoipa, from a description of each endpoint that is given in
`src/api/admin/openapi.rs` and a description of data structure schemas in
`src/api/admin/api.rs`. The code in `openapi.rs` is only used to generate the
OpenAPI specification document and not for the actual implementation in Garage,
whereas structures defined in `api.rs` are also used for the implementation of
API calls. Make sure to write good doc comments for all of these items so that
the OpenAPI specification will be precise and accurate.
An up-to-date version of the OpenAPI specification document should be kept in
the repository in `doc/api/garage-admin-v2.json`. When you are making changes
to the admin API, update this document with the following command:
```
cargo run -- admin-api-schema > doc/api/garage-admin-v2.json
```
## Garage team organization
Alex (handle `lx`) is the lead developer and is responsible of ensuring the
correctness of Garage and stability between version upgrades.
The other maintainers are Trinity (handle `trinity-1686a`), Quentin (handle `quentin`) and Maximilien (handle `halfa`).
Maximilien is responsible for coordinating effort on the Kubernetes integration / Helm chart.
## Pull request merging criteria
The following PRs should only be merged after review and approval from Alex:
- PRs that introduce architectural changes, such as changes in the data model
or change in the coordination protocols between nodes
- PRs that introduce changes on the format of data structures used for
persistent disk storage and internal cluster communication (RPC)
- PRs that are suspected of introducing some kind of breakage or unexpected
behavior due to their complexity
PRs that introduce breaking change for users but don't fall in one of the
previous category should be discussed between maintainers to evaluate the
impact on users when upgrading. Alex's approval is not required to merge them
as long as they are clearly identified as breaking in the PR title, and are
properly merged in the branch for the next major version and not in the current
main branch.
All other PRs can be merged by any maintainer on their own, once they are
confident that the quality standards defined in this document are respected
before merging.
## Merging strategy
When merging PRs, maintainers should ensure that a Git commit is created by
Forgejo that records the PR number, its title and its text in the commit
message. If a PR is fixing an issue, make sure that the issue number is
included in the PR title as well. This is to ensure that when releasing a new
version of Garage, the changelog in the release notes can be properly
constructed by reading the Git log since the last release.
We also want to keep the history "almost linear" to facilitate the use of `git
bisect` if it ever were necessary. This leaves the following two merging
strategies:
- For PRs that consist of many commits that should stay independent, the
"rebase and create merge commit" strategy should be used. The merge commit is
created automatically by Forgejo and saves the PR's number, title and text in
the commit message.
- For PRs that consist of only one commit, or a few number of commits that can
be merged, the "create squash commit" strategy should be used. This way a
single commit will be created by Forgejo which also saves the PR's number,
title and text in the commit message.
When cherry-picking commits from one branch to the other, a simple fast-forward
merging strategy can be used if the commit message already references a PR
number.
Generated
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@@ -3,195 +3,20 @@ resolver = "2"
members = [
"src/db",
"src/util",
"src/net",
"src/rpc",
"src/table",
"src/block",
"src/model",
"src/api/common",
"src/api/s3",
"src/api/k2v",
"src/api/admin",
"src/api",
"src/web",
"src/garage",
"src/k2v-client",
"src/format-table",
"fuzz",
]
default-members = ["src/garage"]
[workspace.dependencies]
# Internal Garage crates
format_table = { version = "0.1.1", path = "src/format-table" }
garage_api_common = { version = "2.3.0", path = "src/api/common" }
garage_api_admin = { version = "2.3.0", path = "src/api/admin" }
garage_api_s3 = { version = "2.3.0", path = "src/api/s3" }
garage_api_k2v = { version = "2.3.0", path = "src/api/k2v" }
garage_block = { version = "2.3.0", path = "src/block" }
garage_db = { version = "2.3.0", path = "src/db", default-features = false }
garage_model = { version = "2.3.0", path = "src/model", default-features = false }
garage_net = { version = "2.3.0", path = "src/net" }
garage_rpc = { version = "2.3.0", path = "src/rpc" }
garage_table = { version = "2.3.0", path = "src/table" }
garage_util = { version = "2.3.0", path = "src/util" }
garage_web = { version = "2.3.0", path = "src/web" }
k2v-client = { version = "0.0.4", path = "src/k2v-client" }
# External crates from crates.io
arc-swap = "1.8"
arbitrary = { version = "1.4.2"}
argon2 = "0.5"
async-trait = "0.1"
backtrace = "0.3"
base64 = "0.22"
blake2 = "0.10"
bytes = "1.11"
bytesize = "2.3"
cfg-if = "1.0"
chrono = { version = "0.4", features = ["serde"] }
crc-fast = "1.9"
crypto-common = "0.1"
gethostname = "1.1"
git-version = "0.3"
hex = "0.4"
hexdump = "0.1"
hmac = "0.12"
itertools = "0.14"
ipnet = "2.11"
lazy_static = "1.5"
libfuzzer-sys = "0.4"
md-5 = "0.10"
mktemp = "0.5"
nix = { version = "0.31", default-features = false, features = ["fs"] }
nom = "8.0"
parking_lot = "0.12"
parse_duration = "2.1"
paste = "1.0"
pin-project = "1.1"
pnet_datalink = "0.35"
rand = "0.9"
sha1 = "0.10"
sha2 = "0.10"
timeago = { version = "0.5", default-features = false }
xxhash-rust = { version = "0.8", default-features = false, features = ["xxh3"] }
aes-gcm = { version = "0.10", features = ["aes", "stream"] }
sodiumoxide = { version = "0.2.5-0", package = "kuska-sodiumoxide" }
kuska-handshake = { version = "0.2.0", features = ["default", "async_std"] }
clap = { version = "4.5", features = ["derive", "env"] }
pretty_env_logger = "0.5"
structopt = { version = "0.3", default-features = false }
syslog-tracing = "0.3"
tracing = "0.1"
tracing-journald = "0.3"
tracing-subscriber = { version = "0.3", features = ["env-filter"] }
heed = { version = "0.22", default-features = false, features = [] }
rusqlite = { version = "0.38", features = ["fallible_uint"] }
r2d2 = "0.8"
r2d2_sqlite = "0.32"
fjall = "2.11"
async-compression = { version = "0.4", features = ["tokio", "zstd"] }
zstd = { version = "0.13", default-features = false }
quick-xml = { version = "0.39", features = ["serialize"] }
rmp-serde = "1.3"
serde = { version = "1.0", default-features = false, features = ["derive", "rc"] }
serde_bytes = "0.11"
serde_json = "1.0"
toml = { version = "0.9", default-features = false, features = ["parse", "serde"] }
utoipa = { version = "5.4", features = ["chrono"] }
# newer version requires rust edition 2021
k8s-openapi = { version = "0.27", features = ["v1_35"] }
kube = { version = "3.0", default-features = false, features = [
"runtime",
"derive",
"client",
"rustls-tls",
] }
schemars = "1.2"
reqwest = { version = "0.13", default-features = false, features = [
"rustls-no-provider",
"json",
] }
form_urlencoded = "1.2"
http = "1.4"
httpdate = "1.0"
http-range = "0.1"
http-body-util = "0.1"
hyper = { version = "1.8", default-features = false }
hyper-util = { version = "0.1", features = ["full"] }
multer = "3.1"
percent-encoding = "2.3"
roxmltree = "0.21"
url = "2.5"
futures = "0.3"
futures-util = "0.3"
tokio = { version = "1.49", default-features = false, features = [
"rt",
"rt-multi-thread",
"io-util",
"net",
"time",
"macros",
"sync",
"signal",
"fs",
] }
tokio-util = { version = "0.7", features = ["compat", "io"] }
tokio-stream = { version = "0.1", features = ["net"] }
socket2 = { version = "0.6", features = ["all"] }
opentelemetry = { version = "0.17", features = ["rt-tokio", "metrics", "trace"] }
opentelemetry-prometheus = "0.10"
opentelemetry-otlp = "0.10"
opentelemetry-contrib = "0.9"
prometheus = "0.13"
# used by the k2v-client crate only
aws-sigv4 = { version = "1.3", default-features = false }
hyper-rustls = { version = "0.27", default-features = false, features = [
"http1",
"http2",
"ring",
"rustls-native-certs",
] }
log = "0.4"
thiserror = "2.0"
# ---- used only as build / dev dependencies ----
assert-json-diff = "2.0"
rustc_version = "0.4"
static_init = "1.0"
aws-smithy-runtime = { version = "1.9", default-features = false, features = [
"tls-rustls",
] }
aws-sdk-config = { version = "1.99", default-features = false }
aws-sdk-s3 = { version = "1.121", default-features = false, features = [
"rt-tokio",
] }
[profile.dev]
lto = "off"
[profile.release]
lto = "thin"
codegen-units = 16
opt-level = 3
strip = "debuginfo"
[workspace.lints.clippy]
# pedantic lints configuration
doc_markdown = "warn"
format_collect = "warn"
manual_midpoint = "warn"
semicolon_if_nothing_returned = "warn"
unnecessary_semicolon = "warn"
unnecessary_wraps = "warn"
# nursery lints configuration
# or_fun_call = "warn" # enable it to help detect non trivial code used in `_or` method
debug = true
+1 -1
View File
@@ -3,5 +3,5 @@ FROM scratch
ENV RUST_BACKTRACE=1
ENV RUST_LOG=garage=info
COPY result/bin/garage /
COPY result-bin/bin/garage /
CMD [ "/garage", "server"]
+8 -3
View File
@@ -1,8 +1,13 @@
.PHONY: doc all run1 run2 run3
.PHONY: doc all release shell run1 run2 run3
all:
clear
cargo build
clear; cargo build
release:
nix-build --attr pkgs.amd64.release --no-build-output
shell:
nix-shell
# ----
+1 -1
View File
@@ -1,4 +1,4 @@
Garage [![status-badge](https://woodpecker.deuxfleurs.fr/api/badges/1/status.svg)](https://woodpecker.deuxfleurs.fr/repos/1)
Garage [![Build Status](https://drone.deuxfleurs.fr/api/badges/Deuxfleurs/garage/status.svg?ref=refs/heads/main)](https://drone.deuxfleurs.fr/Deuxfleurs/garage)
===
<p align="center" style="text-align:center;">
-14
View File
@@ -1,14 +0,0 @@
# Security Reporting
If you wish to report responsibly a security vulnerability about Garage, we ask that you follow the following process.
Please report each security vulnerabilities by filling out the following template:
- PROJECT: A URL to the code repository containing the vulnerable version - be reminded that the source of truth is at https://git.deuxfleurs.fr/deuxfleurs/garage
- PUBLIC: Please let us know if this vulnerability has been made or discussed publicly already, and if so, please let us know where.
- DESCRIPTION: Please provide precise description of the security vulnerability you have found with as much information as you are able and willing to provide.
Please send the above info, along with any other information you feel is pertinent by emailing the core team at: garagehq@deuxfleurs.fr
The Garage Core Team will let you know within a few weeks whether or not your report has been accepted or rejected.
We ask that you please keep the report confidential until we have either responded or made a public announcement.
+52 -13
View File
@@ -3,22 +3,61 @@
with import ./nix/common.nix;
let
pkgs = import nixpkgs { };
pkgs = import pkgsSrc { };
compile = import ./nix/compile.nix;
build_release = target: (compile {
inherit target system git_version nixpkgs;
crane = flake.inputs.crane;
rust-overlay = flake.inputs.rust-overlay;
release = true;
}).garage;
build_debug_and_release = (target: {
debug = (compile {
inherit system target git_version pkgsSrc cargo2nixOverlay;
release = false;
}).workspace.garage { compileMode = "build"; };
release = (compile {
inherit system target git_version pkgsSrc cargo2nixOverlay;
release = true;
}).workspace.garage { compileMode = "build"; };
});
test = (rustPkgs:
pkgs.symlinkJoin {
name = "garage-tests";
paths =
builtins.map (key: rustPkgs.workspace.${key} { compileMode = "test"; })
(builtins.attrNames rustPkgs.workspace);
});
in {
releasePackages = {
amd64 = build_release "x86_64-unknown-linux-musl";
i386 = build_release "i686-unknown-linux-musl";
arm64 = build_release "aarch64-unknown-linux-musl";
arm = build_release "armv6l-unknown-linux-musleabihf";
pkgs = {
amd64 = build_debug_and_release "x86_64-unknown-linux-musl";
i386 = build_debug_and_release "i686-unknown-linux-musl";
arm64 = build_debug_and_release "aarch64-unknown-linux-musl";
arm = build_debug_and_release "armv6l-unknown-linux-musleabihf";
win = {
amd64 = build_debug_and_release "x86_64-w64-mingw32";
};
apple = {
arm64 = build_debug_and_release "aarch64-apple-darwin";
amd64 = build_debug_and_release "x86_64-apple-darwin";
};
};
test = {
amd64 = test (compile {
inherit system git_version pkgsSrc cargo2nixOverlay;
target = "x86_64-unknown-linux-musl";
features = [
"garage/bundled-libs"
"garage/k2v"
"garage/sled"
"garage/lmdb"
"garage/sqlite"
];
});
};
clippy = {
amd64 = (compile {
inherit system git_version pkgsSrc cargo2nixOverlay;
target = "x86_64-unknown-linux-musl";
compiler = "clippy";
}).workspace.garage { compileMode = "build"; };
};
flakePackages = flake.packages.${system};
}
+1 -1
View File
@@ -1,7 +1,7 @@
<!DOCTYPE html>
<html>
<head>
<title>Garage administration API v0</title>
<title>Garage Adminstration API v0</title>
<!-- needed for adaptive design -->
<meta charset="utf-8"/>
<meta name="viewport" content="width=device-width, initial-scale=1">
+5 -5
View File
@@ -3,10 +3,10 @@ info:
version: v0.8.0
title: Garage Administration API v0+garage-v0.8.0
description: |
Administrate your Garage cluster programmatically, including status, layout, keys, buckets, and maintenance tasks.
*Disclaimer: The API is not stable yet, hence its v0 tag. The API can change at any time, and changes can include breaking backward compatibility. Read the changelog and upgrade your scripts before upgrading. Additionally, this specification is very early stage and can contain bugs, especially on error return codes/types that are not tested yet. Do not expect a well finished and polished product!*
paths:
Administrate your Garage cluster programatically, including status, layout, keys, buckets, and maintainance tasks.
*Disclaimer: The API is not stable yet, hence its v0 tag. The API can change at any time, and changes can include breaking backward compatibility. Read the changelog and upgrade your scripts before upgrading. Additionnaly, this specification is very early stage and can contain bugs, especially on error return codes/types that are not tested yet. Do not expect a well finished and polished product!*
paths:
/status:
get:
tags:
@@ -632,7 +632,7 @@ paths:
operationId: "UpdateBucket"
summary: "Update a bucket"
description: |
All fields (`websiteAccess` and `quotas`) are optional.
All fields (`websiteAccess` and `quotas`) are optionnal.
If they are present, the corresponding modifications are applied to the bucket, otherwise nothing is changed.
In `websiteAccess`: if `enabled` is `true`, `indexDocument` must be specified.
-24
View File
@@ -1,24 +0,0 @@
<!DOCTYPE html>
<html>
<head>
<title>Garage administration API v1</title>
<!-- needed for adaptive design -->
<meta charset="utf-8"/>
<meta name="viewport" content="width=device-width, initial-scale=1">
<link href="./css/redoc.css" rel="stylesheet">
<!--
Redoc doesn't change outer page styles
-->
<style>
body {
margin: 0;
padding: 0;
}
</style>
</head>
<body>
<redoc spec-url='./garage-admin-v1.yml'></redoc>
<script src="./redoc.standalone.js"> </script>
</body>
</html>
File diff suppressed because it is too large Load Diff
-24
View File
@@ -1,24 +0,0 @@
<!DOCTYPE html>
<html>
<head>
<title>Garage administration API v2</title>
<!-- needed for adaptive design -->
<meta charset="utf-8"/>
<meta name="viewport" content="width=device-width, initial-scale=1">
<link href="./css/redoc.css" rel="stylesheet">
<!--
Redoc doesn't change outer page styles
-->
<style>
body {
margin: 0;
padding: 0;
}
</style>
</head>
<body>
<redoc spec-url='./garage-admin-v2.json'></redoc>
<script src="./redoc.standalone.js"> </script>
</body>
</html>
File diff suppressed because it is too large Load Diff
File diff suppressed because one or more lines are too long
+2 -2
View File
@@ -1,6 +1,6 @@
+++
title = "Build your own app"
weight = 40
weight = 4
sort_by = "weight"
template = "documentation.html"
+++
@@ -51,4 +51,4 @@ We are currently building this SDK for [Python](@/documentation/build/python.md#
More information:
- [In the reference manual](@/documentation/reference-manual/admin-api.md)
- [Full specification](https://garagehq.deuxfleurs.fr/api/garage-admin-v0.html)
- [Full specifiction](https://garagehq.deuxfleurs.fr/api/garage-admin-v0.html)
+13 -67
View File
@@ -37,84 +37,30 @@ import (
"context"
"fmt"
"os"
"strings"
garage "git.deuxfleurs.fr/garage-sdk/garage-admin-sdk-golang"
)
func main() {
// Initialization
// Set Host and other parameters
configuration := garage.NewConfiguration()
configuration.Host = "127.0.0.1:3903"
// We can now generate a client
client := garage.NewAPIClient(configuration)
// Authentication is handled through the context pattern
ctx := context.WithValue(context.Background(), garage.ContextAccessToken, "s3cr3t")
// Nodes
fmt.Println("--- nodes ---")
nodes, _, _ := client.NodesApi.GetNodes(ctx).Execute()
fmt.Fprintf(os.Stdout, "First hostname: %v\n", nodes.KnownNodes[0].Hostname)
capa := int64(1000000000)
change := []garage.NodeRoleChange{
garage.NodeRoleChange{NodeRoleUpdate: &garage.NodeRoleUpdate {
Id: *nodes.KnownNodes[0].Id,
Zone: "dc1",
Capacity: *garage.NewNullableInt64(&capa),
Tags: []string{ "fast", "amd64" },
}},
// Send a request
resp, r, err := client.NodesApi.GetNodes(ctx).Execute()
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `NodesApi.GetNodes``: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
staged, _, _ := client.LayoutApi.AddLayout(ctx).NodeRoleChange(change).Execute()
msg, _, _ := client.LayoutApi.ApplyLayout(ctx).LayoutVersion(*garage.NewLayoutVersion(staged.Version + 1)).Execute()
fmt.Printf(strings.Join(msg.Message, "\n")) // Layout configured
health, _, _ := client.NodesApi.GetHealth(ctx).Execute()
fmt.Printf("Status: %s, nodes: %v/%v, storage: %v/%v, partitions: %v/%v\n", health.Status, health.ConnectedNodes, health.KnownNodes, health.StorageNodesOk, health.StorageNodes, health.PartitionsAllOk, health.Partitions)
// Key
fmt.Println("\n--- key ---")
key := "openapi-key"
keyInfo, _, _ := client.KeyApi.AddKey(ctx).AddKeyRequest(garage.AddKeyRequest{Name: *garage.NewNullableString(&key) }).Execute()
defer client.KeyApi.DeleteKey(ctx).Id(*keyInfo.AccessKeyId).Execute()
fmt.Printf("AWS_ACCESS_KEY_ID=%s\nAWS_SECRET_ACCESS_KEY=%s\n", *keyInfo.AccessKeyId, *keyInfo.SecretAccessKey.Get())
id := *keyInfo.AccessKeyId
canCreateBucket := true
updateKeyRequest := *garage.NewUpdateKeyRequest()
updateKeyRequest.SetName("openapi-key-updated")
updateKeyRequest.SetAllow(garage.UpdateKeyRequestAllow { CreateBucket: &canCreateBucket })
update, _, _ := client.KeyApi.UpdateKey(ctx).Id(id).UpdateKeyRequest(updateKeyRequest).Execute()
fmt.Printf("Updated %v with key name %v\n", *update.AccessKeyId, *update.Name)
keyList, _, _ := client.KeyApi.ListKeys(ctx).Execute()
fmt.Printf("Keys count: %v\n", len(keyList))
// Bucket
fmt.Println("\n--- bucket ---")
global_name := "global-ns-openapi-bucket"
local_name := "local-ns-openapi-bucket"
bucketInfo, _, _ := client.BucketApi.CreateBucket(ctx).CreateBucketRequest(garage.CreateBucketRequest{
GlobalAlias: &global_name,
LocalAlias: &garage.CreateBucketRequestLocalAlias {
AccessKeyId: keyInfo.AccessKeyId,
Alias: &local_name,
},
}).Execute()
defer client.BucketApi.DeleteBucket(ctx).Id(*bucketInfo.Id).Execute()
fmt.Printf("Bucket id: %s\n", *bucketInfo.Id)
updateBucketRequest := *garage.NewUpdateBucketRequest()
website := garage.NewUpdateBucketRequestWebsiteAccess()
website.SetEnabled(true)
website.SetIndexDocument("index.html")
website.SetErrorDocument("errors/4xx.html")
updateBucketRequest.SetWebsiteAccess(*website)
quotas := garage.NewUpdateBucketRequestQuotas()
quotas.SetMaxSize(1000000000)
quotas.SetMaxObjects(999999999)
updateBucketRequest.SetQuotas(*quotas)
updatedBucket, _, _ := client.BucketApi.UpdateBucket(ctx).Id(*bucketInfo.Id).UpdateBucketRequest(updateBucketRequest).Execute()
fmt.Printf("Bucket %v website activation: %v\n", *updatedBucket.Id, *updatedBucket.WebsiteAccess)
bucketList, _, _ := client.BucketApi.ListBuckets(ctx).Execute()
fmt.Printf("Bucket count: %v\n", len(bucketList))
// Process the response
fmt.Fprintf(os.Stdout, "Target hostname: %v\n", resp.KnownNodes[resp.Node].Hostname)
}
```
+2 -2
View File
@@ -31,9 +31,9 @@ npm install --save git+https://git.deuxfleurs.fr/garage-sdk/garage-admin-sdk-js.
A short example:
```javascript
const garage = require('garage_administration_api_v1garage_v0_9_0');
const garage = require('garage_administration_api_v0garage_v0_8_0');
const api = new garage.ApiClient("http://127.0.0.1:3903/v1");
const api = new garage.ApiClient("http://127.0.0.1:3903/v0");
api.authentications['bearerAuth'].accessToken = "s3cr3t";
const [node, layout, key, bucket] = [
+3 -3
View File
@@ -5,13 +5,13 @@ weight = 99
## S3
If you are developing a new application, you may want to use Garage to store your user's media.
If you are developping a new application, you may want to use Garage to store your user's media.
The S3 API that Garage uses is a standard REST API, so as long as you can make HTTP requests,
you can query it. You can check the [S3 REST API Reference](https://docs.aws.amazon.com/AmazonS3/latest/API/API_Operations_Amazon_Simple_Storage_Service.html) from Amazon to learn more.
Developing your own wrapper around the REST API is time consuming and complicated.
Instead, there are some libraries already available.
Developping your own wrapper around the REST API is time consuming and complicated.
Instead, there are some libraries already avalaible.
Some of them are maintained by Amazon, some by Minio, others by the community.
+6 -7
View File
@@ -23,7 +23,7 @@ client = minio.Minio(
"GKyourapikey",
"abcd[...]1234",
# Force the region, this is specific to garage
region="garage",
region="region",
)
```
@@ -80,7 +80,7 @@ from garage_admin_sdk.apis import *
from garage_admin_sdk.models import *
configuration = garage_admin_sdk.Configuration(
host = "http://localhost:3903/v1",
host = "http://localhost:3903/v0",
access_token = "s3cr3t"
)
@@ -94,14 +94,13 @@ print(f"running garage {status.garage_version}, node_id {status.node}")
# Change layout of this node
current = layout.get_layout()
layout.add_layout([
NodeRoleChange(
id = status.node,
layout.add_layout({
status.node: NodeClusterInfo(
zone = "dc1",
capacity = 1000000000,
capacity = 1,
tags = [ "dev" ],
)
])
})
layout.apply_layout(LayoutVersion(
version = current.version + 1
))
+2 -2
View File
@@ -1,6 +1,6 @@
+++
title = "Existing integrations"
weight = 30
weight = 3
sort_by = "weight"
template = "documentation.html"
+++
@@ -23,7 +23,7 @@ To configure S3-compatible software to interact with Garage,
you will need the following parameters:
- An **API endpoint**: this corresponds to the HTTP or HTTPS address
used to contact the Garage server. When running Garage locally this will usually
used to contact the Garage server. When runing Garage locally this will usually
be `http://127.0.0.1:3900`. In a real-world setting, you would usually have a reverse-proxy
that adds TLS support and makes your Garage server available under a public hostname
such as `https://garage.example.com`.
+25 -292
View File
@@ -11,10 +11,8 @@ In this section, we cover the following web applications:
| [Peertube](#peertube) | ✅ | Supported with the website endpoint, proxifying private videos unsupported |
| [Mastodon](#mastodon) | ✅ | Natively supported |
| [Matrix](#matrix) | ✅ | Tested with `synapse-s3-storage-provider` |
| [ejabberd](#ejabberd) | | `mod_s3_upload` |
| [Ente](#ente) | | Natively supported |
| [Pixelfed](#pixelfed) | ❓ | Natively supported |
| [Pleroma](#pleroma) | ✅ | Natively supported |
| [Pixelfed](#pixelfed) | | Not yet tested |
| [Pleroma](#pleroma) | | Not yet tested |
| [Lemmy](#lemmy) | ✅ | Supported with pict-rs |
| [Funkwhale](#funkwhale) | ❓ | Not yet tested |
| [Misskey](#misskey) | ❓ | Not yet tested |
@@ -38,7 +36,7 @@ Second, we suppose you have created a key and a bucket.
As a reminder, you can create a key for your nextcloud instance as follow:
```bash
garage key create nextcloud-key
garage key new --name nextcloud-key
```
Keep the Key ID and the Secret key in a pad, they will be needed later.
@@ -54,7 +52,7 @@ garage bucket allow nextcloud --read --write --key nextcloud-key
Now edit your Nextcloud configuration file to enable object storage.
On my installation, the config. file is located at the following path: `/var/www/nextcloud/config/config.php`.
We will add a new root key to the `$CONFIG` dictionary named `objectstore`:
We will add a new root key to the `$CONFIG` dictionnary named `objectstore`:
```php
<?php
@@ -70,7 +68,7 @@ $CONFIG = array(
'hostname' => '127.0.0.1', // Can also be a domain name, eg. garage.example.com
'port' => 3900, // Put your reverse proxy port or your S3 API port
'use_ssl' => false, // Set it to true if you have a TLS enabled reverse proxy
'region' => 'garage', // Garage default region is named "garage", edit according to your cluster config
'region' => 'garage', // Garage has only one region named "garage"
'use_path_style' => true // Garage supports only path style, must be set to true
],
],
@@ -81,53 +79,6 @@ To test your new configuration, just reload your Nextcloud webpage and start sen
*External link:* [Nextcloud Documentation > Primary Storage](https://docs.nextcloud.com/server/latest/admin_manual/configuration_files/primary_storage.html)
#### SSE-C encryption (since Garage v1.0)
Since version 1.0, Garage supports server-side encryption with customer keys
(SSE-C). In this mode, Garage is responsible for encrypting and decrypting
objects, but it does not store the encryption key itself. The encryption key
should be provided by Nextcloud upon each request. This mode of operation is
supported by Nextcloud and it has successfully been tested together with
Garage.
To enable SSE-C encryption:
1. Make sure your Garage server is accessible via SSL through a reverse proxy
such as Nginx, and that it is using a valid public certificate (Nextcloud
might be able to connect to an S3 server that is using a self-signed
certificate, but you will lose many hours while trying, so don't).
Configure values for `use_ssl` and `port` accordingly in your `config.php`
file.
2. Generate an encryption key using the following command:
```
openssl rand -base64 32
```
Make sure to keep this key **secret**!
3. Add the encryption key in your `config.php` file as follows:
```php
<?php
$CONFIG = array(
'objectstore' => [
'class' => '\\OC\\Files\\ObjectStore\\S3',
'arguments' => [
...
'sse_c_key' => 'exampleencryptionkeyLbU+5fKYQcVoqnn+RaIOXgo=',
...
],
],
```
Nextcloud will now make Garage encrypt files at rest in the storage bucket.
These files will not be readable by an S3 client that has credentials to the
bucket but doesn't also know the secret encryption key.
### External Storage
**From the GUI.** Activate the "External storage support" app from the "Applications" page (click on your account icon on the top right corner of your screen to display the menu). Go to your parameters page (also located below your account icon). Click on external storage (or the corresponding translation in your language).
@@ -136,7 +87,7 @@ bucket but doesn't also know the secret encryption key.
*Click on the picture to zoom*
Add a new external storage. Put what you want in "folder name" (eg. "shared"). Select "Amazon S3". Keep "Access Key" for the Authentication field.
In Configuration, put your bucket name (eg. nextcloud), the host (eg. 127.0.0.1), the port (eg. 3900 or 443), the region ("garage" if you use the default, or the one your configured in your `garage.toml`). Tick the SSL box if you have put an HTTPS proxy in front of garage. You must tick the "Path access" box and you must leave the "Legacy authentication (v2)" box empty. Put your Key ID (eg. GK...) and your Secret Key in the last two input boxes. Finally click on the tick symbol on the right of your screen.
In Configuration, put your bucket name (eg. nextcloud), the host (eg. 127.0.0.1), the port (eg. 3900 or 443), the region (garage). Tick the SSL box if you have put an HTTPS proxy in front of garage. You must tick the "Path access" box and you must leave the "Legacy authentication (v2)" box empty. Put your Key ID (eg. GK...) and your Secret Key in the last two input boxes. Finally click on the tick symbol on the right of your screen.
Now go to your "Files" app and a new "linked folder" has appeared with the name you chose earlier (eg. "shared").
@@ -187,15 +138,15 @@ a reasonable trade-off for some instances.
Create a key for Peertube:
```bash
garage key create peertube-key
garage key new --name peertube-key
```
Keep the Key ID and the Secret key in a pad, they will be needed later.
We need two buckets, one for normal videos (named peertube-videos) and one for webtorrent videos (named peertube-playlists).
We need two buckets, one for normal videos (named peertube-video) and one for webtorrent videos (named peertube-playlist).
```bash
garage bucket create peertube-videos
garage bucket create peertube-playlists
garage bucket create peertube-video
garage bucket create peertube-playlist
```
Now we allow our key to read and write on these buckets:
@@ -239,7 +190,7 @@ object_storage:
# Put localhost only if you have a garage instance running on that node
endpoint: 'http://localhost:3900' # or "garage.example.com" if you have TLS on port 443
# Garage default region is named "garage", edit according to your config
# Garage supports only one region for now, named garage
region: 'garage'
credentials:
@@ -254,7 +205,7 @@ object_storage:
proxify_private_files: false
streaming_playlists:
bucket_name: 'peertube-playlists'
bucket_name: 'peertube-playlist'
# Keep it empty for our example
prefix: ''
@@ -264,7 +215,7 @@ object_storage:
# Same settings but for webtorrent videos
videos:
bucket_name: 'peertube-videos'
bucket_name: 'peertube-video'
prefix: ''
# You must fill this field to make Peertube use our reverse proxy/website logic
base_url: 'http://peertube-videos.web.garage.localhost'
@@ -293,7 +244,7 @@ with average object size ranging from 50 KB to 150 KB.
As such, your Garage cluster should be configured appropriately for good performance:
- use Garage v0.8.0 or higher with the [LMDB database engine](@documentation/reference-manual/configuration.md#db-engine-since-v0-8-0).
Older versions of Garage used the Sled database engine which had issues, such as databases quickly ending up taking tens of GB of disk space.
With the default Sled database engine, your database could quickly end up taking tens of GB of disk space.
- the Garage database should be stored on a SSD
### Creating your bucket
@@ -301,7 +252,7 @@ As such, your Garage cluster should be configured appropriately for good perform
This is the usual Garage setup:
```bash
garage key create mastodon-key
garage key new --name mastodon-key
garage bucket create mastodon-data
garage bucket allow mastodon-data --read --write --key mastodon-key
```
@@ -336,7 +287,6 @@ From the [official Mastodon documentation](https://docs.joinmastodon.org/admin/t
```bash
$ RAILS_ENV=production bin/tootctl media remove --days 3
$ RAILS_ENV=production bin/tootctl media remove --days 15 --prune-profiles
$ RAILS_ENV=production bin/tootctl media remove-orphans
$ RAILS_ENV=production bin/tootctl preview_cards remove --days 15
```
@@ -355,6 +305,8 @@ Imports: 1.7 KB
Settings: 0 Bytes
```
Unfortunately, [old avatars and headers cannot currently be cleaned up](https://github.com/mastodon/mastodon/issues/9567).
### Migrating your data
Data migration should be done with an efficient S3 client.
@@ -413,7 +365,7 @@ mc mirror --newer-than "3h" ./public/system/ garage/mastodon-data
## Matrix
Matrix is a chat communication protocol. Its main stable server implementation, [Synapse](https://matrix-org.github.io/synapse/latest/), provides a module to store media on a S3 backend. Additionally, a server independent media store supporting S3 has been developed by the community, it has been made possible thanks to how the matrix API has been designed and will work with implementations like Conduit, Dendrite, etc.
Matrix is a chat communication protocol. Its main stable server implementation, [Synapse](https://matrix-org.github.io/synapse/latest/), provides a module to store media on a S3 backend. Additionally, a server independent media store supporting S3 has been developped by the community, it has been made possible thanks to how the matrix API has been designed and will work with implementations like Conduit, Dendrite, etc.
### synapse-s3-storage-provider (synapse only)
@@ -426,7 +378,7 @@ Supposing you have a working synapse installation, you can add the module with p
Now create a bucket and a key for your matrix instance (note your Key ID and Secret Key somewhere, they will be needed later):
```bash
garage key create matrix-key
garage key new --name matrix-key
garage bucket create matrix
garage bucket allow matrix --read --write --key matrix-key
```
@@ -442,7 +394,7 @@ media_storage_providers:
store_synchronous: True # do we want to wait that the file has been written before returning?
config:
bucket: matrix # the name of our bucket, we chose matrix earlier
region_name: garage # "garage" by default, edit according to your cluster config
region_name: garage # only "garage" is supported for the region field
endpoint_url: http://localhost:3900 # the path to the S3 endpoint
access_key_id: "GKxxx" # your Key ID
secret_access_key: "xxxx" # your Secret Key
@@ -450,7 +402,7 @@ media_storage_providers:
Note that uploaded media will also be stored locally and this behavior can not be deactivated, it is even required for
some operations like resizing images.
In fact, your local filesystem is considered as a cache but without any automated way to garbage collect it.
In fact, your local filesysem is considered as a cache but without any automated way to garbage collect it.
We can build our garbage collector with `s3_media_upload`, a tool provided with the module.
If you installed the module with the command provided before, you should be able to bring it in your path:
@@ -468,7 +420,7 @@ Now we can write a simple script (eg `~/.local/bin/matrix-cache-gc`):
## CONFIGURATION ##
AWS_ACCESS_KEY_ID=GKxxx
AWS_SECRET_ACCESS_KEY=xxxx
AWS_ENDPOINT_URL=http://localhost:3900
S3_ENDPOINT=http://localhost:3900
S3_BUCKET=matrix
MEDIA_STORE=/var/lib/matrix-synapse/media
PG_USER=matrix
@@ -489,7 +441,7 @@ EOF
s3_media_upload update-db 1d
s3_media_upload --no-progress check-deleted $MEDIA_STORE
s3_media_upload --no-progress upload $MEDIA_STORE $S3_BUCKET --delete --endpoint-url $AWS_ENDPOINT_URL
s3_media_upload --no-progress upload $MEDIA_STORE $S3_BUCKET --delete --endpoint-url $S3_ENDPOINT
```
This script will list all the medias that were not accessed in the 24 hours according to your database.
@@ -522,232 +474,13 @@ And add a new line. For example, to run it every 10 minutes:
*External link:* [matrix-media-repo Documentation > S3](https://docs.t2bot.io/matrix-media-repo/configuration/s3-datastore.html)
## ejabberd
ejabberd is an XMPP server implementation which, with the `mod_s3_upload`
module in the [ejabberd-contrib](https://github.com/processone/ejabberd-contrib)
repository, can be integrated to store chat media files in Garage.
For uploads, this module leverages presigned URLs - this allows XMPP clients to
directly send media to Garage. Receiving clients then retrieve this media
through the [static website](@/documentation/cookbook/exposing-websites.md)
functionality.
As the data itself is publicly accessible to someone with knowledge of the
object URL - users are recommended to use
[E2EE](@/documentation/cookbook/encryption.md) to protect this data-at-rest
from unauthorized access.
Install the module with:
```bash
ejabberdctl module_install mod_s3_upload
```
Create the required key and bucket with:
```bash
garage key new --name ejabberd
garage bucket create objects.xmpp-server.fr
garage bucket allow objects.xmpp-server.fr --read --write --key ejabberd
garage bucket website --allow objects.xmpp-server.fr
```
The module can then be configured with:
```
mod_s3_upload:
#bucket_url: https://objects.xmpp-server.fr.my-garage-instance.mydomain.tld
bucket_url: https://my-garage-instance.mydomain.tld/objects.xmpp-server.fr
access_key_id: GK...
access_key_secret: ...
region: garage
download_url: https://objects.xmpp-server.fr
```
Other configuration options can be found in the
[configuration YAML file](https://github.com/processone/ejabberd-contrib/blob/master/mod_s3_upload/conf/mod_s3_upload.yml).
## Ente
Ente is an alternative for Google Photos and Apple Photos. It [can be selfhosted](https://help.ente.io/self-hosting/) and is working fine with Garage as of May 2024.
As a first step we need to create a bucket and a key for Ente:
```bash
garage bucket create ente
garage key create ente-key
# For the CORS setup to work, the key needs to be --owner as well, at least temporarily.
garage bucket allow ente --read --write --owner --key ente-key
```
We also need to setup some CORS rules to allow the Ente frontend to access the bucket:
```bash
export CORS='{"CORSRules":[{"AllowedHeaders":["*"],"AllowedMethods":["GET", "PUT", "POST", "DELETE"],"AllowedOrigins":["*"], "ExposeHeaders":["ETag"]}]}'
aws s3api put-bucket-cors --bucket ente --cors-configuration $CORS
```
Now we need to configure ente-server to use our bucket. This is explained [in the Ente S3 documentation](https://help.ente.io/self-hosting/guides/external-s3).
Prepare a configuration file for ente's backend as `museum.yaml`:
```yaml
credentials-file: /credentials.yaml
apps:
public-albums: https://albums.example.tld # If you want to use the share album feature
internal:
hardcoded-ott:
local-domain-suffix: "@example.com" # Your domain
local-domain-value: 123456 # Custom One-Time Password since we are not sending mail by default
key:
# WARNING -- You MUST CHANGE the values below
# Someone has made an image that can do it for you : https://github.com/EdyTheCow/ente-selfhost/blob/main/images/ente-server-tools/Dockerfile
# Simply build it yourself or run docker run --rm ghcr.io/edythecow/ente-server-tools go run tools/gen-random-keys/main.go
encryption: yvmG/RnzKrbCb9L3mgsmoxXr9H7i2Z4qlbT0mL3ln4w= # CHANGE THIS VALUE
hash: KXYiG07wC7GIgvCSdg+WmyWdXDAn6XKYJtp/wkEU7x573+byBRAYtpTP0wwvi8i/4l37uicX1dVTUzwH3sLZyw== # CHANGE THIS VALUE
jwt:
secret: i2DecQmfGreG6q1vBj5tCokhlN41gcfS2cjOs9Po-u8= # CHANGE THIS VALUE
```
The full configuration file can be found [here](https://github.com/ente-io/ente/blob/main/server/configurations/local.yaml)
Then prepare a credentials file as `credentials.yaml`
```yaml
db:
host: postgres
port: 5432
name: <ente_db_name>
user: <pguser>
password: <pgpass>
s3:
# Override the primary and secondary hot storage. The commented out values
# are the defaults.
#
hot_storage:
primary: b2-eu-cen
# secondary: wasabi-eu-central-2-v3
# If true, enable some workarounds to allow us to use a local minio instance
# for object storage.
#
# 1. Disable SSL.
# 2. Use "path" style S3 URLs (see `use_path_style_urls` below).
# 3. Directly download the file during replication instead of going via the
# Cloudflare worker.
# 4. Do not specify storage classes when uploading objects (since minio does
# not support them, specifically it doesn't support GLACIER).
are_local_buckets: true
# To use "path" style S3 URLs instead of DNS-based bucket access
# default to true if you set "are_local_buckets: true"
# use_path_style_urls: true
b2-eu-cen: # Don't change this key, it is hardcoded
key: <keyID>
secret: <keySecret>
endpoint: garage:3900 # publicly accessible endpoint of your garage instance
region: garage
bucket: <yourbucketName>
use_path_style: true
# you can specify secondary locations, names are hardcoded as well
# wasabi-eu-central-2-v3:
# scw-eu-fr-v3:
# and you can also specify a bucket to be used for embeddings, preview etc..
# default to the first bucket
# derived-storage: wasabi-eu-central-2-derived
```
Finally you can run it with Docker :
```bash
docker run -d --name ente-server --restart unless-stopped -v /path/to/museum.yaml:/museum.yaml -v /path/to/credentials.yaml:/credentials.yaml -p 8080:8080 ghcr.io/ente-io/ente-server
```
For more information on deployment you can check the [ente documentation](https://help.ente.io/self-hosting/)
## Pixelfed
[Pixelfed Technical Documentation > Configuration](https://docs.pixelfed.org/technical-documentation/env.html#filesystem)
## Pleroma
### Creating your bucket
This is the usual Garage setup:
```bash
garage key new --name pleroma-key
garage bucket create pleroma
garage bucket allow pleroma --read --write --owner --key pleroma-key
```
We also need to expose these buckets publicly to serve their content to users:
```bash
garage bucket website --allow pleroma
```
Note the Key ID and Secret Key.
### Configure Pleroma
Update your Pleroma configuration like that in `/etc/pleroma/config.exs`.
```
config :pleroma, Pleroma.Upload,
uploader: Pleroma.Uploaders.S3,
base_url: "https://pleroma.garage.example.tld"
config :ex_aws, :s3,
access_key_id: "GW...",
secret_access_key: "XXX",
region: "garage",
host: "api.garage.example.tld"
```
And restart Pleroma.
You can found more information in [Pleroma Documentation > Pleroma.Uploaders.S3](https://docs-develop.pleroma.social/backend/configuration/cheatsheet/#pleromauploaderss3)
### Migrating your data
Pleroma have an internal migration tool that can encounter some fatal error
```
** (EXIT from #PID<0.98.0>) an exception was raised:
** (File.Error) could not stream "/var/lib/pleroma/uploads/09/f8": illegal operation on a directory
(elixir 1.17.3) lib/file/stream.ex:100: anonymous fn/3 in Enumerable.File.Stream.reduce/3
(elixir 1.17.3) lib/stream.ex:1675: anonymous fn/5 in Stream.resource/3
(elixir 1.17.3) lib/stream.ex:1891: Enumerable.Stream.do_each/4
(elixir 1.17.3) lib/task/supervised.ex:370: Task.Supervised.stream_reduce/7
(elixir 1.17.3) lib/enum.ex:4423: Enum.map/2
(ex_aws_s3 2.5.8) lib/ex_aws/s3/upload.ex:141: ExAws.Operation.ExAws.S3.Upload.perform/2
(pleroma 2.10.0) lib/pleroma/uploaders/s3.ex:60: Pleroma.Uploaders.S3.put_file/1
(pleroma 2.10.0) lib/pleroma/uploaders/uploader.ex:49: Pleroma.Uploaders.Uploader.put_file/2
```
So, use [your best tool](https://garagehq.deuxfleurs.fr/documentation/connect/cli/) to sync `/var/lib/pleroma/uploads/` in your S3.
Then, to avoid some non existent problem (just in case of), run this command
```bash
while true
do
rm -vr $(./bin/pleroma_ctl uploads migrate_local S3 2>&1 | grep "could not stream" | awk -F '"' '{print $2}')
sleep 5
done
```
If you have many files, stop this command sometime and the command bellow (interactive) to delete local
file after upload. Then restart the loop.
```bash
./bin/pleroma_ctl uploads migrate_local S3 --delete
```
And *voilà*
[Pleroma Documentation > Pleroma.Uploaders.S3](https://docs-develop.pleroma.social/backend/configuration/cheatsheet/#pleromauploaderss3)
## Lemmy
@@ -806,7 +539,7 @@ secret_key = 'abcdef0123456789...'
```
PICTRS__STORE__TYPE=object_storage
PICTRS__STORE__ENDPOINT=http://my-garage-instance.mydomain.tld:3900
PICTRS__STORE__ENDPOINT=http:/my-garage-instance.mydomain.tld:3900
PICTRS__STORE__BUCKET_NAME=pictrs-data
PICTRS__STORE__REGION=garage
PICTRS__STORE__ACCESS_KEY=GK...
+3 -60
View File
@@ -54,9 +54,9 @@ how to configure this.
Create your key and bucket:
```bash
garage key create my-key
garage bucket create backups
garage bucket allow backups --read --write --key my-key
garage key new my-key
garage bucket create backup
garage bucket allow backup --read --write --key my-key
```
Then register your Key ID and Secret key in your environment:
@@ -105,7 +105,6 @@ restic restore 79766175 --target /var/lib/postgresql
Restic has way more features than the ones presented here.
You can discover all of them by accessing its documentation from the link below.
Files on Android devices can also be backed up with [restic-android](https://github.com/lhns/restic-android).
*External links:* [Restic Documentation > Amazon S3](https://restic.readthedocs.io/en/stable/030_preparing_a_new_repo.html#amazon-s3)
@@ -161,59 +160,3 @@ kopia repository validate-provider
You can then run all the standard kopia commands: `kopia snapshot create`, `kopia mount`...
Everything should work out-of-the-box.
## Plakar
Create your key and bucket on Garage server:
```bash
garage key create my-plakar-key
garage bucket create plakar-backups
garage bucket allow plakar-backups --read --write --key my-plakar-key
```
On Plakar server, add your Garage as a storage location:
```bash
plakar store add garageS3 s3://my-garage.tld/plakar-backups \
region=garage # Or as you've specified in garage.toml \
access_key=<Key ID from "garage key info my-plakar-key"> \
secret_access_key=<Secret key from "garage key info my-plakar-key">
```
Then create the repository.
```bash
plakar at @garageS3 create -plaintext # Unencrypted
# or
plakar at @garageS3 create #encrypted
```
If you encrypt your backups (Plakar default), you will need to define a strong passphrase. Do not forget to save your password safely. It will be needed to decrypt your backups.
After the repository has been created, check that everything works as expected (that might give an empty result as no file has been added yet, but no error message):
```bash
plakar at @garageS3 check
```
Now that everything is configure, you can use Garage as your backups storage. For instance sync it with a local backup storage:
```bash
$ plakar at ~/backups sync to @garageS3
```
Or list the S3 storage content:
```bash
$ plakar at @garageS3 ls
```
More information in Plakar documentation: https://www.plakar.io/docs/main/quickstart/
## Synology HyperBackup
HyperBackup can be configured to upload backups to garage using a custom S3 destination. However, the HyperBackup client hardcodes the `us-east-1` region that is a critical input to the v4 signature process. If garage is not set to `us-east-1`, HyperBackup will recognize available buckets, but fail during the final setup stage.
In garage.toml:
```toml
[s3_api]
s3_region = "us-east-1"
```
+56 -20
View File
@@ -41,7 +41,7 @@ Some commands:
# list buckets
mc ls garage/
# list objects in a bucket
# list objets in a bucket
mc ls garage/my_files
# copy from your filesystem to garage
@@ -70,17 +70,16 @@ Then a file named `~/.aws/config` and put:
```toml
[default]
region=garage
endpoint_url=http://127.0.0.1:3900
```
Now, supposing Garage is listening on `http://127.0.0.1:3900`, you can list your buckets with:
```bash
aws s3 ls
aws --endpoint-url http://127.0.0.1:3900 s3 ls
```
If you're using awscli `<1.29.0` or `<2.13.0`, you need to pass `--endpoint-url` to each CLI invocation explicitly.
As a workaround, you can redefine the aws command by editing the file `~/.bashrc` in this case:
Passing the `--endpoint-url` parameter to each command is annoying but AWS developers do not provide a corresponding configuration entry.
As a workaround, you can redefine the aws command by editing the file `~/.bashrc`:
```
function aws { command aws --endpoint-url http://127.0.0.1:3900 $@ ; }
@@ -149,15 +148,6 @@ rclone help
This will tremendously accelerate operations such as `rclone sync` or `rclone ncdu` by reducing the number
of ListObjects calls that are made.
**Garage behind Cloudflare proxy:** when running Garage behind Cloudflare proxy, you might see `Response: error 403 Forbidden, Forbidden: Invalid signature` error in your garage logs or `AccessDenied: Forbidden: Invalid signature` error in rclone logs. Try adding `--s3-sign-accept-encoding=false` flag to your rclone command and see if the issue is resolved.
```bash
# this throws an error
rclone lsd garage:
# this should work
rclone lsd --s3-sign-accept-encoding=false garage:
```
## `s3cmd`
@@ -212,13 +202,58 @@ See its usage output for other commands available.
## Cyberduck & duck {#cyberduck}
Both Cyberduck (the GUI) and duck (the CLI) have a concept of "Connection Profiles" that contain some presets for a specific provider.
We wrote the following connection profile for Garage:
Within Cyberduck, a
[Garage connection profile](https://docs.cyberduck.io/protocols/s3/garage/) is
available within the `Preferences -> Profiles` section. This can enabled and
then connections to Garage may be configured.
```xml
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>Protocol</key>
<string>s3</string>
<key>Vendor</key>
<string>garage</string>
<key>Scheme</key>
<string>https</string>
<key>Description</key>
<string>GarageS3</string>
<key>Default Hostname</key>
<string>127.0.0.1</string>
<key>Default Port</key>
<string>4443</string>
<key>Hostname Configurable</key>
<false/>
<key>Port Configurable</key>
<false/>
<key>Username Configurable</key>
<true/>
<key>Username Placeholder</key>
<string>Access Key ID (GK...)</string>
<key>Password Placeholder</key>
<string>Secret Key</string>
<key>Properties</key>
<array>
<string>s3service.disable-dns-buckets=true</string>
</array>
<key>Region</key>
<string>garage</string>
<key>Regions</key>
<array>
<string>garage</string>
</array>
</dict>
</plist>
```
### Instructions for the CLI
*Note: If your garage instance is configured with vhost access style, you can remove `s3service.disable-dns-buckets=true`.*
### Instructions for the GUI
Copy the connection profile, and save it anywhere as `garage.cyberduckprofile`.
Then find this file with your file explorer and double click on it: Cyberduck will open a connection wizard for this profile.
Simply follow the wizard and you should be done!
### Instuctions for the CLI
To configure duck (Cyberduck's CLI tool), start by creating its folder hierarchy:
@@ -268,7 +303,7 @@ duck --delete garage:/my-files/an-object.txt
## WinSCP (libs3) {#winscp}
*You can find instructions on how to use the GUI in french [in our wiki](https://guide.deuxfleurs.fr/prise_en_main/winscp/).*
*You can find instructions on how to use the GUI in french [in our wiki](https://wiki.deuxfleurs.fr/fr/Guide/Garage/WinSCP).*
How to use `winscp.com`, the CLI interface of WinSCP:
@@ -323,3 +358,4 @@ ls
```
And through the web interface at http://[::1]:8080/web/client
+6 -4
View File
@@ -17,13 +17,13 @@ Garage can also help you serve this content.
## Gitea
You can use Garage with Gitea to store your [git LFS](https://git-lfs.github.com/) data, your users' avatar, and their attachments.
You can use Garage with Gitea to store your [git LFS](https://git-lfs.github.com/) data, your users' avatar, and their attachements.
You can configure a different target for each data type (check `[lfs]` and `[attachment]` sections of the Gitea documentation) and you can provide a default one through the `[storage]` section.
Let's start by creating a key and a bucket (your key id and secret will be needed later, keep them somewhere):
```bash
garage key create gitea-key
garage key new --name gitea-key
garage bucket create gitea
garage bucket allow gitea --read --write --key gitea-key
```
@@ -118,7 +118,7 @@ through another support, like a git repository.
As a first step, we will need to create a bucket on Garage and enabling website access on it:
```bash
garage key create nix-key
garage key new --name nix-key
garage bucket create nix.example.com
garage bucket allow nix.example.com --read --write --key nix-key
garage bucket website nix.example.com --allow
@@ -201,9 +201,11 @@ on the binary cache, the client will download the result from the cache instead
### Channels
Channels additionally serve Nix definitions, ie. a `.nix` file referencing
Channels additionnaly serve Nix definitions, ie. a `.nix` file referencing
all the derivations you want to serve.
## Gitlab
*External link:* [Gitlab Documentation > Object storage](https://docs.gitlab.com/ee/administration/object_storage.html)
+5 -1
View File
@@ -1,7 +1,7 @@
+++
title="Cookbook"
template = "documentation.html"
weight = 20
weight = 2
sort_by = "weight"
+++
@@ -37,3 +37,7 @@ This chapter could also be referred as "Tutorials" or "Best practices".
- **[Monitoring Garage](@/documentation/cookbook/monitoring.md)** This page
explains the Prometheus metrics available for monitoring the Garage
cluster/nodes.
- **[Recovering from failures](@/documentation/cookbook/recovering.md):** Garage's first selling point is resilience
to hardware failures. This section explains how to recover from such a failure in the
best possible way.
+12 -24
View File
@@ -8,18 +8,18 @@ have published Ansible roles. We list them and compare them below.
## Comparison of Ansible roles
| Feature | [ansible-role-garage](#zorun-ansible-role-garage) | [garage-docker-ansible-deploy](#moan0s-garage-docker-ansible-deploy) | [eddster2309 ansible-role-garage](#eddster2309-ansible-role-garage) |
|------------------------------------|---------------------------------------------|---------------------------------------------------------------|---------------------------------|
| **Runtime** | Systemd | Docker | Systemd |
| **Target OS** | Any Linux | Any Linux | Any Linux |
| **Architecture** | amd64, arm64, i686 | amd64, arm64 | arm64, arm, 386, amd64 |
| **Additional software** | None | Traefik | Nginx and Keepalived (optional) |
| **Automatic node connection** | ❌ | ✅ | ✅ |
| **Layout management** | ❌ | ✅ | ✅ |
| **Manage buckets & keys** | ❌ | ✅ (basic) | ✅ |
| **Allow custom Garage config** | ✅ | ❌ | ❌ |
| **Facilitate Garage upgrades** | ✅ | ❌ | ✅ |
| **Multiple instances on one host** | ✅ | ✅ | ❌ |
| Feature | [ansible-role-garage](#zorun-ansible-role-garage) | [garage-docker-ansible-deploy](#moan0s-garage-docker-ansible-deploy) |
|------------------------------------|---------------------------------------------|---------------------------------------------------------------|
| **Runtime** | Systemd | Docker |
| **Target OS** | Any Linux | Any Linux |
| **Architecture** | amd64, arm64, i686 | amd64, arm64 |
| **Additional software** | None | Traefik |
| **Automatic node connection** | ❌ | ✅ |
| **Layout management** | ❌ | ✅ |
| **Manage buckets & keys** | ❌ | ✅ (basic) |
| **Allow custom Garage config** | ✅ | ❌ |
| **Facilitate Garage upgrades** | ✅ | ❌ |
| **Multiple instances on one host** | ✅ | ✅ |
## zorun/ansible-role-garage
@@ -49,15 +49,3 @@ structured DNS names, etc).
As a result, this role makes it easier to start with Garage on Ansible,
but is less flexible.
## eddster2309/ansible-role-garage
[Source code](https://github.com/eddster2309/ansible-role-garage), [Ansible galaxy](https://galaxy.ansible.com/ui/standalone/roles/eddster2309/garage/)
This role is a opinionated but customisable role using the official Garage
static binaries and only requires Systemd. As such it should work on any
Linux based host. It includes all the nesscary configuration to
automatically setup a clustered Garage deployment. Most Garage
configuration options are exposed through Ansible variables so while you
can't provide a custom config you can get very close. It can optionally
installed a HA nginx deployment with Keepalived.
+2 -26
View File
@@ -7,31 +7,13 @@ Garage is also available in binary packages on:
## Alpine Linux
If you use Alpine Linux, you can simply install the
[garage](https://pkgs.alpinelinux.org/packages?name=garage) package from the
Alpine Linux repositories (available since v3.17):
```bash
apk add garage
apk install garage
```
The default configuration file is installed to `/etc/garage/garage.toml`. You can run
Garage using: `rc-service garage start`.
If you don't specify `rpc_secret`, it will be automatically replaced with a random string on the first start.
Please note that this package is built without Consul discovery, Kubernetes
discovery, OpenTelemetry exporter, and K2V features (K2V will be enabled once
it's stable).
## Arch Linux
Garage is available in the official repositories under [extra](https://archlinux.org/packages/extra/x86_64/garage).
```bash
pacman -S garage
```
Garage is available in the [AUR](https://aur.archlinux.org/packages/garage).
## FreeBSD
@@ -44,9 +26,3 @@ pkg install garage
```bash
nix-shell -p garage
```
## conda-forge
```bash
pixi global install garage
```
-139
View File
@@ -1,139 +0,0 @@
+++
title = "Encryption"
weight = 50
+++
Encryption is a recurring subject when discussing Garage.
Garage does not handle data encryption by itself, but many things can
already be done with Garage's current feature set and the existing ecosystem.
This page takes a high level approach to security in general and data encryption
in particular.
# Examining your need for encryption
- Why do you want encryption in Garage?
- What is your threat model? What are you fearing?
- A stolen HDD?
- A curious administrator?
- A malicious administrator?
- A remote attacker?
- etc.
- What services do you want to protect with encryption?
- An existing application? Which one? (eg. Nextcloud)
- An application that you are writing
- Any expertise you may have on the subject
This page explains what Garage provides, and how you can improve the situation by yourself
by adding encryption at different levels.
We would be very curious to know your needs and thougs about ideas such as
encryption practices and things like key management, as we want Garage to be a
serious base platform for the development of secure, encrypted applications.
Do not hesitate to come talk to us if you have any thoughts or questions on the
subject.
# Capabilities provided by Garage
## Traffic is encrypted between Garage nodes
RPCs between Garage nodes are encrypted. More specifically, contrary to many
distributed software, it is impossible in Garage to have clear-text RPC. We
use the [kuska handshake](https://github.com/Kuska-ssb/handshake) library which
implements a protocol that has been clearly reviewed, Secure ScuttleButt's
Secret Handshake protocol. This is why setting a `rpc_secret` is mandatory,
and that's also why your nodes have super long identifiers.
## HTTP API endpoints provided by Garage are in clear text
Adding TLS support built into Garage is not currently planned.
## Garage stores data in plain text on the filesystem or encrypted using customer keys (SSE-C)
For standard S3 API requests, Garage does not encrypt data at rest by itself.
For the most generic at rest encryption of data, we recommend setting up your
storage partitions on encrypted LUKS devices.
If you are developing your own client software that makes use of S3 storage,
we recommend implementing data encryption directly on the client side and never
transmitting plaintext data to Garage. This makes it easy to use an external
untrusted storage provider if necessary.
Garage does support [SSE-C
encryption](https://docs.aws.amazon.com/AmazonS3/latest/userguide/ServerSideEncryptionCustomerKeys.html),
an encryption mode of Amazon S3 where data is encrypted at rest using
encryption keys given by the client. The encryption keys are passed to the
server in a header in each request, to encrypt or decrypt data at the moment of
reading or writing. The server discards the key as soon as it has finished
using it for the request. This mode allows the data to be encrypted at rest by
Garage itself, but it requires support in the client software. It is also not
adapted to a model where the server is not trusted or assumed to be
compromised, as the server can easily know the encryption keys. Note however
that when using SSE-C encryption, the only Garage node that knows the
encryption key passed in a given request is the node to which the request is
directed (which can be a gateway node), so it is easy to have untrusted nodes
in the cluster as long as S3 API requests containing SSE-C encryption keys are
not directed to them.
Implementing automatic data encryption directly in Garage without client-side
management of keys (something like
[SSE-S3](https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingServerSideEncryption.html))
could make things simpler for end users that don't want to setup LUKS, but also
raises many more questions, especially around key management: for encryption of
data, where could Garage get the encryption keys from? If we encrypt data but
keep the keys in a plaintext file next to them, it's useless. We probably don't
want to have to manage secrets in Garage as it would be very hard to do in a
secure way. At the time of speaking, there are no plans to implement this in
Garage.
# Adding data encryption using external tools
## Encrypting traffic between a Garage node and your client
You have multiple options to have encryption between your client and a node:
- Setup a reverse proxy with TLS / ACME / Let's encrypt
- Setup a Garage gateway locally, and only contact the garage daemon on `localhost`
- Only contact your Garage daemon over a secure, encrypted overlay network such as Wireguard
## Encrypting data at rest
Protects against the following threats:
- Stolen HDD
Crucially, does not protect against malicious sysadmins or remote attackers that
might gain access to your servers.
Methods include full-disk encryption with tools such as LUKS.
## Encrypting data on the client side
Protects against the following threats:
- A honest-but-curious administrator
- A malicious administrator that tries to corrupt your data
- A remote attacker that can read your server's data
Implementations are very specific to the various applications. Examples:
- Matrix: uses the OLM protocol for E2EE of user messages. Media files stored
in Matrix are probably encrypted using symmetric encryption, with a key that is
distributed in the end-to-end encrypted message that contains the link to the object.
- XMPP: clients normally support either OMEMO / OpenPGP for the E2EE of user
messages. Media files are encrypted per
[XEP-0454](https://xmpp.org/extensions/xep-0454.html).
- Aerogramme: use the user's password as a key to decrypt data in the user's bucket
- Cyberduck: comes with support for
[Cryptomator](https://docs.cyberduck.io/cryptomator/) which allows users to
create client-side vaults to encrypt files in before they are uploaded to a
cloud storage endpoint.
+2 -2
View File
@@ -9,7 +9,7 @@ There are three methods to expose buckets as website:
1. using the PutBucketWebsite S3 API call, which is allowed for access keys that have the owner permission bit set
2. from the Garage CLI, by an administrator of the cluster
2. from the Garage CLI, by an adminstrator of the cluster
3. using the Garage administration API
@@ -38,7 +38,7 @@ Our website serving logic is as follow:
Now we need to infer the URL of your website through your bucket name.
Let assume:
- we set `root_domain = ".web.example.com"` in `garage.toml` ([ref](@/documentation/reference-manual/configuration.md#web_root_domain))
- we set `root_domain = ".web.example.com"` in `garage.toml` ([ref](@/documentation/reference-manual/configuration.md#root_domain))
- our bucket name is `garagehq.deuxfleurs.fr`.
Our bucket will be served if the Host field matches one of these 2 values (the port is ignored):
+8 -11
View File
@@ -20,12 +20,12 @@ sudo apt-get update
sudo apt-get install build-essential
```
## Building from source from the Forgejo repository
## Building from source from the Gitea repository
The primary location for Garage's source code is the
[Forgejo repository](https://git.deuxfleurs.fr/Deuxfleurs/garage),
[Gitea repository](https://git.deuxfleurs.fr/Deuxfleurs/garage),
which contains all of the released versions as well as the code
for the development of the next version.
for the developpement of the next version.
Clone the repository and enter it as follows:
@@ -41,7 +41,7 @@ git tag # List available tags
git checkout v0.8.0 # Change v0.8.0 with the version you wish to build
```
Otherwise you will be building a development build from the `main` branch
Otherwise you will be building a developpement build from the `main` branch
that includes all of the changes to be released in the next version.
Be careful that such a build might be unstable or contain bugs,
and could be incompatible with nodes that run stable versions of Garage.
@@ -85,14 +85,11 @@ The following feature flags are available in v0.8.0:
| Feature flag | Enabled | Description |
| ------------ | ------- | ----------- |
| `bundled-libs` | *by default* | Use bundled version of sqlite3, zstd, lmdb and libsodium |
| `consul-discovery` | optional | Enable automatic registration and discovery<br>of cluster nodes through the Consul API |
| `fjall` | experimental | Enable using Fjall to store Garage's metadata |
| `journald` | optional | Enable logging to systemd-journald with<br>`GARAGE_LOG_TO_JOURNALD=true` environment variable set |
| `system-libs` | optional | Use system version of sqlite3, zstd, lmdb and libsodium<br>if available (exclusive with `bundled-libs`, build using<br>`cargo build --no-default-features --features system-libs`) |
| `k2v` | optional | Enable the experimental K2V API (if used, all nodes on your<br>Garage cluster must have it enabled as well) |
| `kubernetes-discovery` | optional | Enable automatic registration and discovery<br>of cluster nodes through the Kubernetes API |
| `lmdb` | *by default* | Enable using LMDB to store Garage's metadata |
| `metrics` | *by default* | Enable collection of metrics in Prometheus format on the admin API |
| `sqlite` | *by default* | Enable using Sqlite3 to store Garage's metadata |
| `syslog` | optional | Enable logging to Syslog with<br>`GARAGE_LOG_TO_SYSLOG=true` environment variable set |
| `system-libs` | optional | Use system version of sqlite3, zstd, lmdb and libsodium<br>if available (exclusive with `bundled-libs`, build using<br>`cargo build --no-default-features --features system-libs`) |
| `telemetry-otlp` | optional | Enable collection of execution traces using OpenTelemetry |
| `sled` | *by default* | Enable using Sled to store Garage's metadata |
| `lmdb` | optional | Enable using LMDB to store Garage's metadata |
| `sqlite` | optional | Enable using Sqlite3 to store Garage's metadata |
+3 -69
View File
@@ -11,7 +11,7 @@ Firstly clone the repository:
```bash
git clone https://git.deuxfleurs.fr/Deuxfleurs/garage
cd garage/script/helm
cd garage/scripts/helm
```
Deploy with default options:
@@ -26,13 +26,6 @@ Or deploy with custom values:
helm install --create-namespace --namespace garage garage ./garage -f values.override.yaml
```
If you want to manage the CustomResourceDefinition used by garage for its `kubernetes_discovery` outside of the helm chart, add `garage.kubernetesSkipCrd: true` to your custom values and use the kustomization before deploying the helm chart:
```bash
kubectl apply -k ../k8s/crd
helm install --create-namespace --namespace garage garage ./garage -f values.override.yaml
```
After deploying, cluster layout must be configured manually as described in [Creating a cluster layout](@/documentation/quick-start/_index.md#creating-a-cluster-layout). Use the following command to access garage CLI:
```bash
@@ -47,12 +40,12 @@ All possible configuration values can be found with:
helm show values ./garage
```
This is an example `values.override.yaml` for deploying in a microk8s cluster with a https s3 api ingress route:
This is an example `values.overrride.yaml` for deploying in a microk8s cluster with a https s3 api ingress route:
```yaml
garage:
# Use only 2 replicas per object
replicationFactor: 2
replicationMode: "2"
# Start 4 instances (StatefulSets) of garage
deployment:
@@ -93,62 +86,3 @@ helm delete --namespace garage garage
```
Note that this will leave behind custom CRD `garagenodes.deuxfleurs.fr`, which must be removed manually if desired.
## Increase PVC size on running Garage instances
Since the Garage Helm chart creates the data and meta PVC based on `StatefulSet` templates, increasing the PVC size can be a bit tricky.
### Confirm the `StorageClass` used for Garage supports volume expansion
Confirm the storage class used for garage.
```bash
kubectl -n garage get pvc
NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS VOLUMEATTRIBUTESCLASS AGE
data-garage-0 Bound pvc-080360c9-8ce3-4acf-8579-1701e57b7f3f 30Gi RWO longhorn-local <unset> 77d
data-garage-1 Bound pvc-ab8ba697-6030-4fc7-ab3c-0d6df9e3dbc0 30Gi RWO longhorn-local <unset> 5d8h
data-garage-2 Bound pvc-3ab37551-0231-4604-986d-136d0fd950ec 30Gi RWO longhorn-local <unset> 5d5h
meta-garage-0 Bound pvc-3b457302-3023-4169-846e-c928c5f2ea65 3Gi RWO longhorn-local <unset> 77d
meta-garage-1 Bound pvc-49ace2b9-5c85-42df-9247-51c4cf64b460 3Gi RWO longhorn-local <unset> 5d8h
meta-garage-2 Bound pvc-99e2e50f-42b4-4128-ae2f-b52629259723 3Gi RWO longhorn-local <unset> 5d5h
```
In this case, the storage class is `longhorn-local`. Now, check if `ALLOWVOLUMEEXPANSION` is true for the used `StorageClass`.
```bash
kubectl get storageclasses.storage.k8s.io longhorn-local
NAME PROVISIONER RECLAIMPOLICY VOLUMEBINDINGMODE ALLOWVOLUMEEXPANSION AGE
longhorn-local driver.longhorn.io Delete Immediate true 103d
```
If your `StorageClass` does not support volume expansion, double check if you can enable it. Otherwise, your only real option is to spin up a new Garage cluster with increased size and migrate all data over.
If your `StorageClass` supports expansion, you are free to continue.
### Increase the size of the PVCs
Increase the size of all PVCs to your desired size.
```bash
kubectl -n garage edit pvc data-garage-0
kubectl -n garage edit pvc data-garage-1
kubectl -n garage edit pvc data-garage-2
kubectl -n garage edit pvc meta-garage-0
kubectl -n garage edit pvc meta-garage-1
kubectl -n garage edit pvc meta-garage-2
```
### Increase the size of the `StatefulSet` PVC template
This is an optional step, but if not done, future instances of Garage will be created with the original size from the template.
```bash
kubectl -n garage delete sts --cascade=orphan garage
statefulset.apps "garage" deleted
```
This will remove the Garage `StatefulSet` but leave the pods running. It may seem destructive but needs to be done this way since edits to the size of PVC templates are prohibited.
### Redeploy the `StatefulSet`
Now the size of future PVCs can be increased, and the Garage Helm chart can be upgraded. The new `StatefulSet` should take ownership of the orphaned pods again.
+6 -2
View File
@@ -18,7 +18,7 @@ api_bind_addr = "0.0.0.0:3903"
```
This will allow anyone to scrape Prometheus metrics by fetching
`http://localhost:3903/metrics`. If you want to restrict access
`http://localhost:3093/metrics`. If you want to restrict access
to the exported metrics, set the `metrics_token` configuration value
to a bearer token to be used when fetching the metrics endpoint.
@@ -49,5 +49,9 @@ add the following lines in your Prometheus scrape config:
To visualize the scraped data in Grafana,
you can either import our [Grafana dashboard for Garage](https://git.deuxfleurs.fr/Deuxfleurs/garage/raw/branch/main/script/telemetry/grafana-garage-dashboard-prometheus.json)
or make your own.
We detail below the list of exposed metrics and their meaning.
The list of exported metrics is available on our [dedicated page](@/documentation/reference-manual/monitoring.md) in the Reference manual section.
## List of exported metrics
See our [dedicated page](@/documentation/reference-manual/monitoring.md) in the Reference manual section.
+59 -81
View File
@@ -19,15 +19,14 @@ To run a real-world deployment, make sure the following conditions are met:
- You have at least three machines with sufficient storage space available.
- Each machine has an IP address which makes it directly reachable by all other machines.
In many cases, nodes will be behind a NAT and will not each have a public
IPv4 addresses. In this case, is recommended that you use IPv6 for this
end-to-end connectivity if it is available. Otherwise, using a mesh VPN such as
- Each machine has a public IP address which is reachable by other machines. It
is highly recommended that you use IPv6 for this end-to-end connectivity. If
IPv6 is not available, then using a mesh VPN such as
[Nebula](https://github.com/slackhq/nebula) or
[Yggdrasil](https://yggdrasil-network.github.io/) are approaches to consider
in addition to building out your own VPN tunneling.
- This guide will assume you are using Docker containers to deploy Garage on each node.
- This guide will assume you are using Docker containers to deploy Garage on each node.
Garage can also be run independently, for instance as a [Systemd service](@/documentation/cookbook/systemd.md).
You can also use an orchestrator such as Nomad or Kubernetes to automatically manage
Docker containers on a fleet of nodes.
@@ -43,7 +42,7 @@ For our example, we will suppose the following infrastructure with IPv6 connecti
| Brussels | Mars | fc00:F::1 | 1.5 TB |
Note that Garage will **always** store the three copies of your data on nodes at different
locations. This means that in the case of this small example, the usable capacity
locations. This means that in the case of this small example, the available capacity
of the cluster is in fact only 1.5 TB, because nodes in Brussels can't store more than that.
This also means that nodes in Paris and London will be under-utilized.
To make better use of the available hardware, you should ensure that the capacity
@@ -53,9 +52,9 @@ to store 2 TB of data in total.
### Best practices
- If you have reasonably fast networking between all your nodes, and are planing to store
mostly large files, bump the `block_size` configuration parameter to 10 MB
(`block_size = "10M"`).
- If you have fast dedicated networking between all your nodes, and are planing to store
very large files, bump the `block_size` configuration parameter to 10 MB
(`block_size = 10485760`).
- Garage stores its files in two locations: it uses a metadata directory to store frequently-accessed
small metadata items, and a data directory to store data blocks of uploaded objects.
@@ -68,42 +67,36 @@ to store 2 TB of data in total.
EXT4 is not recommended as it has more strict limitations on the number of inodes,
which might cause issues with Garage when large numbers of objects are stored.
- Servers with multiple HDDs are supported natively by Garage without resorting
to RAID, see [our dedicated documentation page](@/documentation/operations/multi-hdd.md).
- If you only have an HDD and no SSD, it's fine to put your metadata alongside the data
on the same drive. Having lots of RAM for your kernel to cache the metadata will
help a lot with performance. Make sure to use the LMDB database engine,
instead of Sled, which suffers from quite bad performance degradation on HDDs.
Sled is still the default for legacy reasons, but is not recommended anymore.
- For the metadata storage, Garage does not do checksumming and integrity
verification on its own, so it is better to use a robust filesystem such as
BTRFS or ZFS. Users have reported that when using the LMDB database engine
(the default), database files have a tendency of becoming corrupted after an
unclean shutdown (e.g. a power outage), so you should take regular snapshots
to be able to recover from such a situation. This can be done using Garage's
built-in automatic snapshotting (since v0.9.4), or by using filesystem level
snapshots. If you cannot do so, you might want to switch to Sqlite which is
more robust.
verification on its own. If you are afraid of bitrot/data corruption,
put your metadata directory on a BTRFS partition. Otherwise, just use regular
EXT4 or XFS.
- LMDB is the fastest and most tested database engine, but it has the following
weaknesses: 1/ data files are not architecture-independent, you cannot simply
move a Garage metadata directory between nodes running different architectures,
and 2/ LMDB is not suited for 32-bit platforms. Sqlite is a viable alternative
if any of these are of concern.
- If you only have an HDD and no SSD, it's fine to put your metadata alongside
the data on the same drive, but then consider your filesystem choice wisely
(see above). Having lots of RAM for your kernel to cache the metadata will
help a lot with performance. The default LMDB database engine is the most
tested and has good performance.
- Having a single server with several storage drives is currently not very well
supported in Garage ([#218](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/218)).
For an easy setup, just put all your drives in a RAID0 or a ZFS RAIDZ array.
If you're adventurous, you can try to format each of your disk as
a separate XFS partition, and then run one `garage` daemon per disk drive,
or use something like [`mergerfs`](https://github.com/trapexit/mergerfs) to merge
all your disks in a single union filesystem that spreads load over them.
## Get a Docker image
Our docker image is currently named `dxflrs/garage` and is stored on the [Docker Hub](https://hub.docker.com/r/dxflrs/garage/tags?page=1&ordering=last_updated).
We encourage you to use a fixed tag (eg. `v2.3.0`) and not the `latest` tag.
For this example, we will use the latest published version at the time of the writing which is `v2.3.0` but it's up to you
We encourage you to use a fixed tag (eg. `v0.8.0`) and not the `latest` tag.
For this example, we will use the latest published version at the time of the writing which is `v0.8.0` but it's up to you
to check [the most recent versions on the Docker Hub](https://hub.docker.com/r/dxflrs/garage/tags?page=1&ordering=last_updated).
For example:
```
docker pull dxflrs/garage:v2.3.0
sudo docker pull dxflrs/garage:v0.8.0
```
## Deploying and configuring Garage
@@ -126,9 +119,8 @@ A valid `/etc/garage.toml` for our cluster would look as follows:
metadata_dir = "/var/lib/garage/meta"
data_dir = "/var/lib/garage/data"
db_engine = "lmdb"
metadata_auto_snapshot_interval = "6h"
replication_factor = 3
replication_mode = "3"
compression_level = 2
@@ -152,8 +144,6 @@ Check the following for your configuration files:
- Make sure `rpc_public_addr` contains the public IP address of the node you are configuring.
This parameter is optional but recommended: if your nodes have trouble communicating with
one another, consider adding it.
Alternatively, you can also set `rpc_public_addr_subnet`, which can filter
the addresses announced to other peers to a specific subnet.
- Make sure `rpc_secret` is the same value on all nodes. It should be a 32-bytes hex-encoded secret key.
You can generate such a key with `openssl rand -hex 32`.
@@ -171,13 +161,12 @@ docker run \
-v /etc/garage.toml:/etc/garage.toml \
-v /var/lib/garage/meta:/var/lib/garage/meta \
-v /var/lib/garage/data:/var/lib/garage/data \
dxflrs/garage:v2.3.0
dxflrs/garage:v0.8.0
```
With this command line, Garage should be started automatically at each boot.
Please note that we use host networking as otherwise the network indirection
added by Docker would prevent Garage nodes from communicating with one another
(especially if using IPv6).
It should be restarted automatically at each reboot.
Please note that we use host networking as otherwise Docker containers
can not communicate with IPv6.
If you want to use `docker-compose`, you may use the following `docker-compose.yml` file as a reference:
@@ -185,7 +174,7 @@ If you want to use `docker-compose`, you may use the following `docker-compose.y
version: "3"
services:
garage:
image: dxflrs/garage:v2.3.0
image: dxflrs/garage:v0.8.0
network_mode: "host"
restart: unless-stopped
volumes:
@@ -194,14 +183,12 @@ services:
- /var/lib/garage/data:/var/lib/garage/data
```
If you wish to upgrade your cluster, make sure to read the corresponding
[documentation page](@/documentation/operations/upgrading.md) first, as well as
the documentation relevant to your version of Garage in the case of major
upgrades. With the containerized setup proposed here, the upgrade process
will require stopping and removing the existing container, and re-creating it
with the upgraded version.
Upgrading between Garage versions should be supported transparently,
but please check the relase notes before doing so!
To upgrade, simply stop and remove this container and
start again the command with a new version of Garage.
## Controlling the daemon
## Controling the daemon
The `garage` binary has two purposes:
- it acts as a daemon when launched with `garage server`
@@ -210,12 +197,6 @@ The `garage` binary has two purposes:
Ensure an appropriate `garage` binary (the same version as your Docker image) is available in your path.
If your configuration file is at `/etc/garage.toml`, the `garage` binary should work with no further change.
You can also use an alias as follows to use the Garage binary inside your docker container:
```bash
alias garage="docker exec -ti <container name> /garage"
```
You can test your `garage` CLI utility by running a simple command such as:
```bash
@@ -259,7 +240,7 @@ You can then instruct nodes to connect to one another as follows:
Venus$ garage node connect 563e1ac825ee3323aa441e72c26d1030d6d4414aeb3dd25287c531e7fc2bc95d@[fc00:1::1]:3901
```
You don't need to instruct all node to connect to all other nodes:
You don't nead to instruct all node to connect to all other nodes:
nodes will discover one another transitively.
Now if your run `garage status` on any node, you should have an output that looks as follows:
@@ -283,12 +264,12 @@ of a role that is assigned to each active cluster node.
For our example, we will suppose we have the following infrastructure
(Capacity, Identifier and Zone are specific values to Garage described in the following):
| Location | Name | Disk Space | Identifier | Zone (`-z`) | Capacity (`-c`) |
|----------|---------|------------|------------|-------------|-----------------|
| Paris | Mercury | 1 TB | `563e` | `par1` | `1T` |
| Paris | Venus | 2 TB | `86f0` | `par1` | `2T` |
| London | Earth | 2 TB | `6814` | `lon1` | `2T` |
| Brussels | Mars | 1.5 TB | `212f` | `bru1` | `1.5T` |
| Location | Name | Disk Space | `Capacity` | `Identifier` | `Zone` |
|----------|---------|------------|------------|--------------|--------------|
| Paris | Mercury | 1 TB | `10` | `563e` | `par1` |
| Paris | Venus | 2 TB | `20` | `86f0` | `par1` |
| London | Earth | 2 TB | `20` | `6814` | `lon1` |
| Brussels | Mars | 1.5 TB | `15` | `212f` | `bru1` |
#### Node identifiers
@@ -310,8 +291,6 @@ garage status
It will display the IP address associated with each node;
from the IP address you will be able to recognize the node.
We will now use the `garage layout assign` command to configure the correct parameters for each node.
#### Zones
Zones are simply a user-chosen identifier that identify a group of server that are grouped together logically.
@@ -321,29 +300,29 @@ In most cases, a zone will correspond to a geographical location (i.e. a datacen
Behind the scene, Garage will use zone definition to try to store the same data on different zones,
in order to provide high availability despite failure of a zone.
Zones are passed to Garage using the `-z` flag of `garage layout assign` (see below).
#### Capacity
Garage needs to know the storage capacity (disk space) it can/should use on
each node, to be able to correctly balance data.
Garage reasons on an abstract metric about disk storage that is named the *capacity* of a node.
The capacity configured in Garage must be proportional to the disk space dedicated to the node.
Capacity values are expressed in bytes and are passed to Garage using the `-c` flag of `garage layout assign` (see below).
Capacity values must be **integers** but can be given any signification.
Here we chose that 1 unit of capacity = 100 GB.
#### Tags
You can add additional tags to nodes using the `-t` flag of `garage layout assign` (see below).
Tags have no specific meaning for Garage and can be used at your convenience.
Note that the amount of data stored by Garage on each server may not be strictly proportional to
its capacity value, as Garage will priorize having 3 copies of data in different zones,
even if this means that capacities will not be strictly respected. For example in our above examples,
nodes Earth and Mars will always store a copy of everything each, and the third copy will
have 66% chance of being stored by Venus and 33% chance of being stored by Mercury.
#### Injecting the topology
Given the information above, we will configure our cluster as follow:
```bash
garage layout assign 563e -z par1 -c 1T -t mercury
garage layout assign 86f0 -z par1 -c 2T -t venus
garage layout assign 6814 -z lon1 -c 2T -t earth
garage layout assign 212f -z bru1 -c 1.5T -t mars
garage layout assign 563e -z par1 -c 10 -t mercury
garage layout assign 86f0 -z par1 -c 20 -t venus
garage layout assign 6814 -z lon1 -c 20 -t earth
garage layout assign 212f -z bru1 -c 15 -t mars
```
At this point, the changes in the cluster layout have not yet been applied.
@@ -353,7 +332,6 @@ To show the new layout that will be applied, call:
garage layout show
```
Make sure to read carefully the output of `garage layout show`.
Once you are satisfied with your new layout, apply it with:
```bash
@@ -361,7 +339,7 @@ garage layout apply
```
**WARNING:** if you want to use the layout modification commands in a script,
make sure to read [this page](@/documentation/operations/layout.md) first.
make sure to read [this page](@/documentation/reference-manual/layout.md) first.
## Using your Garage cluster
@@ -371,5 +349,5 @@ and is covered in the [quick start guide](@/documentation/quick-start/_index.md)
Remember also that the CLI is self-documented thanks to the `--help` flag and
the `help` subcommand (e.g. `garage help`, `garage key --help`).
Configuring S3-compatible applications to interact with Garage
Configuring S3-compatible applicatiosn to interact with Garage
is covered in the [Integrations](@/documentation/connect/_index.md) section.
@@ -1,11 +1,11 @@
+++
title = "Recovering from failures"
weight = 40
weight = 50
+++
Garage is meant to work on old, second-hand hardware.
In particular, this makes it likely that some of your drives will fail, and some manual intervention will be needed.
Fear not! Garage is fully equipped to handle drive failures, in most common cases.
Fear not! For Garage is fully equipped to handle drive failures, in most common cases.
## A note on availability of Garage
@@ -61,7 +61,7 @@ garage repair -a --yes blocks
This will re-synchronize blocks of data that are missing to the new HDD, reading them from copies located on other nodes.
You can check on the advancement of this process by doing the following command:
You can check on the advancement of this process by doing the following command:
```bash
garage stats -a
@@ -108,60 +108,3 @@ garage layout apply # once satisfied, apply the changes
Garage will then start synchronizing all required data on the new node.
This process can be monitored using the `garage stats -a` command.
## Replacement scenario 3: corrupted metadata {#corrupted_meta}
In some cases, your metadata DB file might become corrupted, for instance if
your node suffered a power outage and did not shut down properly. In this case,
you can recover without having to change the node ID and rebuilding a cluster
layout. This means that data blocks will not need to be shuffled around, you
must simply find a way to repair the metadata file. The best way is generally
to discard the corrupted file and recover it from another source.
First of all, start by locating the database file in your metadata directory,
which [depends on your `db_engine`
choice](@/documentation/reference-manual/configuration.md#db_engine). Then,
your recovery options are as follows:
- **Option 1: resyncing from other nodes.** In case your cluster is replicated
with two or three copies, you can simply delete the database file, and Garage
will resync from other nodes. To do so, stop Garage, delete the database file
or directory, and restart Garage. Then, do a full table repair by calling
`garage repair -a --yes tables`. This will take a bit of time to complete as
the new node will need to receive copies of the metadata tables from the
network.
- **Option 2: restoring a snapshot taken by Garage.** Since v0.9.4, Garage can
[automatically take regular
snapshots](@/documentation/reference-manual/configuration.md#metadata_auto_snapshot_interval)
of your metadata DB file. This file or directory should be located under
`<metadata_dir>/snapshots`, and is named according to the UTC time at which it
was taken. Stop Garage, discard the database file/directory and replace it by the
snapshot you want to use. For instance, in the case of LMDB:
```bash
cd $METADATA_DIR
mv db.lmdb db.lmdb.bak
cp -r snapshots/2024-03-15T12:13:52Z db.lmdb
```
And for Sqlite:
```bash
cd $METADATA_DIR
mv db.sqlite db.sqlite.bak
cp snapshots/2024-03-15T12:13:52Z db.sqlite
```
Then, restart Garage and run a full table repair by calling `garage repair -a
--yes tables`. This should run relatively fast as only the changes that
occurred since the snapshot was taken will need to be resynchronized. Of
course, if your cluster is not replicated, you will lose all changes that
occurred since the snapshot was taken.
- **Option 3: restoring a filesystem-level snapshot.** If you are using ZFS or
BTRFS to snapshot your metadata partition, refer to their specific
documentation on rolling back or copying files from an old snapshot.
Note that, depending on the properties of the filesystem and of the DB engine,
if these snapshots were taken during a write operation to the database, they may
also be corrupted and thus unfit for recovery.
+4 -144
View File
@@ -7,7 +7,7 @@ The main reason to add a reverse proxy in front of Garage is to provide TLS to y
In production you will likely need your certificates signed by a certificate authority.
The most automated way is to use a provider supporting the [ACME protocol](https://datatracker.ietf.org/doc/html/rfc8555)
such as [Let's Encrypt](https://letsencrypt.org/) or [ZeroSSL](https://zerossl.com/).
such as [Let's Encrypt](https://letsencrypt.org/), [ZeroSSL](https://zerossl.com/) or [Buypass Go SSL](https://www.buypass.com/ssl/products/acme).
If you are only testing Garage, you can generate a self-signed certificate to follow the documentation:
@@ -97,7 +97,7 @@ server {
location / {
proxy_pass http://s3_backend;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header Host $http_host;
proxy_set_header Host $host;
# Disable buffering to a temporary file.
proxy_max_temp_file_size 0;
}
@@ -142,74 +142,7 @@ server {
## Apache httpd
The [Apache HTTP Server](https://httpd.apache.org/)
is a general purpose web server that includes
[reverse proxy](https://httpd.apache.org/docs/2.4/mod/mod_proxy.html)
capabilities.
### Exposing the S3 endpoints
Create a new [virtual host](https://httpd.apache.org/docs/2.4/vhosts/),
obtain a certificate using
[certbot](https://eff-certbot.readthedocs.io/en/stable/using.html#apache),
and add the
[`ProxyPass`](https://httpd.apache.org/docs/2.4/mod/mod_proxy.html#proxypass)
and
[`ProxyPreserveHost`](https://httpd.apache.org/docs/2.4/mod/mod_proxy.html#proxypreservehost)
options:
```apache
<VirtualHost *:443>
ServerName garage.example.com
SSLCertificateFile /etc/letsencrypt/live/garage.example.com/fullchain.pem
SSLCertificateKeyFile /etc/letsencrypt/live/garage.example.com/privkey.pem
Include /etc/letsencrypt/options-ssl-apache.conf
Header always set Strict-Transport-Security "max-age=31536000"
Header always add Content-Security-Policy upgrade-insecure-requests
ProxyPass "/" "http://localhost:3900/" nocanon
ProxyPreserveHost on
</VirtualHost>
```
The `nocanon` keyword is important for
[presigned URLs](https://docs.aws.amazon.com/AmazonS3/latest/userguide/using-presigned-url.html);
otherwise,
> `mod_proxy` will canonicalise ProxyPassed URLs.
> But this may be incompatible with some backends,
> particularly those that make use of `PATH_INFO`.
> The optional `nocanon` keyword suppresses this
> and passes the URL path "raw" to the backend.
### Exposing the web endpoint
Adding static websites backed by Garage works very similarly,
with the only difference being the port selected in the `ProxyPass` directive.
```apache
ProxyPass "/" "http://localhost:3902/" nocanon
```
### Using Unix sockets
Apache can also proxy via Unix sockets instead of TCP ports,
if Garage is so configured.
`garage.toml`:
```toml
[s3_api]
api_bind_addr = "/run/garage/s3_api.socket"
```
Apache config:
```apache
ProxyPass "/" "unix:/run/garage/s3_api.socket|http://localhost/" nocanon
```
@TODO
## Traefik v2
@@ -339,7 +272,7 @@ Add the following configuration section [to compress response](https://doc.traef
### Add caching response
Traefik's caching middleware is only available on [enterprise version](https://doc.traefik.io/traefik-enterprise/middlewares/http-cache/), however the freely-available [Souin plugin](https://github.com/darkweak/souin#tr%C3%A6fik-container) can also do the job. (section to be completed)
Traefik's caching middleware is only available on [entreprise version](https://doc.traefik.io/traefik-enterprise/middlewares/http-cache/), however the freely-available [Souin plugin](https://github.com/darkweak/souin#tr%C3%A6fik-container) can also do the job. (section to be completed)
### Complete example
@@ -445,47 +378,6 @@ admin.garage.tld {
But at the same time, the `reverse_proxy` is very flexible.
For a production deployment, you should [read its documentation](https://caddyserver.com/docs/caddyfile/directives/reverse_proxy) as it supports features like DNS discovery of upstreams, load balancing with checks, streaming parameters, etc.
### Caching
Caddy can compiled with a
[cache plugin](https://github.com/caddyserver/cache-handler) which can be used
to provide a hot-cache at the webserver-level for static websites hosted by
Garage.
This can be configured as follows:
```caddy
# Caddy global configuration section
{
# Bare minimum configuration to enable cache.
order cache before rewrite
cache
#cache
# allowed_http_verbs GET
# default_cache_control public
# ttl 8h
#}
}
# Site specific section
https:// {
cache
#cache {
# timeout {
# backend 30s
# }
#}
reverse_proxy ...
}
```
Caching is a complicated subject, and the reader is encouraged to study the
available options provided by the plugin.
### On-demand TLS
Caddy supports a technique called
@@ -536,35 +428,3 @@ https:// {
reverse_proxy localhost:3902 192.168.1.2:3902 example.tld:3902
}
```
More information on how this endpoint is implemented in Garage is available
in the [Admin API Reference](@/documentation/reference-manual/admin-api.md) page.
### Fileserver browser
Caddy's built-in
[file_server](https://caddyserver.com/docs/caddyfile/directives/file_server)
browser functionality can be extended with the
[caddy-fs-s3](https://github.com/sagikazarmark/caddy-fs-s3) module.
This can be configured to use Garage as a backend with the following
configuration:
```caddy
browse.garage.tld {
file_server {
fs s3 {
bucket test-bucket
region garage
endpoint https://s3.garage.tld
use_path_style
}
browse
}
}
```
Caddy must also be configured with the required `AWS_ACCESS_KEY_ID` and
`AWS_SECRET_ACCESS_KEY` environment variables to access the bucket.
+1 -15
View File
@@ -28,26 +28,12 @@ StateDirectory=garage
DynamicUser=true
ProtectHome=true
NoNewPrivileges=true
LimitNOFILE=42000
[Install]
WantedBy=multi-user.target
```
**A note on hardening:** Garage will be run as a non privileged user, its user
id is dynamically allocated by systemd (set with `DynamicUser=true`). It cannot
access (read or write) home folders (`/home`, `/root` and `/run/user`), the
rest of the filesystem can only be read but not written, only the path seen as
`/var/lib/garage` is writable as seen by the service. Additionally, the process
can not gain new privileges over time.
For this to work correctly, your `garage.toml` must be set with
`metadata_dir=/var/lib/garage/meta` and `data_dir=/var/lib/garage/data`. This
is mandatory to use the DynamicUser hardening feature of systemd, which
autocreates these directories as virtual mapping. If the directory
`/var/lib/garage` already exists before starting the server for the first time,
the systemd service might not start correctly. Note that in your host
filesystem, Garage data will be held in `/var/lib/private/garage`.
*A note on hardening: garage will be run as a non privileged user, its user id is dynamically allocated by systemd. It cannot access (read or write) home folders (/home, /root and /run/user), the rest of the filesystem can only be read but not written, only the path seen as /var/lib/garage is writable as seen by the service (mapped to /var/lib/private/garage on your host). Additionnaly, the process can not gain new privileges over time.*
To start the service then automatically enable it at boot:
@@ -1,6 +1,6 @@
+++
title = "Upgrading Garage"
weight = 10
weight = 60
+++
Garage is a stateful clustered application, where all nodes are communicating together and share data structures.
@@ -9,7 +9,7 @@ On a new version release, there is 2 possibilities:
- protocols and data structures remained the same ➡️ this is a **minor upgrade**
- protocols or data structures changed ➡️ this is a **major upgrade**
You can quickly know what type of update you will have to operate by looking at the version identifier:
You can quickly now what type of update you will have to operate by looking at the version identifier:
when we require our users to do a major upgrade, we will always bump the first nonzero component of the version identifier
(e.g. from v0.7.2 to v0.8.0).
Conversely, for versions that only require a minor upgrade, the first nonzero component will always stay the same (e.g. from v0.8.0 to v0.8.1).
@@ -56,9 +56,9 @@ From a high level perspective, a major upgrade looks like this:
10. Enable API access (reverse step 1)
11. Monitor your cluster while load comes back, check that all your applications are happy with this new version
### Major upgrades with minimal downtime
### Major upgarades with minimal downtime
There is only one operation that has to be coordinated cluster-wide: the switch of one version of the internal RPC protocol to the next.
There is only one operation that has to be coordinated cluster-wide: the passage of one version of the internal RPC protocol to the next.
This means that an upgrade with very limited downtime can simply be performed from one major version to the next by restarting all nodes
simultaneously in the new version.
The downtime will simply be the time required for all nodes to stop and start again, which should be less than a minute.
@@ -71,19 +71,7 @@ The entire procedure would look something like this:
2. Take each node offline individually to back up its metadata folder, bring them back online once the backup is done.
You can do all of the nodes in a single zone at once as that won't impact global cluster availability.
Do not try to manually copy the metadata folder of a running node.
**Since Garage v0.9.4,** you can use the `garage meta snapshot --all` command
to take a simultaneous snapshot of the metadata database files of all your
nodes. This avoids the tedious process of having to take them down one by
one before upgrading. Be careful that if automatic snapshotting is enabled,
Garage only keeps the last two snapshots and deletes older ones, so you might
want to disable automatic snapshotting in your upgraded configuration file
until you have confirmed that the upgrade ran successfully. In addition to
snapshotting the metadata databases of your nodes, you should back-up at
least the `cluster_layout` file of one of your Garage instances (this file
should be the same on all nodes and you can copy it safely while Garage is
running).
Do not try to make a backup of the metadata folder of a running node.
3. Prepare your binaries and configuration files for the new Garage version
@@ -92,6 +80,6 @@ The entire procedure would look something like this:
5. If any specific migration procedure is required, it is usually in one of the two cases:
- It can be run on online nodes after the new version has started, during regular cluster operation.
- it has to be run offline, in which case you will have to again take all nodes offline one after the other to run the repair
- it has to be run offline
For this last step, please refer to the specific documentation pertaining to the version upgrade you are doing.
+4 -2
View File
@@ -1,6 +1,6 @@
+++
title = "Design"
weight = 70
weight = 6
sort_by = "weight"
template = "documentation.html"
+++
@@ -10,7 +10,7 @@ perspective. It will allow you to understand if Garage is a good fit for
you, how to better use it, how to contribute to it, what can Garage could
and could not do, etc.
- **[Goals and use cases](@/documentation/design/goals.md):** This page explains why Garage was conceived and what practical use cases it targets.
- **[Goals and use cases](@/documentation/design/goals.md):** This page explains why Garage was concieved and what practical use cases it targets.
- **[Related work](@/documentation/design/related-work.md):** This pages presents the theoretical background on which Garage is built, and describes other software storage solutions and why they didn't work for us.
@@ -31,3 +31,5 @@ We love to talk and hear about Garage, that's why we keep a log here:
- [(en, 2021-04-28) Distributed object storage is centralised](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/commit/b1f60579a13d3c5eba7f74b1775c84639ea9b51a/doc/talks/2021-04-28_spirals-team/talk.pdf)
- [(fr, 2020-12-02) Garage : jouer dans la cour des grands quand on est un hébergeur associatif](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/commit/b1f60579a13d3c5eba7f74b1775c84639ea9b51a/doc/talks/2020-12-02_wide-team/talk.pdf)
+5 -5
View File
@@ -15,14 +15,14 @@ The more a user request will require intra-cluster requests to complete, the mor
This is especially true for sequential requests: requests that must wait the result of another request to be sent.
We designed Garage without consensus algorithms (eg. Paxos or Raft) to minimize the number of sequential and parallel requests.
This series of benchmarks quantifies the impact of this design choice.
This serie of benchmarks quantifies the impact of this design choice.
### On a simple simulated network
We start with a controlled environment, all the instances are running on the same (powerful enough) machine.
To control the network latency, we simulate the network with [mknet](https://git.deuxfleurs.fr/trinity-1686a/mknet) (a tool we developed, based on `tc` and the linux network stack).
To measure S3 endpoints latency, we use our own tool [s3lat](https://git.deuxfleurs.fr/quentin/s3lat/) to observe only the intra-cluster latency and not some contention on the nodes (CPU, RAM, disk I/O, network bandwidth, etc.).
To control the network latency, we simulate the network with [mknet](https://git.deuxfleurs.fr/trinity-1686a/mknet) (a tool we developped, based on `tc` and the linux network stack).
To mesure S3 endpoints latency, we use our own tool [s3lat](https://git.deuxfleurs.fr/quentin/s3lat/) to observe only the intra-cluster latency and not some contention on the nodes (CPU, RAM, disk I/O, network bandwidth, etc.).
Compared to other benchmark tools, S3Lat sends only one (small) request at the same time and measures its latency.
We selected 5 standard endpoints that are often in the critical path: ListBuckets, ListObjects, GetObject, PutObject and RemoveObject.
@@ -32,7 +32,7 @@ In this first benchmark, we consider 5 instances that are located in a different
Compared to garage, minio latency drastically increases on 3 endpoints: GetObject, PutObject, RemoveObject.
We suppose that these requests on minio make transactions over Raft, involving 4 sequential requests: 1) sending the message to the leader, 2) having the leader dispatch it to the other nodes, 3) waiting for the confirmation of followers and finally 4) committing it. With our current configuration, one Raft transaction will take around 400 ms. GetObject seems to correlate to 1 transaction while PutObject and RemoveObject seems to correlate to 2 or 3. Reviewing minio code would be required to confirm this hypothesis.
We suppose that these requests on minio make transactions over Raft, involving 4 sequential requests: 1) sending the message to the leader, 2) having the leader dispatch it to the other nodes, 3) waiting for the confirmation of followers and finally 4) commiting it. With our current configuration, one Raft transaction will take around 400 ms. GetObject seems to correlate to 1 transaction while PutObject and RemoveObject seems to correlate to 2 or 3. Reviewing minio code would be required to confirm this hypothesis.
Conversely, garage uses an architecture similar to DynamoDB and never require global cluster coordination to answer a request.
Instead, garage can always contact the right node in charge of the requested data, and can answer in as low as one request in the case of GetObject and PutObject. We also observed that Garage latency, while often lower to minio, is more dispersed: garage is still in beta and has not received any performance optimization yet.
@@ -50,7 +50,7 @@ We plot a similar graph as before:
This new graph is very similar to the one before, neither minio or garage seems to benefit from this new topology, but they also do not suffer from it.
Considering garage, this is expected: nodes in the same DC are put in the same zone, and then data are spread on different zones for data resiliency and availability.
Considering garage, this is expected: nodes in the same DC are put in the same zone, and then data are spread on different zones for data resiliency and availaibility.
Then, in the default mode, requesting data requires to query at least 2 zones to be sure that we have the most up to date information.
These requests will involve at least one inter-DC communication.
In other words, we prioritize data availability and synchronization over raw performances.
+8 -23
View File
@@ -42,30 +42,15 @@ locations. They use Garage themselves for the following tasks:
- As a [Matrix media backend](https://github.com/matrix-org/synapse-s3-storage-provider)
- To store personal data and shared documents through [Bagage](https://git.deuxfleurs.fr/Deuxfleurs/bagage), a homegrown WebDav-to-S3 proxy
- In the Drone continuous integration platform to store task logs
- As a Nix binary cache
- To store personal data and shared documents through [Bagage](https://git.deuxfleurs.fr/Deuxfleurs/bagage), a homegrown WebDav-to-S3 and SFTP-to-S3 proxy
- As a backup target using `rclone` and `restic`
- As a backup target using `rclone`
The Deuxfleurs Garage cluster is a multi-site cluster currently composed of
9 nodes in 3 physical locations.
### Triplebit
[Triplebit](https://www.triplebit.org) is a non-profit hosting provider and
ISP focused on improving access to privacy-related services. They use
Garage themselves for the following tasks:
- Hosting of their homepage, [privacyguides.org](https://www.privacyguides.org/), and various other static sites
- As a PowerDNS authoritative zone backend through [Lightning Stream](https://doc.powerdns.com/lightningstream/latest/index.html) and [LMDB](https://doc.powerdns.com/authoritative/backends/lmdb.html)
- As a Mastodon media storage backend for [mstdn.party](https://mstdn.party/) and [mstdn.plus](https://mstdn.plus/)
- As a PeerTube storage backend for [neat.tube](https://neat.tube/)
- As a [Matrix media backend](https://github.com/matrix-org/synapse-s3-storage-provider)
Triplebit's Garage cluster is a multi-site cluster currently composed of
15 storage nodes in 3 physical locations.
4 nodes in 2 physical locations. In the future it will be expanded to at
least 3 physical locations to fully exploit Garage's potential for high
availability.
+4 -3
View File
@@ -61,7 +61,7 @@ Garage prioritizes which nodes to query according to a few criteria:
For further reading on the cluster structure look at the [gateway](@/documentation/cookbook/gateways.md)
and [cluster layout management](@/documentation/operations/layout.md) pages.
and [cluster layout management](@/documentation/reference-manual/layout.md) pages.
## Garbage collection
@@ -94,10 +94,10 @@ delete a tombstone, the following condition has to be met:
- All nodes responsible for storing this entry are aware of the existence of
the tombstone, i.e. they cannot hold another version of the entry that is
superseded by the tombstone. This ensures that deleting the tombstone is
superseeded by the tombstone. This ensures that deleting the tombstone is
safe and that no deleted value will come back in the system.
Garage uses atomic database operations (such as compare-and-swap and
Garage makes use of Sled's atomic operations (such as compare-and-swap and
transactions) to ensure that only tombstones that have been correctly
propagated to other nodes are ever deleted from the local entry tree.
@@ -141,3 +141,4 @@ rebalance of data, this would have led to the disk utilization to explode
during the rebalancing, only to shrink again after 24 hours. The 10-minute
delay is a compromise that gives good security while not having this problem of
disk space explosion on rebalance.
+3 -3
View File
@@ -37,7 +37,7 @@ However, Amazon S3 source code is not open but alternatives were proposed.
We identified Minio, Pithos, Swift and Ceph.
Minio/Ceph enforces a total order, so properties similar to a (relaxed) filesystem.
Swift and Pithos are probably the most similar to AWS S3 with their consistent hashing ring.
However Pithos is not maintained anymore. More precisely the company that published Pithos version 1 has developed a second version 2 but has not open sourced it.
However Pithos is not maintained anymore. More precisely the company that published Pithos version 1 has developped a second version 2 but has not open sourced it.
Some tests conducted by the [ACIDES project](https://acides.org/) have shown that Openstack Swift consumes way more resources (CPU+RAM) that we can afford. Furthermore, people developing Swift have not designed their software for geo-distribution.
There were many attempts in research too. I am only thinking to [LBFS](https://pdos.csail.mit.edu/papers/lbfs:sosp01/lbfs.pdf) that was used as a basis for Seafile. But none of them have been effectively implemented yet.
@@ -63,11 +63,11 @@ Due to its industry oriented design, Ceph is also far from being *Simple* to ope
In a certain way, Ceph and MinIO are closer together than they are from Garage or OpenStack Swift.
**[Pithos](https://github.com/exoscale/pithos):**
Pithos has been abandoned and should probably not used yet, in the following we explain why we did not pick their design.
Pithos has been abandonned and should probably not used yet, in the following we explain why we did not pick their design.
Pithos was relying as a S3 proxy in front of Cassandra (and was working with Scylla DB too).
From its designers' mouth, storing data in Cassandra has shown its limitations justifying the project abandonment.
They built a closed-source version 2 that does not store blobs in the database (only metadata) but did not communicate further on it.
We considered their v2's design but concluded that it does not fit both our *Self-contained & lightweight* and *Simple* properties. It makes the development, the deployment and the operations more complicated while reducing the flexibility.
We considered there v2's design but concluded that it does not fit both our *Self-contained & lightweight* and *Simple* properties. It makes the development, the deployment and the operations more complicated while reducing the flexibility.
**[Riak CS](https://docs.riak.com/riak/cs/2.1.1/index.html):**
*Not written yet*
+1 -1
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@@ -1,6 +1,6 @@
+++
title = "Development"
weight = 80
weight = 7
sort_by = "weight"
template = "documentation.html"
+++
+28 -5
View File
@@ -25,7 +25,7 @@ git clone https://git.deuxfleurs.fr/Deuxfleurs/garage
cd garage
```
*Optionally, you can use our nix.conf file to speed up compilations:*
*Optionnaly, you can use our nix.conf file to speed up compilations:*
```bash
sudo mkdir -p /etc/nix
@@ -36,7 +36,7 @@ sudo killall nix-daemon
Now you can enter our nix-shell, all the required packages will be downloaded but they will not pollute your environment outside of the shell:
```bash
nix-shell -A devShell
nix-shell
```
You can use the traditional Rust development workflow:
@@ -65,8 +65,8 @@ nix-build -j $(nproc) --max-jobs auto
```
Our build has multiple parameters you might want to set:
- `release` to build with release optimisations instead of debug
- `target` allows for cross compilation
- `release` build with release optimisations instead of debug
- `target allows` for cross compilation
- `compileMode` can be set to test or bench to build a unit test runner
- `git_version` to inject the hash to display when running `garage stats`
@@ -80,7 +80,13 @@ nix-build \
--git_version $(git rev-parse HEAD)
```
*The result is located in `result/bin`. You can pass arguments to cross compile: check `.woodpecker/release.yml` for examples.*
*The result is located in `result/bin`. You can pass arguments to cross compile: check `.drone.yml` for examples.*
If you modify a `Cargo.toml` or regenerate any `Cargo.lock`, you must run `cargo2nix`:
```
cargo2nix -f
```
Many tools like rclone, `mc` (minio-client), or `aws` (awscliv2) will be available in your environment and will be useful to test Garage.
@@ -118,6 +124,23 @@ cargo fmt # format the project, run it before any commit!
cargo clippy # run the linter, run it before any commit!
```
This is specific to our project, but you will need one last tool, `cargo2nix`.
To install it, run:
```bash
cargo install --git https://github.com/superboum/cargo2nix --branch main cargo2nix
```
You must use it every time you modify a `Cargo.toml` or regenerate a `Cargo.lock` file as follow:
```bash
cargo build # Rebuild Cargo.lock if needed
cargo2nix -f
```
It will output a `Cargo.nix` file which is a specific `Cargo.lock` file dedicated to Nix that is required by our CI
which means you must include it in your commits.
Later, to use our scripts and integration tests, you might need additional tools.
These tools are listed at the end of the `shell.nix` package in the `nativeBuildInputs` part.
It is up to you to find a way to install the ones you need on your computer.
+14 -3
View File
@@ -3,6 +3,15 @@ title = "Miscellaneous notes"
weight = 20
+++
## Quirks about cargo2nix/rust in Nix
If you use submodules in your crate (like `crdt` and `replication` in `garage_table`), you must list them in `default.nix`
The Windows target does not work. it might be solvable through [overrides](https://github.com/cargo2nix/cargo2nix/blob/master/overlay/overrides.nix). Indeed, we pass `x86_64-pc-windows-gnu` but mingw need `x86_64-w64-mingw32`
We have a simple [PR on cargo2nix](https://github.com/cargo2nix/cargo2nix/pull/201) that fixes critical bugs but the project does not seem very active currently. We must use [my patched version of cargo2nix](https://github.com/superboum/cargo2nix) to enable i686 and armv6l compilation. We might need to contribute to cargo2nix in the future.
## Nix
Nix has no armv7 + musl toolchains but armv7l is backward compatible with armv6l.
@@ -72,9 +81,12 @@ Our cache will be checked.
- http://www.lpenz.org/articles/nixchannel/index.html
## Woodpecker
## Drone
Woodpecker can do parallelism both at the step and the pipeline level. At the step level, parallelism is restricted to the same runner.
Do not try to set a build as trusted from the interface or the CLI tool,
your request would be ignored. Instead, directly edit the database (table `repos`, column `repo_trusted`).
Drone can do parallelism both at the step and the pipeline level. At the step level, parallelism is restricted to the same runner.
## Building Docker containers
@@ -87,4 +99,3 @@ We were:
- Unable to use the kaniko container provided by Google as we can't run arbitrary logic: we need to put our secret in .docker/config.json.
Finally we chose to build kaniko through nix and use it in a `nix-shell`.
We then switched to using kaniko from nixpkgs when it was packaged.
+42 -19
View File
@@ -23,7 +23,7 @@ This logic is defined in `nix/build_index.nix`.
For each commit, we first pass the code to a formatter (rustfmt) and a linter (clippy).
Then we try to build it in debug mode and run both unit tests and our integration tests.
Additionally, when releasing, our integration tests are run on the release build for amd64 and i686.
Additionnaly, when releasing, our integration tests are run on the release build for amd64 and i686.
## Generated Artifacts
@@ -32,7 +32,7 @@ We generate the following binary artifacts for now:
- **os**: linux
- **format**: static binary, docker container
Additionally we also build two web pages and one JSON document:
Additionnaly we also build two web pages and one JSON document:
- the documentation (this website)
- [the release page](https://garagehq.deuxfleurs.fr/_releases.html)
- [the release list in JSON format](https://garagehq.deuxfleurs.fr/_releases.json)
@@ -42,7 +42,7 @@ and the docker containers on Docker Hub.
## Automation
We automated our release process with Nix and Woodpecker to make it more reliable.
We automated our release process with Nix and Drone to make it more reliable.
Here we describe how we have done in case you want to debug or improve it.
### Caching build steps
@@ -62,31 +62,52 @@ Sending to the cache is done through `nix copy`, for example:
nix copy --to 's3://nix?endpoint=garage.deuxfleurs.fr&region=garage&secret-key=/etc/nix/signing-key.sec' result
```
*The signing key possessed by the Garage maintainers is required to update the Nix cache.*
*Note that you need the signing key. In our case, it is stored as a secret in Drone.*
The previous command will only send the built package and not its dependencies.
In the case of our CI pipeline, we want to cache all intermediate build steps
as well. This can be done using this quite involved command (here as an example
for the `pkgs.amd64.release` package):
The previous command will only send the built packet and not its dependencies.
To send its dependency, a tool named `nix-copy-closure` has been created but it is not compatible with the S3 protocol.
Instead, you can use the following commands to list all the runtime dependencies:
```bash
nix copy -j8 \
--to 's3://nix?endpoint=garage.deuxfleurs.fr&region=garage&secret-key=/etc/nix/nix-signing-key.sec' \
$(nix path-info pkgs.amd64.release --file default.nix --derivation --recursive | sed 's/\.drv$/.drv^*/')
nix copy \
--to 's3://nix?endpoint=garage.deuxfleurs.fr&region=garage&secret-key=/etc/nix/signing-key.sec' \
$(nix-store -qR result/)
```
This command will simultaneously build all of the required Nix paths (using at
most 8 parallel Nix builder jobs) and send the resulting objects to the cache.
*We could also write this expression with xargs but this tool is not available in our container.*
This can be run for all the Garage packages we build using the following command:
But in certain cases, we want to cache compile time dependencies also.
For example, the Nix project does not provide binaries for cross compiling to i686 and thus we need to compile gcc on our own.
We do not want to compile gcc each time, so even if it is a compile time dependency, we want to cache it.
This time, the command is a bit more involved:
```bash
nix copy --to \
's3://nix?endpoint=garage.deuxfleurs.fr&region=garage&secret-key=/etc/nix/signing-key.sec' \
$(nix-store -qR --include-outputs \
$(nix-instantiate))
```
This is the command we use in our CI as we expect the final binary to change, so we mainly focus on
caching our development dependencies.
*Currently there is no automatic garbage collection of the cache: we should monitor its growth.
Hopefully, we can erase it totally without breaking any build, the next build will only be slower.*
In practise, we concluded that we do not want to cache all the compilation dependencies.
Instead, we want to cache the toolchain we use to build Garage each time we change it.
So we removed from Drone any automatic update of the cache and instead handle them manually with:
```
source ~/.awsrc
nix-shell --attr cache --run 'refresh_cache'
nix-shell --run 'refresh_toolchain'
```
We don't automate this step at each CI build, as *there is currently no automatic garbage collection of the cache.*
This means we should also monitor the cache's size; if it ever becomes too big we can erase it with:
Internally, it will run `nix-build` on `nix/toolchain.nix` and send the output plus its depedencies to the cache.
To erase the cache:
```
mc rm --recursive --force 'garage/nix/'
@@ -136,9 +157,9 @@ nix-shell --run refresh_index
If you want to compile for different architectures, you will need to repeat all these commands for each architecture.
**In practice, and except for debugging, you will never directly run these commands. Release is handled by Woodpecker.**
**In practise, and except for debugging, you will never directly run these commands. Release is handled by drone**
### Drone (obsolete)
### Drone
Our instance is available at [https://drone.deuxfleurs.fr](https://drone.deuxfleurs.fr).
You need an account on [https://git.deuxfleurs.fr](https://git.deuxfleurs.fr) to use it.
@@ -174,3 +195,5 @@ drone sign --save Deuxfleurs/garage
```
Looking at the file, you will see that most of the commands are `nix-shell` and `nix-build` commands with various parameters.
-23
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@@ -1,23 +0,0 @@
+++
title = "Operations & Maintenance"
weight = 50
sort_by = "weight"
template = "documentation.html"
+++
This section contains a number of important information on how to best operate a Garage cluster,
to ensure integrity and availability of your data:
- **[Upgrading Garage](@/documentation/operations/upgrading.md):** General instructions on how to
upgrade your cluster from one version to the next. Instructions specific for each version upgrade
can bef ound in the [working documents](@/documentation/working-documents/_index.md) section.
- **[Layout management](@/documentation/operations/layout.md):** Best practices for using the `garage layout`
commands when adding or removing nodes from your cluster.
- **[Durability and repairs](@/documentation/operations/durability-repairs.md):** How to check for small things
that might be going wrong, and how to recover from such failures.
- **[Recovering from failures](@/documentation/operations/recovering.md):** Garage's first selling point is resilience
to hardware failures. This section explains how to recover from such a failure in the
best possible way.
-147
View File
@@ -1,147 +0,0 @@
+++
title = "Durability & Repairs"
weight = 30
+++
To ensure the best durability of your data and to fix any inconsistencies that may
pop up in a distributed system, Garage provides a series of repair operations.
This guide will explain the meaning of each of them and when they should be applied.
# General syntax of repair operations
Repair operations described below are of the form `garage repair <repair_name>`.
These repairs will not launch without the `--yes` flag, which should
be added as follows: `garage repair --yes <repair_name>`.
By default these repair procedures will only run on the Garage node your CLI is
connecting to. To run on all nodes, add the `-a` flag as follows:
`garage repair -a --yes <repair_name>`.
# Data block operations
## Data store scrub {#scrub}
Scrubbing the data store means examining each individual data block to check that
their content is correct, by verifying their hash. Any block found to be corrupted
(e.g. by bitrot or by an accidental manipulation of the datastore) will be
restored from another node that holds a valid copy.
Scrubs are automatically scheduled by Garage to run every 25-35 days (the
actual time is randomized to spread load across nodes). The next scheduled run
can be viewed with `garage worker get`.
A scrub can also be launched manually using `garage repair scrub start`.
To view the status of an ongoing scrub, first find the task ID of the scrub worker
using `garage worker list`. Then, run `garage worker info <scrub_task_id>` to
view detailed runtime statistics of the scrub. To gather cluster-wide information,
this command has to be run on each individual node.
A scrub is a very disk-intensive operation that might slow down your cluster.
You may pause an ongoing scrub using `garage repair scrub pause`, but note that
the scrub will resume automatically 24 hours later as Garage will not let your
cluster run without a regular scrub. If the scrub procedure is too intensive
for your servers and is slowing down your workload, the recommended solution
is to increase the "scrub tranquility" using `garage worker set scrub-tranquility`.
A higher tranquility value will make Garage take longer pauses between two block
verifications. Of course, scrubbing the entire data store will also take longer.
## Block check and resync
In some cases, nodes hold a reference to a block but do not actually have the block
stored on disk. Conversely, they may also have on-disk blocks that are not referenced
any more. To fix both cases, a block repair may be run with `garage repair blocks`.
This will scan the entire block reference counter table to check that the blocks
exist on disk, and will scan the entire disk store to check that stored blocks
are referenced.
It is recommended to run this procedure when changing your cluster layout,
after the metadata tables have finished synchronizing between nodes
(usually a few hours after `garage layout apply`).
## Inspecting lost blocks
In extremely rare situations, data blocks may be unavailable from the entire cluster.
This means that even using `garage repair blocks`, some nodes may be unable
to fetch data blocks for which they hold a reference.
These errors are stored on each node in a list of "block resync errors", i.e.
blocks for which the last resync operation failed.
This list can be inspected using `garage block list-errors`.
These errors usually fall into one of the following categories:
1. a block is still referenced but the object was deleted, this is a case
of metadata reference inconsistency (see below for the fix)
2. a block is referenced by a non-deleted object, but could not be fetched due
to a transient error such as a network failure
3. a block is referenced by a non-deleted object, but could not be fetched due
to a permanent error such as there not being any valid copy of the block on the
entire cluster
To help make the difference between cases 1 and cases 2 and 3, you may use the
`garage block info` command to see which objects hold a reference to each block.
In the second case (transient errors), Garage will try to fetch the block again
after a certain time, so the error should disappear naturally. You can also
request Garage to try to fetch the block immediately using `garage block retry-now`
if you have fixed the transient issue.
If you are confident that you are in the third scenario and that your data block
is definitely lost, then there is no other choice than to declare your S3 objects
as unrecoverable, and to delete them properly from the data store. This can be done
using the `garage block purge` command.
## Rebalancing data directories
In [multi-HDD setups](@/documentation/operations/multi-hdd.md), to ensure that
data blocks are well balanced between storage locations, you may run a
rebalance operation using `garage repair rebalance`. This is useful when
adding storage locations or when capacities of the storage locations have been
changed. Once this is finished, Garage will know for each block of a single
possible location where it can be, which can increase access speed. This
operation will also move out all data from locations marked as read-only.
# Metadata operations
## Metadata snapshotting
It is good practice to setup automatic snapshotting of your metadata database
file, to recover from situations where it becomes corrupted on disk. This can
be done at the filesystem level if you are using ZFS or BTRFS.
Since Garage v0.9.4, Garage is able to take snapshots of the metadata database
itself. This basically amounts to copying the database file, except that it can
be run live while Garage is running without the risk of corruption or
inconsistencies. This can be setup to run automatically on a schedule using
[`metadata_auto_snapshot_interval`](@/documentation/reference-manual/configuration.md#metadata_auto_snapshot_interval).
A snapshot can also be triggered manually using the `garage meta snapshot`
command. Note that taking a snapshot using this method is very intensive as it
requires making a full copy of the database file, so you might prefer using
filesystem-level snapshots if possible. To recover a corrupted node from such a
snapshot, read the instructions
[here](@/documentation/operations/recovering.md#corrupted_meta).
## Metadata table resync
Garage automatically resyncs all entries stored in the metadata tables every hour,
to ensure that all nodes have the most up-to-date version of all the information
they should be holding.
The resync procedure is based on a Merkle tree that allows to efficiently find
differences between nodes.
In some special cases, e.g. before an upgrade, you might want to run a table
resync manually. This can be done using `garage repair tables`.
## Metadata table reference fixes
In some very rare cases where nodes are unavailable, some references between objects
are broken. For instance, if an object is deleted, the underlying versions or data
blocks may still be held by Garage. If you suspect that such corruption has occurred
in your cluster, you can run one of the following repair procedures:
- `garage repair versions`: checks that all versions belong to a non-deleted object, and purges any orphan version
- `garage repair block-refs`: checks that all block references belong to a non-deleted object version, and purges any orphan block reference (this will then allow the blocks to be garbage-collected)
- `garage repair block-rc`: checks that the reference counters for blocks are in sync with the actual number of non-deleted entries in the block reference table
-274
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@@ -1,274 +0,0 @@
+++
title = "Cluster layout management"
weight = 20
+++
The cluster layout in Garage is a table that assigns to each node a role in
the cluster. The role of a node in Garage can either be a storage node with
a certain capacity, or a gateway node that does not store data and is only
used as an API entry point for faster cluster access.
An introduction to building cluster layouts can be found in the [production deployment](@/documentation/cookbook/real-world.md) page.
In Garage, all of the data that can be stored in a given cluster is divided
into slices which we call *partitions*. Each partition is stored by
one or several nodes in the cluster
(see [`replication_factor`](@/documentation/reference-manual/configuration.md#replication_factor)).
The layout determines the correspondence between these partitions,
which exist on a logical level, and actual storage nodes.
## How cluster layouts work in Garage
A cluster layout is composed of the following components:
- a table of roles assigned to nodes, defined by the user
- an optimal assignation of partitions to nodes, computed by an algorithm that is ran once when calling `garage layout apply` or the ApplyClusterLayout API endpoint
- a version number
Garage nodes will always use the cluster layout with the highest version number.
Garage nodes also maintain and synchronize between them a set of proposed role
changes that haven't yet been applied. These changes will be applied (or
canceled) in the next version of the layout.
All operations on the layout can be realized using the `garage` CLI or using the
[administration API endpoint](@/documentation/reference-manual/admin-api.md).
We give here a description of CLI commands, the admin API semantics are very similar.
The following commands insert modifications to the set of proposed role changes
for the next layout version (but they do not create the new layout immediately):
```bash
garage layout assign [...]
garage layout remove [...]
```
The following command can be used to inspect the layout that is currently set in the cluster
and the changes proposed for the next layout version, if any:
```bash
garage layout show
```
The following commands create a new layout with the specified version number,
that either takes into account the proposed changes or cancels them:
```bash
garage layout apply --version <new_version_number>
garage layout revert --version <new_version_number>
```
The version number of the new layout to create must be 1 + the version number
of the previous layout that existed in the cluster. The `apply` and `revert`
commands will fail otherwise.
## Warnings about Garage cluster layout management
**⚠️ Never make several calls to `garage layout apply` or `garage layout
revert` with the same value of the `--version` flag. Doing so can lead to the
creation of several different layouts with the same version number, in which
case your Garage cluster will become inconsistent until fixed.** If a call to
`garage layout apply` or `garage layout revert` has failed and `garage layout
show` indicates that a new layout with the given version number has not been
set in the cluster, then it is fine to call the command again with the same
version number.
If you are using the `garage` CLI by typing individual commands in your
shell, you shouldn't have much issues as long as you run commands one after
the other and take care of checking the output of `garage layout show`
before applying any changes.
If you are using the `garage` CLI or the admin API to script layout changes,
follow the following recommendations:
- If using the CLI, make all of your `garage` CLI calls to the same RPC host.
If using the admin API, make all of your API calls to the same Garage node. Do
not connect to individual nodes to send them each a piece of the layout changes
you are making, as the changes propagate asynchronously between nodes and might
not all be taken into account at the time when the new layout is applied.
- **Only call `garage layout apply`/ApplyClusterLayout once**, and call it
**strictly after** all of the `layout assign` and `layout remove`
commands/UpdateClusterLayout API calls have returned.
## Understanding unexpected layout calculations
When adding, removing or modifying nodes in a cluster layout, sometimes
unexpected assignations of partitions to node can occur. These assignations
are in fact normal and logical, given the objectives of the algorithm. Indeed,
**the layout algorithm prioritizes moving less data between nodes over
achieving equal distribution of load. It also tries to use all links between
pairs of nodes in equal proportions when moving data.** This section presents
two examples and illustrates how one can control Garage's behavior to obtain
the desired results.
### Example 1
In this example, a cluster is originally composed of 3 nodes in 3 different
zones (data centers). The three nodes are of equal capacity, therefore they
are all fully exploited and all store a copy of all of the data in the cluster.
Then, a fourth node of the same size is added in the datacenter `dc1`.
As illustrated by the following, **Garage will by default not store any data on the new node**:
```
$ garage layout show
==== CURRENT CLUSTER LAYOUT ====
ID Tags Zone Capacity Usable capacity
b10c110e4e854e5a node1 dc1 1000.0 MB 1000.0 MB (100.0%)
a235ac7695e0c54d node2 dc2 1000.0 MB 1000.0 MB (100.0%)
62b218d848e86a64 node3 dc3 1000.0 MB 1000.0 MB (100.0%)
Zone redundancy: maximum
Current cluster layout version: 6
==== STAGED ROLE CHANGES ====
ID Tags Zone Capacity
a11c7cf18af29737 node4 dc1 1000.0 MB
==== NEW CLUSTER LAYOUT AFTER APPLYING CHANGES ====
ID Tags Zone Capacity Usable capacity
b10c110e4e854e5a node1 dc1 1000.0 MB 1000.0 MB (100.0%)
a11c7cf18af29737 node4 dc1 1000.0 MB 0 B (0.0%)
a235ac7695e0c54d node2 dc2 1000.0 MB 1000.0 MB (100.0%)
62b218d848e86a64 node3 dc3 1000.0 MB 1000.0 MB (100.0%)
Zone redundancy: maximum
==== COMPUTATION OF A NEW PARTITION ASSIGNATION ====
Partitions are replicated 3 times on at least 3 distinct zones.
Optimal partition size: 3.9 MB (3.9 MB in previous layout)
Usable capacity / total cluster capacity: 3.0 GB / 4.0 GB (75.0 %)
Effective capacity (replication factor 3): 1000.0 MB
A total of 0 new copies of partitions need to be transferred.
dc1 Tags Partitions Capacity Usable capacity
b10c110e4e854e5a node1 256 (0 new) 1000.0 MB 1000.0 MB (100.0%)
a11c7cf18af29737 node4 0 (0 new) 1000.0 MB 0 B (0.0%)
TOTAL 256 (256 unique) 2.0 GB 1000.0 MB (50.0%)
dc2 Tags Partitions Capacity Usable capacity
a235ac7695e0c54d node2 256 (0 new) 1000.0 MB 1000.0 MB (100.0%)
TOTAL 256 (256 unique) 1000.0 MB 1000.0 MB (100.0%)
dc3 Tags Partitions Capacity Usable capacity
62b218d848e86a64 node3 256 (0 new) 1000.0 MB 1000.0 MB (100.0%)
TOTAL 256 (256 unique) 1000.0 MB 1000.0 MB (100.0%)
```
While unexpected, this is logical because of the following facts:
- storing some data on the new node does not help increase the total quantity
of data that can be stored on the cluster, as the two other zones (`dc2` and
`dc3`) still need to store a full copy of everything, and their capacity is
still the same;
- there is therefore no need to move any data on the new node as this would be pointless;
- moving data to the new node has a cost which the algorithm decides to not pay if not necessary.
This distribution of data can however not be what the administrator wanted: if
they added a new node to `dc1`, it might be because the existing node is too
slow, and they wish to divide its load by half. In that case, what they need to
do to force Garage to distribute the data between the two nodes is to attribute
only half of the capacity to each node in `dc1` (in our example, 500M instead of 1G).
In that case, Garage would determine that to be able to store 1G in total, it
would need to store 500M on the old node and 500M on the added one.
### Example 2
The following example is a slightly different scenario, where `dc1` had two
nodes that were used at 50%, and `dc2` and `dc3` each have one node that is
100% used. All node capacities are the same.
Then, a node from `dc1` is moved into `dc3`. One could expect that the roles of
`dc1` and `dc3` would simply be swapped: the remaining node in `dc1` would be
used at 100%, and the two nodes now in `dc3` would be used at 50%. Instead,
this happens:
```
==== CURRENT CLUSTER LAYOUT ====
ID Tags Zone Capacity Usable capacity
b10c110e4e854e5a node1 dc1 1000.0 MB 500.0 MB (50.0%)
a11c7cf18af29737 node4 dc1 1000.0 MB 500.0 MB (50.0%)
a235ac7695e0c54d node2 dc2 1000.0 MB 1000.0 MB (100.0%)
62b218d848e86a64 node3 dc3 1000.0 MB 1000.0 MB (100.0%)
Zone redundancy: maximum
Current cluster layout version: 8
==== STAGED ROLE CHANGES ====
ID Tags Zone Capacity
a11c7cf18af29737 node4 dc3 1000.0 MB
==== NEW CLUSTER LAYOUT AFTER APPLYING CHANGES ====
ID Tags Zone Capacity Usable capacity
b10c110e4e854e5a node1 dc1 1000.0 MB 1000.0 MB (100.0%)
a235ac7695e0c54d node2 dc2 1000.0 MB 1000.0 MB (100.0%)
62b218d848e86a64 node3 dc3 1000.0 MB 753.9 MB (75.4%)
a11c7cf18af29737 node4 dc3 1000.0 MB 246.1 MB (24.6%)
Zone redundancy: maximum
==== COMPUTATION OF A NEW PARTITION ASSIGNATION ====
Partitions are replicated 3 times on at least 3 distinct zones.
Optimal partition size: 3.9 MB (3.9 MB in previous layout)
Usable capacity / total cluster capacity: 3.0 GB / 4.0 GB (75.0 %)
Effective capacity (replication factor 3): 1000.0 MB
A total of 128 new copies of partitions need to be transferred.
dc1 Tags Partitions Capacity Usable capacity
b10c110e4e854e5a node1 256 (128 new) 1000.0 MB 1000.0 MB (100.0%)
TOTAL 256 (256 unique) 1000.0 MB 1000.0 MB (100.0%)
dc2 Tags Partitions Capacity Usable capacity
a235ac7695e0c54d node2 256 (0 new) 1000.0 MB 1000.0 MB (100.0%)
TOTAL 256 (256 unique) 1000.0 MB 1000.0 MB (100.0%)
dc3 Tags Partitions Capacity Usable capacity
62b218d848e86a64 node3 193 (0 new) 1000.0 MB 753.9 MB (75.4%)
a11c7cf18af29737 node4 63 (0 new) 1000.0 MB 246.1 MB (24.6%)
TOTAL 256 (256 unique) 2.0 GB 1000.0 MB (50.0%)
```
As we can see, the node that was moved to `dc3` (node4) is only used at 25% (approximately),
whereas the node that was already in `dc3` (node3) is used at 75%.
This can be explained by the following:
- node1 will now be the only node remaining in `dc1`, thus it has to store all
of the data in the cluster. Since it was storing only half of it before, it has
to retrieve the other half from other nodes in the cluster.
- The data which it does not have is entirely stored by the other node that was
in `dc1` and that is now in `dc3` (node4). There is also a copy of it on node2
and node3 since both these nodes have a copy of everything.
- node3 and node4 are the two nodes that will now be in a datacenter that is
under-utilized (`dc3`), this means that those are the two candidates from which
data can be removed to be moved to node1.
- Garage will move data in equal proportions from all possible sources, in this
case it means that it will transfer 25% of the entire data set from node3 to
node1 and another 25% from node4 to node1.
This explains why node3 ends with 75% utilization (100% from before minus 25%
that is moved to node1), and node4 ends with 25% (50% from before minus 25%
that is moved to node1).
This illustrates the second principle of the layout computation: **if there is
a choice in moving data out of some nodes, then all links between pairs of
nodes are used in equal proportions** (this is approximately true, there is
randomness in the algorithm to achieve this so there might be some small
fluctuations, as we see above).
-101
View File
@@ -1,101 +0,0 @@
+++
title = "Multi-HDD support"
weight = 15
+++
Since v0.9, Garage natively supports nodes that have several storage drives
for storing data blocks (not for metadata storage).
## Initial setup
To set up a new Garage storage node with multiple HDDs,
format and mount all your drives in different directories,
and use a Garage configuration as follows:
```toml
data_dir = [
{ path = "/path/to/hdd1", capacity = "2T" },
{ path = "/path/to/hdd2", capacity = "4T" },
]
```
Garage will automatically balance all blocks stored by the node
among the different specified directories, proportionally to the
specified capacities.
## Updating the list of storage locations
If you add new storage locations to your `data_dir`,
Garage will not rebalance existing data between storage locations.
Newly written blocks will be balanced proportionally to the specified capacities,
and existing data may be moved between drives to improve balancing,
but only opportunistically when a data block is re-written (e.g. an object
is re-uploaded, or an object with a duplicate block is uploaded).
To understand precisely what is happening, we need to dive in to how Garage
splits data among the different storage locations.
First of all, Garage divides the set of all possible block hashes
in a fixed number of slices (currently 1024), and assigns
to each slice a primary storage location among the specified data directories.
The number of slices having their primary location in each data directory
is proportional to the capacity specified in the config file.
When Garage receives a block to write, it will always write it in the primary
directory of the slice that contains its hash.
Now, to be able to not lose existing data blocks when storage locations
are added, Garage also keeps a list of secondary data directories
for all of the hash slices. Secondary data directories for a slice indicates
storage locations that once were primary directories for that slice, i.e. where
Garage knows that data blocks of that slice might be stored.
When Garage is requested to read a certain data block,
it will first look in the primary storage directory of its slice,
and if it doesn't find it there it goes through all of the secondary storage
locations until it finds it. This allows Garage to continue operating
normally when storage locations are added, without having to shuffle
files between drives to place them in the correct location.
This relatively simple strategy works well but does not ensure that data
is correctly balanced among drives according to their capacity.
To rebalance data, two strategies can be used:
- Lazy rebalancing: when a block is re-written (e.g. the object is re-uploaded),
Garage checks whether the existing copy is in the primary directory of the slice
or in a secondary directory. If the current copy is in a secondary directory,
Garage re-writes a copy in the primary directory and deletes the one from the
secondary directory. This might never end up rebalancing everything if there
are data blocks that are only read and never written.
- Active rebalancing: an operator of a Garage node can explicitly launch a repair
procedure that rebalances the data directories, moving all blocks to their
primary location. Once done, all secondary locations for all hash slices are
removed so that they won't be checked anymore when looking for a data block.
## Read-only storage locations
If you would like to move all data blocks from an existing data directory to one
or several new data directories, mark the old directory as read-only:
```toml
data_dir = [
{ path = "/path/to/old_data", read_only = true },
{ path = "/path/to/new_hdd1", capacity = "2T" },
{ path = "/path/to/new_hdd2", capacity = "4T" },
]
```
Garage will be able to read requested blocks from the read-only directory.
Garage will also move data out of the read-only directory either progressively
(lazy rebalancing) or if requested explicitly (active rebalancing).
Once an active rebalancing has finished, your read-only directory should be empty:
it might still contain subdirectories, but no data files. You can check that
it contains no files using:
```bash
find -type f /path/to/old_data # should not print anything
```
at which point it can be removed from the `data_dir` list in your config file.
+130 -245
View File
@@ -1,6 +1,6 @@
+++
title = "Quick Start"
weight = 10
weight = 0
sort_by = "weight"
template = "documentation.html"
+++
@@ -35,18 +35,10 @@ Place this binary somewhere in your `$PATH` so that you can invoke the `garage`
command directly (for instance you can copy the binary in `/usr/local/bin`
or in `~/.local/bin`).
You may also check whether your distribution already includes a
[binary package for Garage](@/documentation/cookbook/binary-packages.md).
If a binary of the last version is not available for your architecture,
or if you want a build customized for your system,
you can [build Garage from source](@/documentation/cookbook/from-source.md).
If none of these option work for you, you can also run Garage in a Docker
container. For simplicity, a minimal command to launch Garage using Docker is
provided in this quick start guide. We recommend reading the tutorial on
[configuring a multi-node cluster](@/documentation/cookbook/real-world.md) to
learn about the full Docker workflow for Garage.
## Configuring and starting Garage
@@ -62,9 +54,9 @@ to generate unique and private secrets for security reasons:
cat > garage.toml <<EOF
metadata_dir = "/tmp/meta"
data_dir = "/tmp/data"
db_engine = "sqlite"
db_engine = "lmdb"
replication_factor = 1
replication_mode = "none"
rpc_bind_addr = "[::]:3901"
rpc_public_addr = "127.0.0.1:3901"
@@ -80,23 +72,20 @@ bind_addr = "[::]:3902"
root_domain = ".web.garage.localhost"
index = "index.html"
[k2v_api]
api_bind_addr = "[::]:3904"
[admin]
api_bind_addr = "[::]:3903"
api_bind_addr = "0.0.0.0:3903"
admin_token = "$(openssl rand -base64 32)"
metrics_token = "$(openssl rand -base64 32)"
EOF
```
See the [Configuration file format](https://garagehq.deuxfleurs.fr/documentation/reference-manual/configuration/)
for complete options and values.
Now that your configuration file has been created, you can put
it in the right place. By default, garage looks at **`/etc/garage.toml`.**
By default, Garage looks for its configuration file in **`/etc/garage.toml`.**
Since we have written our configuration file in the working directory, we will have to set
the following environment variable:
```bash
export GARAGE_CONFIG_FILE=$(pwd)/garage.toml
```
You can also store it somewhere else, but you will have to specify `-c path/to/garage.toml`
at each invocation of the `garage` binary (for example: `garage -c ./garage.toml server`, `garage -c ./garage.toml status`).
As you can see, the `rpc_secret` is a 32 bytes hexadecimal string.
You can regenerate it with `openssl rand -hex 32`.
@@ -109,99 +98,18 @@ Garage server will not be persistent. Change these to locations on your local di
your data to be persisted properly.
### Configuring initial access credentials
Since `v2.3.0`, Garage can automatically create a default access key and a default storage bucket,
based on values provided in environment variables.
To use this feature, export the following environment variables:
```bash
export GARAGE_DEFAULT_ACCESS_KEY="GK$(openssl rand -hex 16)"
export GARAGE_DEFAULT_SECRET_KEY="$(openssl rand -hex 32)"
export GARAGE_DEFAULT_BUCKET="default-bucket"
```
The example above creates a random access key ID and associated secret key.
You can also provide an access key ID and secret key of your own.
### Launching the Garage server
Use the following command to launch the Garage server:
```bash
garage server --single-node --default-bucket
```
The `--single-node` flag instructs Garage to automatically configure a single-node cluster without data replication.
The `--default-bucket` flag instructs Garage to create a default access key and a default bucket using the environment variables we defined above.
Both flags are optional and can be omitted, in which case you will have to follow manual configuration steps described below.
**For older versions of Garage (before v2.3.0):** automatic configuration using `--single-node` and `--default-bucket` is not available,
you must follow the manual configuration steps.
Alternatively, if you cannot or do not wish to run the Garage binary directly,
you may use Docker to run Garage in a container using the following command:
```bash
docker run \
-d \
--name garage-container \
-p 3900:3900 -p 3901:3901 -p 3902:3902 -p 3903:3903 \
-v $(pwd)/garage.toml:/etc/garage.toml \
-e GARAGE_DEFAULT_ACCESS_KEY \
-e GARAGE_DEFAULT_SECRET_KEY \
-e GARAGE_DEFAULT_BUCKET \
dxflrs/garage:v2.3.0
/garage server --single-node --default-bucket
```
Note that this command will NOT create persistent volumes for Garage's data, so
your cluster will be wiped if the container terminates. To persist Garage's
data, you must manually add volumes for the `data` and `metadata` directories
and configure their correct paths in your `garage.toml` files (see [configuring
a multi-node cluster](@/documentation/cookbook/real-world.md)).
Under Linux, you can substitute `--network host` for `-p 3900:3900 -p 3901:3901 -p 3902:3902 -p 3903:3903`.
### Checking that Garage runs correctly
The `garage` utility is also used as a CLI tool to administrate your Garage
deployment. It needs read access to your configuration file and to the metadata directory
to obtain connection parameters to contact the local Garage node.
Use the following command to show the status of your cluster:
Use the following command to launch the Garage server with our configuration file:
```
garage status
garage server
```
If you are running Garage in a Docker container, you can use the following command instead:
```bash
docker exec garage-container /garage status
```
This should show something like this:
You can tune Garage's verbosity as follows (from less verbose to more verbose):
```
==== HEALTHY NODES ====
ID Hostname Address Tags Zone Capacity DataAvail Version
563e1ac825ee3323 linuxbox 127.0.0.1:3901 [default] dc1 19.9 GiB 19.5 GiB (97.6%) v2.3.0
```
### Troubleshooting
Ensure your configuration file, `metadata_dir` and `data_dir` are readable by the user running the `garage` server or Docker.
When running the `garage` CLI, ensure that the path to your configuration file is correctly specified (see below),
and that it can read it and read from your metadata directory.
You can tune Garage's verbosity by setting the `RUST_LOG=` environment variable.
Available log levels are (from less verbose to more verbose): `error`, `warn`, `info` *(default)*, `debug` and `trace`.
```bash
RUST_LOG=garage=info garage server # default
RUST_LOG=garage=info garage server
RUST_LOG=garage=debug garage server
RUST_LOG=garage=trace garage server
```
@@ -210,97 +118,58 @@ Log level `info` is the default value and is recommended for most use cases.
Log level `debug` can help you check why your S3 API calls are not working.
### Checking that Garage runs correctly
## Uploading and downloading from Garage
The `garage` utility is also used as a CLI tool to configure your Garage deployment.
It uses values from the TOML configuration file to find the Garage daemon running on the
local node, therefore if your configuration file is not at `/etc/garage.toml` you will
again have to specify `-c path/to/garage.toml`.
This section will show how to download and upload files on Garage using a third-party tool named `awscli`.
### Install and configure `awscli`
If you have python on your system, you can install it with:
```bash
python -m pip install --user awscli
```
Now that `awscli` is installed, you must configure it to talk to your Garage
instance using the credentials defined above. Here is a simple way to create
a configuration file in `~/.awsrc` using a single command that will save the
secrets from your environment:
```bash
cat > ~/.awsrc <<EOF
export AWS_ENDPOINT_URL='http://localhost:3900'
export AWS_DEFAULT_REGION='garage'
export AWS_ACCESS_KEY_ID='$GARAGE_DEFAULT_ACCESS_KEY'
export AWS_SECRET_ACCESS_KEY='$GARAGE_DEFAULT_SECRET_KEY'
aws --version
EOF
If the `garage` CLI is able to correctly detect the parameters of your local Garage node,
the following command should be enough to show the status of your cluster:
```
Note that you need to have at least `awscli` `>=1.29.0` or `>=2.13.0`, otherwise you
need to specify `--endpoint-url` explicitly on each `awscli` invocation.
Now, each time you want to use `awscli` on this target, run:
```bash
source ~/.awsrc
garage status
```
*You can create multiple files with different names if you
have multiple Garage clusters or different keys.
Switching from one cluster to another is as simple as
sourcing the right file.*
This should show something like this:
### Example usage of `awscli`
```bash
# list buckets
aws s3 ls
# list objects of a bucket
aws s3 ls s3://default-bucket
# copy from your filesystem to garage
aws s3 cp /proc/cpuinfo s3://default-bucket/cpuinfo.txt
# copy from garage to your filesystem
aws s3 cp s3://default-bucket/cpuinfo.txt /tmp/cpuinfo.txt
```
==== HEALTHY NODES ====
ID Hostname Address Tag Zone Capacity
563e1ac825ee3323… linuxbox 127.0.0.1:3901 NO ROLE ASSIGNED
```
Note that you can use `awscli` for more advanced operations like
creating a bucket, pre-signing a request or managing your website.
[Read the full documentation to know more](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/s3/index.html).
## Creating a cluster layout
Some features are however not implemented like ACL or policy.
Check [our S3 compatibility list](@/documentation/reference-manual/s3-compatibility.md).
Creating a cluster layout for a Garage deployment means informing Garage
of the disk space available on each node of the cluster
as well as the zone (e.g. datacenter) each machine is located in.
### Other tools for interacting with Garage
For our test deployment, we are using only one node. The way in which we configure
it does not matter, you can simply write:
The following tools can also be used to send and receive files from/to Garage:
```bash
garage layout assign -z dc1 -c 1 <node_id>
```
- [minio-client](@/documentation/connect/cli.md#minio-client)
- [s3cmd](@/documentation/connect/cli.md#s3cmd)
- [rclone](@/documentation/connect/cli.md#rclone)
- [Cyberduck](@/documentation/connect/cli.md#cyberduck)
- [WinSCP](@/documentation/connect/cli.md#winscp)
where `<node_id>` corresponds to the identifier of the node shown by `garage status` (first column).
You can enter simply a prefix of that identifier.
For instance here you could write just `garage layout assign -z dc1 -c 1 563e`.
An exhaustive list is maintained in the ["Integrations" > "Browsing tools" section](@/documentation/connect/_index.md).
The layout then has to be applied to the cluster, using:
```bash
garage layout apply
```
## Creating buckets and keys
## Manual configuration
In this section, we will suppose that we want to create a bucket named `nextcloud-bucket`
that will be accessed through a key named `nextcloud-app-key`.
This section provides instructions that are equivalent to using the
`--single-node` and `--default-bucket` flags for automatic configuration. If
you are using an older version of Garage (before v2.3.0), you must follow
these instructions as automatic configuration is not available.
We will have to run quite a few `garage` administration commands to get started.
If you ever get lost, don't forget that the `help` command and the `--help` flags can help you anywhere,
Don't forget that `help` command and `--help` subcommands can help you anywhere,
the CLI tool is self-documented! Two examples:
```
@@ -308,80 +177,25 @@ garage help
garage bucket allow --help
```
### Configuring the `garage` CLI
Remember that the `garage` CLI needs to know the path of your `garage.toml` configuration file.
If it is not in the default location of `/etc/garage.toml`, you can specify it either:
- by setting the `GARAGE_CONFIG_FILE` environment variable;
- by adding the `-c` flag to each `garage` command, for example: `garage -c ./garage.toml status`.
If you are running Garage in a Docker container, you can set the following alias
to provide a fake `garage`command that uses the Garage binary inside your container:
```bash
alias garage="docker exec -ti <container name> /garage"
```
You can test that your `garage` CLI is configured correctly by running a basic command such as `garage status`.
### Creating a cluster layout
When you first start a cluster without automatic configuration, the output of `garage status` will look as follows:
```
==== HEALTHY NODES ====
ID Hostname Address Tags Zone Capacity DataAvail Version
563e1ac825ee3323 linuxbox 127.0.0.1:3901 NO ROLE ASSIGNED v2.3.0
```
Creating a cluster layout for a Garage deployment means informing Garage of the
disk space available on each node of the cluster using the `-c` flag, as well
as the name of the zone (e.g. datacenter) each machine is located in using the
`-z` flag.
For our test deployment, we are have only one node with zone named `dc1` and a
capacity of `1G`, though the capacity is ignored for a single node deployment
and can be changed later when adding new nodes.
```bash
garage layout assign -z dc1 -c 1G <node_id>
```
where `<node_id>` corresponds to the identifier of the node shown by `garage status` (first column).
You can enter simply a prefix of that identifier.
For instance here you could write just `garage layout assign -z dc1 -c 1G 563e`.
The layout then has to be applied to the cluster, using:
```bash
garage layout apply --version 1
```
### Creating buckets and keys
### Create a bucket
Let's take an example where we want to deploy NextCloud using Garage as the
main data storage. We will suppose that we want to create a bucket named
`nextcloud-bucket` that will be accessed through a key named
`nextcloud-app-key`.
main data storage.
#### Create a bucket
First, create the bucket with the following command:
First, create a bucket with the following command:
```
garage bucket create nextcloud-bucket
```
Check that the bucket was created properly:
Check that everything went well:
```
garage bucket list
garage bucket info nextcloud-bucket
```
#### Create an API key
### Create an API key
The `nextcloud-bucket` bucket now exists on the Garage server,
however it cannot be accessed until we add an API key with the proper access rights.
@@ -392,7 +206,7 @@ one key can access multiple buckets, multiple keys can access one bucket.
Create an API key using the following command:
```
garage key create nextcloud-app-key
garage key new --name nextcloud-app-key
```
The output should look as follows:
@@ -404,14 +218,14 @@ Secret key: 7d37d093435a41f2aab8f13c19ba067d9776c90215f56614adad6ece597dbb34
Authorized buckets:
```
Check that the key was created properly:
Check that everything works as intended:
```
garage key list
garage key info nextcloud-app-key
```
#### Allow a key to access a bucket
### Allow a key to access a bucket
Now that we have a bucket and a key, we need to give permissions to the key on the bucket:
@@ -430,5 +244,76 @@ You can check at any time the allowed keys on your bucket with:
garage bucket info nextcloud-bucket
```
You should now be able to read and write objects to the bucket using the
credentials created above.
## Uploading and downlading from Garage
To download and upload files on garage, we can use a third-party tool named `awscli`.
### Install and configure `awscli`
If you have python on your system, you can install it with:
```bash
python -m pip install --user awscli
```
Now that `awscli` is installed, you must configure it to talk to your Garage instance,
with your key. There are multiple ways to do that, the simplest one is to create a file
named `~/.awsrc` with this content:
```bash
export AWS_ACCESS_KEY_ID=xxxx # put your Key ID here
export AWS_SECRET_ACCESS_KEY=xxxx # put your Secret key here
export AWS_DEFAULT_REGION='garage'
export AWS_ENDPOINT='http://localhost:3900'
function aws { command aws --endpoint-url $AWS_ENDPOINT $@ ; }
aws --version
```
Now, each time you want to use `awscli` on this target, run:
```bash
source ~/.awsrc
```
*You can create multiple files with different names if you
have multiple Garage clusters or different keys.
Switching from one cluster to another is as simple as
sourcing the right file.*
### Example usage of `awscli`
```bash
# list buckets
aws s3 ls
# list objects of a bucket
aws s3 ls s3://my_files
# copy from your filesystem to garage
aws s3 cp /proc/cpuinfo s3://my_files/cpuinfo.txt
# copy from garage to your filesystem
aws s3 cp s3/my_files/cpuinfo.txt /tmp/cpuinfo.txt
```
Note that you can use `awscli` for more advanced operations like
creating a bucket, pre-signing a request or managing your website.
[Read the full documentation to know more](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/s3/index.html).
Some features are however not implemented like ACL or policy.
Check [our s3 compatibility list](@/documentation/reference-manual/s3-compatibility.md).
### Other tools for interacting with Garage
The following tools can also be used to send and recieve files from/to Garage:
- [minio-client](@/documentation/connect/cli.md#minio-client)
- [s3cmd](@/documentation/connect/cli.md#s3cmd)
- [rclone](@/documentation/connect/cli.md#rclone)
- [Cyberduck](@/documentation/connect/cli.md#cyberduck)
- [WinSCP](@/documentation/connect/cli.md#winscp)
An exhaustive list is maintained in the ["Integrations" > "Browsing tools" section](@/documentation/connect/_index.md).
+1 -1
View File
@@ -1,6 +1,6 @@
+++
title = "Reference Manual"
weight = 60
weight = 5
sort_by = "weight"
template = "documentation.html"
+++
+30 -229
View File
@@ -6,253 +6,54 @@ weight = 40
The Garage administration API is accessible through a dedicated server whose
listen address is specified in the `[admin]` section of the configuration
file (see [configuration file
reference](@/documentation/reference-manual/configuration.md)).
reference](@/documentation/reference-manual/configuration.md))
The current version of the admin API is v2. No breaking changes to the Garage
administration API will be published outside of a major release.
**WARNING.** At this point, there is no comittement to stability of the APIs described in this document.
We will bump the version numbers prefixed to each API endpoint at each time the syntax
or semantics change, meaning that code that relies on these endpoint will break
when changes are introduced.
History of previous versions:
The Garage administration API was introduced in version 0.7.2, this document
does not apply to older versions of Garage.
- Before Garage v0.7.2 - no admin API
- Garage v0.7.2 - admin API v0
- Garage v0.9.0 - admin API v1, deprecate admin API v0
- Garage v2.0.0 - admin API v2, deprecate admin API v1
## Access control
### Using an API token
The admin API uses two different tokens for acces control, that are specified in the config file's `[admin]` section:
Administration API tokens tokens are used as simple HTTP bearer tokens. In
other words, to authenticate access to an admin API endpoint, add the following
HTTP header to your request:
- `metrics_token`: the token for accessing the Metrics endpoint (if this token
is not set in the config file, the Metrics endpoint can be accessed without
access control);
- `admin_token`: the token for accessing all of the other administration
endpoints (if this token is not set in the config file, access to these
endpoints is disabled entirely).
These tokens are used as simple HTTP bearer tokens. In other words, to
authenticate access to an admin API endpoint, add the following HTTP header
to your request:
```
Authorization: Bearer <token>
```
### User-defined API tokens
## Administration API endpoints
Cluster administrators may dynamically define administration tokens using the CLI commands under `garage admin-token`.
Such tokens may be limited in scope, meaning that they may enable access to only a subset of API calls.
They may also have an expiration date to limit their use in time.
### Metrics-related endpoints
Here is an example to create an administration token that is valid for 30 days
and gives access to only a subset of API calls, allowing it to create buckets
and access keys and give keys permissions on buckets:
```bash
$ garage admin-token create --expires-in 30d \
--scope ListBuckets,GetBucketInfo,ListKeys,GetKeyInfo,CreateBucket,CreateKey,AllowBucketKey,DenyBucketKey \
my-token
This is your secret bearer token, it will not be shown again by Garage:
8ed1830b10a276ff57061950.kOSIpxWK9zSGbTO9Xadpv3YndSFWma0_snXcYHaORXk
==== ADMINISTRATION TOKEN INFORMATION ====
Token ID: 8ed1830b10a276ff57061950
Token name: my-token
Created: 2025-06-15 15:12:44.160 +02:00
Validity: valid
Expiration: 2025-07-15 15:12:44.117 +02:00
Scope: ListBuckets
GetBucketInfo
ListKeys
GetKeyInfo
CreateBucket
CreateKey
AllowBucketKey
DenyBucketKey
```
When running this command, your token will be shown only once and **will never
be shown again by Garage**, so make sure to save it directly. The token is
hashed internally, and is identified by its prefix (32 hex digits followed by a
dot) which is saved in clear.
When running `garage admin-token list`, you might see something like this:
```
ID Created Name Expiration Scope
- - metrics_token (from daemon configuration) never Metrics
8ed1830b10a276ff57061950 2025-06-15 my-token 2025-07-15 15:12:44.117 +02:00 ListBuckets, ... (8)
```
### Master API tokens
The admin API can also use two different master tokens for access control,
specified in the config file's `[admin]` section:
- `metrics_token`: the token for accessing the Metrics endpoint. If this token
is not set in the config file, the Metrics endpoint can be accessed without
access control.
- `admin_token`: the token for accessing all of the other administration
endpoints. If this token is not set in the config file, access to these
endpoints is only possible with a user-defined admin token.
With the introduction of multiple user-defined admin tokens, the use of master
API tokens is now discouraged.
## Using the admin API
All of the admin API endpoints are described in the OpenAPI specification:
- APIv2 - [HTML spec](https://garagehq.deuxfleurs.fr/api/garage-admin-v2.html) - [OpenAPI JSON](https://garagehq.deuxfleurs.fr/api/garage-admin-v2.json)
- APIv1 (deprecated) - [HTML spec](https://garagehq.deuxfleurs.fr/api/garage-admin-v1.html) - [OpenAPI YAML](https://garagehq.deuxfleurs.fr/api/garage-admin-v1.yml)
- APIv0 (deprecated) - [HTML spec](https://garagehq.deuxfleurs.fr/api/garage-admin-v0.html) - [OpenAPI YAML](https://garagehq.deuxfleurs.fr/api/garage-admin-v0.yml)
Making a request to the API from the command line can be as simple as running:
```bash
curl -H 'Authorization: Bearer s3cr3t' http://localhost:3903/v2/GetClusterStatus | jq
```
For more advanced use cases, we recommend using an SDK.
[Go to the "Build your own app" section to know how to use our SDKs](@/documentation/build/_index.md)
### Making API calls from the `garage` CLI
Since v2.0.0, the `garage` binary provides a subcommand `garage json-api` that
allows you to invoke the API without making an HTTP request. This can be
useful for scripting Garage deployments.
`garage json-api` proxies API calls through Garage's internal RPC protocol,
therefore it does not require any form of authentication: RPC connection
parameters are discovered automatically to contact the locally-running Garage
instance (as when running any other `garage` CLI command).
For simple calls that take no parameters, usage is as follows:
```
$ garage json-api GetClusterHealth
{
"connectedNodes": 3,
"knownNodes": 3,
"partitions": 256,
"partitionsAllOk": 256,
"partitionsQuorum": 256,
"status": "healthy",
"storageNodes": 3,
"storageNodesOk": 3
}
```
If you need to specify a JSON body for your call, you can add it directly after
the name of the function you are calling:
```
$ garage json-api CreateAdminToken '{"name": "test"}'
```
Or you can feed it through stdin by adding a `-` as the last command parameter:
```
$ garage json-api CreateAdminToken -
{"name": "test"}
<EOF>
```
For admin API calls that would have taken query parameters in their HTTP version, these parameters can be passed in the JSON body object:
```
$ garage json-api GetAdminTokenInfo '{"id":"b0e6e0ace2c0b2aca4cdb2de"}'
```
For admin API calls that take both query parameters and a JSON body, combine them in the following fashion:
```
$ garage json-api UpdateAdminToken '{"id":"b0e6e0ace2c0b2aca4cdb2de", "body":{"name":"not a test"}}'
```
## Special administration API endpoints
### Metrics `GET /metrics`
#### Metrics `GET /metrics`
Returns internal Garage metrics in Prometheus format.
The metrics are directly documented when returned by the API.
**Example:**
### Cluster operations
```
$ curl -i http://localhost:3903/metrics
HTTP/1.1 200 OK
content-type: text/plain; version=0.0.4
content-length: 12145
date: Tue, 08 Aug 2023 07:25:05 GMT
These endpoints are defined on a dedicated [Redocly page](https://garagehq.deuxfleurs.fr/api/garage-admin-v0.html). You can also download its [OpenAPI specification](https://garagehq.deuxfleurs.fr/api/garage-admin-v0.yml).
# HELP api_admin_error_counter Number of API calls to the various Admin API endpoints that resulted in errors
# TYPE api_admin_error_counter counter
api_admin_error_counter{api_endpoint="CheckWebsiteEnabled",status_code="400"} 1
api_admin_error_counter{api_endpoint="CheckWebsiteEnabled",status_code="404"} 3
# HELP api_admin_request_counter Number of API calls to the various Admin API endpoints
# TYPE api_admin_request_counter counter
api_admin_request_counter{api_endpoint="CheckWebsiteEnabled"} 7
api_admin_request_counter{api_endpoint="Health"} 3
# HELP api_admin_request_duration Duration of API calls to the various Admin API endpoints
...
Requesting the API from the command line can be as simple as running:
```bash
curl -H 'Authorization: Bearer s3cr3t' http://localhost:3903/v0/status | jq
```
### Health `GET /health`
Returns `200 OK` if enough nodes are up to have a quorum (ie. serve requests),
otherwise returns `503 Service Unavailable`.
**Example:**
```
$ curl -i http://localhost:3903/health
HTTP/1.1 200 OK
content-type: text/plain
content-length: 102
date: Tue, 08 Aug 2023 07:22:38 GMT
Garage is fully operational
Consult the full health check API endpoint at /v2/GetClusterHealth for more details
```
### On-demand TLS `GET /check`
To prevent abuse for on-demand TLS, Caddy developers have specified an endpoint that can be queried by the reverse proxy
to know if a given domain is allowed to get a certificate. Garage implements these endpoints to tell if a given domain is handled by Garage or is garbage.
Garage responds with the following logic:
- If the domain matches the pattern `<bucket-name>.<s3_api.root_domain>`, returns 200 OK
- If the domain matches the pattern `<bucket-name>.<s3_web.root_domain>` and website is configured for `<bucket>`, returns 200 OK
- If the domain matches the pattern `<bucket-name>` and website is configured for `<bucket>`, returns 200 OK
- Otherwise, returns 404 Not Found, 400 Bad Request or 5xx requests.
*Note 1: because in the path-style URL mode, there is only one domain that is not known by Garage, hence it is not supported by this API endpoint.
You must manually declare the domain in your reverse-proxy. Idem for K2V.*
*Note 2: buckets in a user's namespace are not supported yet by this endpoint. This is a limitation of this endpoint currently.*
**Example:** Suppose a Garage instance is configured with `s3_api.root_domain = .s3.garage.localhost` and `s3_web.root_domain = .web.garage.localhost`.
With a private `media` bucket (name in the global namespace, website is disabled), the endpoint will feature the following behavior:
```
$ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=media.s3.garage.localhost
200
$ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=media
400
$ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=media.web.garage.localhost
400
```
With a public `example.com` bucket (name in the global namespace, website is activated), the endpoint will feature the following behavior:
```
$ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=example.com.s3.garage.localhost
200
$ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=example.com
200
$ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=example.com.web.garage.localhost
200
```
**References:**
- [Using On-Demand TLS](https://caddyserver.com/docs/automatic-https#using-on-demand-tls)
- [Add option for a backend check to approve use of on-demand TLS](https://github.com/caddyserver/caddy/pull/1939)
- [Serving tens of thousands of domains over HTTPS with Caddy](https://caddy.community/t/serving-tens-of-thousands-of-domains-over-https-with-caddy/11179)
For more advanced use cases, we recommend using a SDK.
[Go to the "Build your own app" section to know how to use our SDKs](@/documentation/build/_index.md)
File diff suppressed because it is too large Load Diff
+13 -21
View File
@@ -35,22 +35,7 @@ This makes setting up and administering storage clusters, we hope, as easy as it
A Garage cluster can very easily evolve over time, as storage nodes are added or removed.
Garage will automatically rebalance data between nodes as needed to ensure the desired number of copies.
Read about cluster layout management [here](@/documentation/operations/layout.md).
### Several replication modes
Garage supports a variety of replication modes, with configurable replica count,
and with various levels of consistency, in order to adapt to a variety of usage scenarios.
Read our reference page on [supported replication modes](@/documentation/reference-manual/configuration.md#replication_factor)
to select the replication mode best suited to your use case (hint: in most cases, `replication_factor = 3` is what you want).
### Compression and deduplication
All data stored in Garage is deduplicated, and optionally compressed using
Zstd. Objects uploaded to Garage are chunked in blocks of constant sizes (see
[`block_size`](@/documentation/reference-manual/configuration.md#block_size)),
and the hashes of individual blocks are used to dispatch them to storage nodes
and to deduplicate them.
Read about cluster layout management [here](@/documentation/reference-manual/layout.md).
### No RAFT slowing you down
@@ -61,7 +46,14 @@ directed to a Garage cluster can be handled independently of one another instead
of going through a central bottleneck (the leader node).
As a consequence, requests can be handled much faster, even in cases where latency
between cluster nodes is important (see our [benchmarks](@/documentation/design/benchmarks/index.md) for data on this).
This is particularly useful when nodes are far from one another and talk to one other through standard Internet connections.
This is particularly usefull when nodes are far from one another and talk to one other through standard Internet connections.
### Several replication modes
Garage supports a variety of replication modes, with 1 copy, 2 copies or 3 copies of your data,
and with various levels of consistency, in order to adapt to a variety of usage scenarios.
Read our reference page on [supported replication modes](@/documentation/reference-manual/configuration.md#replication-mode)
to select the replication mode best suited to your use case (hint: in most cases, `replication_mode = "3"` is what you want).
### Web server for static websites
@@ -84,13 +76,13 @@ exposing the same content under different domain names.
Garage also supports bucket aliases which are local to a single user:
this allows different users to have different buckets with the same name, thus avoiding naming collisions.
This can be helpful for instance if you want to write an application that creates per-user buckets with always the same name.
This can be helpfull for instance if you want to write an application that creates per-user buckets with always the same name.
This feature is totally invisible to S3 clients and does not break compatibility with AWS.
### Cluster administration API
Garage provides a fully-fledged REST API to administer your cluster programmatically.
Garage provides a fully-fledged REST API to administer your cluster programatically.
Functionality included in the admin API include: setting up and monitoring
cluster nodes, managing access credentials, and managing storage buckets and bucket aliases.
A full reference of the administration API is available [here](@/documentation/reference-manual/admin-api.md).
@@ -100,7 +92,7 @@ A full reference of the administration API is available [here](@/documentation/r
Garage makes some internal metrics available in the Prometheus data format,
which allows you to build interactive dashboards to visualize the load and internal state of your storage cluster.
For developers and performance-savvy administrators,
For developpers and performance-savvy administrators,
Garage also supports exporting traces of what it does internally in OpenTelemetry format.
This allows to monitor the time spent at various steps of the processing of requests,
in order to detect potential performance bottlenecks.
@@ -129,5 +121,5 @@ related to objects stored in an S3 bucket.
In the context of our research project, [Aérogramme](https://aerogramme.deuxfleurs.fr),
K2V is used to provide metadata and log storage for operations on encrypted e-mail storage.
Learn more on the specification of K2V [here](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/commit/f8be15c37db857e177d543de7be863692628d567/doc/drafts/k2v-spec.md)
Learn more on the specification of K2V [here](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/branch/k2v/doc/drafts/k2v-spec.md)
and on how to enable it in Garage [here](@/documentation/reference-manual/k2v.md).
+4 -3
View File
@@ -3,7 +3,7 @@ title = "K2V"
weight = 100
+++
Starting with version 0.7.2, Garage introduces an optional feature, K2V,
Starting with version 0.7.2, Garage introduces an optionnal feature, K2V,
which is an alternative storage API designed to help efficiently store
many small values in buckets (in opposition to S3 which is more designed
to store large blobs).
@@ -16,10 +16,10 @@ the `k2v` feature flag enabled can be obtained from our download page under
with `-k2v` (example: `v0.7.2-k2v`).
The specification of the K2V API can be found
[here](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/commit/f8be15c37db857e177d543de7be863692628d567/doc/drafts/k2v-spec.md).
[here](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/branch/main/doc/drafts/k2v-spec.md).
This document also includes a high-level overview of K2V's design.
The K2V API uses AWSv4 signatures for authentication, same as the S3 API.
The K2V API uses AWSv4 signatures for authentification, same as the S3 API.
The AWS region used for signature calculation is always the same as the one
defined for the S3 API in the config file.
@@ -55,3 +55,4 @@ cargo build --features cli --bin k2v-cli
The CLI utility is self-documented, run `k2v-cli --help` to learn how to use
it. There is also a short README.md in the `src/k2v-client` folder with some
instructions.
-188
View File
@@ -1,188 +0,0 @@
+++
title = "Known issues"
weight = 80
+++
Issues in each section are roughly sorted by order of decreasing impact, based on actual reports from users.
## Architectural limitations
Issues that are caused by design decisions of Garage internals, and that can't
be fixed without major architectural changes in the codebase.
### Metadata performance issues with many objects
**Related issues:**
- [#851 - Performances collapse with 10 millions pictures in a bucket](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/851)
- [#1222 - Cluster Setup Write Performance Degraded After Writing 10 Million Object (200-300Kb per object)](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/1222)
### Very big objects cause performance degradation
For each object, there is a single metadata entry called a `Version` that
contains a list of all of the data blocks in the object. For very big objects,
this entry can contain thousands of block references. During the uploading of
an object, this metadata entry needs to be read, deserialized, reserialized and
written for each individual data block uploaded. This means that the
complexity of an upload is `O(n²)` in the number of blocks needed.
This manifests by excessive metadata I/O and CPU usage, and uploads eventually stalling.
**Mitigation:** Increase the `block_size` configuration parameter to reduce the
number of blocks. Make sure multipart uploads use chunks that are at least
`block_size` in size, and that are an exact multiple of `block_size` to avoid
the creation of smaller blocks.
**Long-term solution:** An architectural change in the metadata system would be
required to store block lists in many independent metadata entries instead of
one single big entry per object.
**Related issues:**
- [#662 - Large Files fail to upload](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/662)
- [#1366 - High CPU usage and performance degradation during long multipart uploads](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/1366)
### No conditional writes / locking / WORM support (`if-none-match`, ...)
This is structurally impossible to implement in Garage due to the lack of a consensus algorithm,
which is one of Garage's core design choices which we cannot reconsider.
A semi-working, *unsafe* implementation of WORM and object locking could be
implemented, with the following constraint: only after the completion of the
first write (in case of WORM) or the setting of a lock (for object lock) can we
guarantee that the object cannot be overwritten. In case where an overwrite
requests arrives at the same time as the initial request to write or to lock
the object, we cannot implement a safe and consistent way to reject it. This
means that many practical use-cases for `if-none-match` cannot be supported
(e.g. using it to implement mutual exclusion between concurrent writers).
**Related issues:**
- [#1052 - Support conditional writes](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/1052)
- [#1127 - Feature Request: WORM (Write Once Read Many) / Object Lock Support](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/1127)
### `CreateBucket` race condition
Also due to the lack of a consensus algorithm, there is no mutual exclusion
between concurrent `CreateBucket` requests using the same bucket name.
**Related issues:**
- [#649 - Race condition in CreateBucket](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/649)
### Metadata and data have the same replication factor
There is a single `replication_factor` in the configuration file that applies both to data blocks and metadata entries.
This makes clusters with `replication_factor = 1` particularly vulnerable in cases of metadata corruption (see below), as there
is a single copy of the metadata for each object even in multi-node clusters.
**Mitigation:** Do not use `replication_factor = 1`.
**Long-term solution:** We want to allow scenarios such as replicating the
metadata on 2, 3 or more nodes and the data on only 1 or 2 nodes (for example),
so that the metadata can benefit from better redundancy without increasing the
storage costs for the entire dataset. This will require some important changes
in the codebase.
**Related issues:**
- [#720 - Separate replication modes for metadata/data](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/720)
### Node count limitation
Garage will have issues in clusters with too many nodes, it will not be able to
spread data uniformly among nodes and some nodes will fill up faster than
other. This starts to manifest when the number of nodes is bigger than `10 ×
replication_factor`. This is due to the fact that Garage uses only 256
partitions internally.
**Mitigation:** Build clusters with fewer, bigger nodes.
**Potential solution:** This can be fixed by increasing the number of
partitions in Garage. The code paths exist, there is [a `const`
somewhere](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/commit/6fd9bba0cb55062cb1725ab961b7fa8acb9dcc61/src/rpc/layout/mod.rs#L35)
that theoretically allows to increase the number of partitions up to `2^16`,
but this has not been tested so there might be bugs.
### Buckets are not sharded
For each bucket, the first metadata layer that contains an index of all objects
is not sharded. This index, which includes the names and all metadata (size,
headers, ...) for each object, is stored on `$replication_factor` nodes.
For instance with `replication_factor = 3`, a given bucket will use only 3
specific nodes for this index (chosen at random when the bucket is created) to
store this index. In a multi-zone deployments, these nodes will be spread in
different zones. Each bucket uses a different set of 3 random nodes for its
index.
As a consequence, very large buckets might cause uneven load distribution
within a cluster. If all of the requests on a cluster are for objects in a
single bucket, then the `$replication_factor` nodes that store the index will
become a hotspot in the cluster, with more intensive metadata access patterns.
There is no way of choosing which nodes will have this role.
Currently, we have no report of this being an issue in practice.
**Mitigation:** This impacts in particular clusters that are used for a single
purpose with a single bucket. This can be solved by dividing your dataset among
many buckets, using a client-side sharding strategy that you will have to
design. Use at least as many buckets as you have nodes on your cluster.
## Bugs
Known bugs that are complex to diagnose and fix, and therefore have not been
fixed yet.
### LMDB metadata corruption
Many users have reported situations where the LMDB metadata db becomes
corrupted, sometimes after a forced shutdown of Garage or in case of power
loss. A corrupted database file is generally not recoverable.
**Mitigation:** Use a `replication_factor` of at least 2. Configure automatic
snapshotting using `metadata_auto_snapshot_interval` so that in case of
corruption you can rollback to a working database.
Note that taking filesystem-level snapshots of your `metadata_dir`, although it
is much faster and less I/O intensive than Garage's built-in snapshotting, does
not ensure that the snapshot will be consistent. If the snapshot is taking
during a metadata write, the snapshot itself might be corrupted and thus not
usable as a rollback point. Therefore, prefer using
`metadata_auto_snapshot_interval` in all cases.
### Layout updates might require manual intervention
In case of disconnected nodes, when changing the cluster layout to remove these
nodes and add other nodes instead, Garage might not be able to properly evict
the old nodes from the system. This is a built-in security measure to avoid any
inconsistent cluster states.
This manifests by several cluster layout versions staying active even after a
full resync. You can diagnose this situation with `garage layout history`,
which will give you instructions to fix it.
### Tag assignment
In the `garage layout assign` command, the `-t` argument has to be repeated
multiple times to set multiple tags on a node. Writing multiple tags separated
by commas will result in a single string.
## General footguns
Choices made by the developers that users must be aware of if they don't want
to run into potential issues.
### Resync tranquility is conservative by default
By default, the worker parameters `resync-tranquility` and `resync-worker-count` are set to very conservative values, to avoid overloading nodes with I/O when data needs to be resynchronized between nodes.
This can cause issues where the resync queue grows faster than it can be cleared, which in turn causes performance issues in the rest of Garage.
This situation is indicated by a big resync queue with few resync errors (the queue is not caused by a disconnected/malfunctionning node).
To fix it, increase the number of resync workers and reduce the resync tranquility. For instance, if you want to resync as fast as possible:
```
garage worker set -a resync-worker-count 8
garage worker set -a resync-tranquility 0
```
+77
View File
@@ -0,0 +1,77 @@
+++
title = "Cluster layout management"
weight = 50
+++
The cluster layout in Garage is a table that assigns to each node a role in
the cluster. The role of a node in Garage can either be a storage node with
a certain capacity, or a gateway node that does not store data and is only
used as an API entry point for faster cluster access.
An introduction to building cluster layouts can be found in the [production deployment](@/documentation/cookbook/real-world.md) page.
## How cluster layouts work in Garage
In Garage, a cluster layout is composed of the following components:
- a table of roles assigned to nodes
- a version number
Garage nodes will always use the cluster layout with the highest version number.
Garage nodes also maintain and synchronize between them a set of proposed role
changes that haven't yet been applied. These changes will be applied (or
canceled) in the next version of the layout
The following commands insert modifications to the set of proposed role changes
for the next layout version (but they do not create the new layout immediately):
```bash
garage layout assign [...]
garage layout remove [...]
```
The following command can be used to inspect the layout that is currently set in the cluster
and the changes proposed for the next layout version, if any:
```bash
garage layout show
```
The following commands create a new layout with the specified version number,
that either takes into account the proposed changes or cancels them:
```bash
garage layout apply --version <new_version_number>
garage layout revert --version <new_version_number>
```
The version number of the new layout to create must be 1 + the version number
of the previous layout that existed in the cluster. The `apply` and `revert`
commands will fail otherwise.
## Warnings about Garage cluster layout management
**Warning: never make several calls to `garage layout apply` or `garage layout
revert` with the same value of the `--version` flag. Doing so can lead to the
creation of several different layouts with the same version number, in which
case your Garage cluster will become inconsistent until fixed.** If a call to
`garage layout apply` or `garage layout revert` has failed and `garage layout
show` indicates that a new layout with the given version number has not been
set in the cluster, then it is fine to call the command again with the same
version number.
If you are using the `garage` CLI by typing individual commands in your
shell, you shouldn't have much issues as long as you run commands one after
the other and take care of checking the output of `garage layout show`
before applying any changes.
If you are using the `garage` CLI to script layout changes, follow the following recommendations:
- Make all of your `garage` CLI calls to the same RPC host. Do not use the
`garage` CLI to connect to individual nodes to send them each a piece of the
layout changes you are making, as the changes propagate asynchronously
between nodes and might not all be taken into account at the time when the
new layout is applied.
- **Only call `garage layout apply` once**, and call it **strictly after** all
of the `layout assign` and `layout remove` commands have returned.
+1 -118
View File
@@ -27,112 +27,6 @@ Exposes the Garage replication factor configured on the node
garage_replication_factor 3
```
#### `garage_local_disk_avail` and `garage_local_disk_total` (gauge)
Reports the available and total disk space on each node, for data and metadata separately.
```
garage_local_disk_avail{volume="data"} 540341960704
garage_local_disk_avail{volume="metadata"} 540341960704
garage_local_disk_total{volume="data"} 763063566336
garage_local_disk_total{volume="metadata"} 763063566336
```
### Cluster health status metrics
#### `cluster_healthy` (gauge)
Whether all storage nodes are connected (0 or 1)
```
cluster_healthy 0
```
#### `cluster_available` (gauge)
Whether all requests can be served, even if some storage nodes are disconnected
```
cluster_available 1
```
#### `cluster_connected_nodes` (gauge)
Number of nodes currently connected
```
cluster_connected_nodes 3
```
#### `cluster_known_nodes` (gauge)
Number of nodes already seen once in the cluster
```
cluster_known_nodes 3
```
#### `cluster_layout_node_connected` (gauge)
Connection status for individual nodes of the cluster layout
```
cluster_layout_node_connected{id="62b218d848e86a64",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 1
cluster_layout_node_connected{id="a11c7cf18af29737",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 0
cluster_layout_node_connected{id="a235ac7695e0c54d",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 1
cluster_layout_node_connected{id="b10c110e4e854e5a",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 1
```
#### `cluster_layout_node_disconnected_time` (gauge)
Time (in seconds) since last connection to individual nodes of the cluster layout
```
cluster_layout_node_disconnected_time{id="62b218d848e86a64",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 0
cluster_layout_node_disconnected_time{id="a235ac7695e0c54d",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 0
cluster_layout_node_disconnected_time{id="b10c110e4e854e5a",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 0
```
#### `cluster_storage_nodes` (gauge)
Number of storage nodes declared in the current layout
```
cluster_storage_nodes 4
```
#### `cluster_storage_nodes_ok` (gauge)
Number of storage nodes currently connected
```
cluster_storage_nodes_ok 3
```
#### `cluster_partitions` (gauge)
Number of partitions in the layout (this is always 256)
```
cluster_partitions 256
```
#### `cluster_partitions_all_ok` (gauge)
Number of partitions for which all storage nodes are connected
```
cluster_partitions_all_ok 64
```
#### `cluster_partitions_quorum` (gauge)
Number of partitions for which we have a quorum of connected nodes and all requests can be served
```
cluster_partitions_quorum 256
```
### Metrics of the API endpoints
#### `api_admin_request_counter` (counter)
@@ -225,17 +119,6 @@ block_bytes_read 120586322022
block_bytes_written 3386618077
```
#### `block_ram_buffer_free_kb` (gauge)
Kibibytes available for buffering blocks that have to be sent to remote nodes.
When clients send too much data to this node and a storage node is not receiving
data fast enough due to slower network conditions, this will decrease down to
zero and backpressure will be applied.
```
block_ram_buffer_free_kb 219829
```
#### `block_compression_level` (counter)
Exposes the block compression level configured for the Garage node.
@@ -392,7 +275,7 @@ table_merkle_updater_todo_queue_length{table_name="block_ref"} 0
#### `table_sync_items_received`, `table_sync_items_sent` (counters)
Number of data items sent to/received from other nodes during resync procedures
Number of data items sent to/recieved from other nodes during resync procedures
```
table_sync_items_received{from="<remote node>",table_name="bucket_v2"} 3
+20 -24
View File
@@ -23,17 +23,16 @@ Feel free to open a PR to suggest fixes this table. Minio is missing because the
- 2022-05-25 - Many Ceph S3 endpoints are not documented but implemented. Following a notification from the Ceph community, we added them.
## High-level features
| Feature | Garage | [Openstack Swift](https://docs.openstack.org/swift/latest/s3_compat.html) | [Ceph Object Gateway](https://docs.ceph.com/en/latest/radosgw/s3/) | [Riak CS](https://docs.riak.com/riak/cs/2.1.1/references/apis/storage/s3/index.html) | [OpenIO](https://docs.openio.io/latest/source/arch-design/s3_compliancy.html) |
|------------------------------|----------------------------------|-----------------|---------------|---------|-----|
| [signature v2](https://docs.aws.amazon.com/AmazonS3/latest/API/Appendix-Sigv2.html) (deprecated) | ❌ Missing | ✅ | ✅ | ✅ | ✅ |
| [signature v2](https://docs.aws.amazon.com/general/latest/gr/signature-version-2.html) (deprecated) | ❌ Missing | ✅ | ✅ | ✅ | ✅ |
| [signature v4](https://docs.aws.amazon.com/AmazonS3/latest/API/sig-v4-authenticating-requests.html) | ✅ Implemented | ✅ | ✅ | ❌ | ✅ |
| [URL path-style](https://docs.aws.amazon.com/AmazonS3/latest/userguide/VirtualHosting.html#path-style-access) (eg. `host.tld/bucket/key`) | ✅ Implemented | ✅ | ✅ | ❓| ✅ |
| [URL vhost-style](https://docs.aws.amazon.com/AmazonS3/latest/userguide/VirtualHosting.html#virtual-hosted-style-access) URL (eg. `bucket.host.tld/key`) | ✅ Implemented | ❌| ✅| ✅ | ✅ |
| [Presigned URLs](https://docs.aws.amazon.com/AmazonS3/latest/userguide/ShareObjectPreSignedURL.html) | ✅ Implemented | ❌| ✅ | ✅ | ✅(❓) |
| [SSE-C encryption](https://docs.aws.amazon.com/AmazonS3/latest/userguide/ServerSideEncryptionCustomerKeys.html) | ✅ Implemented | ❓ | ✅ | ❌ | ✅ |
| [Bucket versioning](https://docs.aws.amazon.com/AmazonS3/latest/userguide/Versioning.html) | ❌ Missing | ✅ | ✅ | ❌ | ✅ |
*Note:* OpenIO does not says if it supports presigned URLs. Because it is part
of signature v4 and they claim they support it without additional precisions,
@@ -45,7 +44,7 @@ we suppose that OpenIO supports presigned URLs.
All endpoints that are missing on Garage will return a 501 Not Implemented.
Some `x-amz-` headers are not implemented.
### Core endpoints
### Core endoints
| Endpoint | Garage | [Openstack Swift](https://docs.openstack.org/swift/latest/s3_compat.html) | [Ceph Object Gateway](https://docs.ceph.com/en/latest/radosgw/s3/) | [Riak CS](https://docs.riak.com/riak/cs/2.1.1/references/apis/storage/s3/index.html) | [OpenIO](https://docs.openio.io/latest/source/arch-design/s3_compliancy.html) |
|------------------------------|----------------------------------|-----------------|---------------|---------|-----|
@@ -76,13 +75,16 @@ but these endpoints are documented in [Red Hat Ceph Storage - Chapter 2. Ceph Ob
| Endpoint | Garage | [Openstack Swift](https://docs.openstack.org/swift/latest/s3_compat.html) | [Ceph Object Gateway](https://docs.ceph.com/en/latest/radosgw/s3/) | [Riak CS](https://docs.riak.com/riak/cs/2.1.1/references/apis/storage/s3/index.html) | [OpenIO](https://docs.openio.io/latest/source/arch-design/s3_compliancy.html) |
|------------------------------|----------------------------------|-----------------|---------------|---------|-----|
| [AbortMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_AbortMultipartUpload.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ |
| [CompleteMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_CompleteMultipartUpload.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ |
| [CreateMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_CreateMultipartUpload.html) | ✅ Implemented | ✅| ✅ | ✅ | ✅ |
| [ListMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListMultipartUpload.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ |
| [ListParts](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListParts.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ |
| [UploadPart](https://docs.aws.amazon.com/AmazonS3/latest/API/API_UploadPart.html) | ✅ Implemented | ✅ | ✅| ✅ | ✅ |
| [UploadPartCopy](https://docs.aws.amazon.com/AmazonS3/latest/API/API_UploadPartCopy.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ |
| [AbortMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_AbortMultipartUpload.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ |
| [CompleteMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_CompleteMultipartUpload.html) | ✅ Implemented (see details below) | ✅ | ✅ | ✅ | ✅ |
| [CreateMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_CreateMultipartUpload.html) | ✅ Implemented | ✅| ✅ | ✅ | ✅ |
| [ListMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListMultipartUpload.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ |
| [ListParts](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListParts.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ |
| [UploadPart](https://docs.aws.amazon.com/AmazonS3/latest/API/API_UploadPart.html) | ✅ Implemented (see details below) | ✅ | ✅| ✅ | ✅ |
| [UploadPartCopy](https://docs.aws.amazon.com/AmazonS3/latest/API/API_UploadPartCopy.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ |
Our implementation of Multipart Upload is currently a bit more restrictive than Amazon's one in some edge cases.
For more information, please refer to our [issue tracker](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/204).
### Website endpoints
@@ -125,22 +127,15 @@ If you need this feature, please [share your use case in our dedicated issue](ht
| Endpoint | Garage | [Openstack Swift](https://docs.openstack.org/swift/latest/s3_compat.html) | [Ceph Object Gateway](https://docs.ceph.com/en/latest/radosgw/s3/) | [Riak CS](https://docs.riak.com/riak/cs/2.1.1/references/apis/storage/s3/index.html) | [OpenIO](https://docs.openio.io/latest/source/arch-design/s3_compliancy.html) |
|------------------------------|----------------------------------|-----------------|---------------|---------|-----|
| [DeleteBucketLifecycle](https://docs.aws.amazon.com/AmazonS3/latest/API/API_DeleteBucketLifecycle.html) | ✅ Implemented | ❌| ✅| ❌| ✅|
| [GetBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_GetBucketLifecycleConfiguration.html) | ✅ Implemented | ❌| ✅ | ❌| ✅|
| [PutBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_PutBucketLifecycleConfiguration.html) | ⚠ Partially implemented (see below) | ❌| ✅ | ❌| ✅|
| [DeleteBucketLifecycle](https://docs.aws.amazon.com/AmazonS3/latest/API/API_DeleteBucketLifecycle.html) | ❌ Missing | ❌| ✅| ❌| ✅|
| [GetBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_GetBucketLifecycleConfiguration.html) | ❌ Missing | ❌| ✅ | ❌| ✅|
| [PutBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_PutBucketLifecycleConfiguration.html) | ❌ Missing | ❌| ✅ | ❌| ✅|
| [GetBucketVersioning](https://docs.aws.amazon.com/AmazonS3/latest/API/API_GetBucketVersioning.html) | ❌ Stub (see below) | ✅| ✅ | ❌| ✅|
| [ListObjectVersions](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListObjectVersions.html) | ❌ Missing | ❌| ✅ | ❌| ✅|
| [PutBucketVersioning](https://docs.aws.amazon.com/AmazonS3/latest/API/API_PutBucketVersioning.html) | ❌ Missing | ❌| ✅| ❌| ✅|
**PutBucketLifecycleConfiguration:** The only actions supported are
`AbortIncompleteMultipartUpload` and `Expiration` (without the
`ExpiredObjectDeleteMarker` field). All other operations are dependent on
either bucket versioning or storage classes which Garage currently does not
implement. The deprecated `Prefix` member directly in the the `Rule`
structure/XML tag is not supported, specified prefixes must be inside the
`Filter` structure/XML tag.
**GetBucketVersioning:** Stub implementation which always returns "versioning not enabled", since Garage does not yet support bucket versioning.
**GetBucketVersioning:** Stub implementation (Garage does not yet support versionning so this always returns "versionning not enabled").
### Replication endpoints
@@ -155,7 +150,7 @@ Please open an issue if you have a use case for replication.
*Note: Ceph documentation briefly says that Ceph supports
[replication through the S3 API](https://docs.ceph.com/en/latest/radosgw/multisite-sync-policy/#s3-replication-api)
but with some limitations.
Additionally, replication endpoints are not documented in the S3 compatibility page so I don't know what kind of support we can expect.*
Additionaly, replication endpoints are not documented in the S3 compatibility page so I don't know what kind of support we can expect.*
### Locking objects
@@ -197,7 +192,7 @@ Please open an issue if you have a use case.
### Vendor specific endpoints
<details><summary>Display Amazon specific endpoints</summary>
<details><summary>Display Amazon specifc endpoints</summary>
| Endpoint | Garage | [Openstack Swift](https://docs.openstack.org/swift/latest/s3_compat.html) | [Ceph Object Gateway](https://docs.ceph.com/en/latest/radosgw/s3/) | [Riak CS](https://docs.riak.com/riak/cs/2.1.1/references/apis/storage/s3/index.html) | [OpenIO](https://docs.openio.io/latest/source/arch-design/s3_compliancy.html) |
@@ -234,3 +229,4 @@ Please open an issue if you have a use case.
| [SelectObjectContent](https://docs.aws.amazon.com/AmazonS3/latest/API/API_SelectObjectContent.html) | ❌ Missing | ❌| ❌| ❌| ❌|
</details>
+1 -1
View File
@@ -1,6 +1,6 @@
+++
title = "Working Documents"
weight = 90
weight = 8
sort_by = "weight"
template = "documentation.html"
+++
@@ -3,7 +3,7 @@ title = "S3 compatibility target"
weight = 5
+++
If there is a specific S3 functionality you have a need for, feel free to open
If there is a specific S3 functionnality you have a need for, feel free to open
a PR to put the corresponding endpoints higher in the list. Please explain
your motivations for doing so in the PR message.
+4 -4
View File
@@ -42,7 +42,7 @@ The general principle are similar, but details have not been updated.**
A version is defined by the existence of at least one entry in the blocks table for a certain version UUID.
We must keep the following invariant: if a version exists in the blocks table, it has to be referenced in the objects table.
We explicitly manage concurrent versions of an object: the version timestamp and version UUID columns are index columns, thus we may have several concurrent versions of an object.
Important: before deleting an older version from the objects table, we must make sure that we did a successful delete of the blocks of that version from the blocks table.
Important: before deleting an older version from the objects table, we must make sure that we did a successfull delete of the blocks of that version from the blocks table.
Thus, the workflow for reading an object is as follows:
@@ -68,7 +68,7 @@ Workflow for DELETE:
1. Check write permission (LDAP)
2. Get current version (or versions) in object table
3. Do the deletion of those versions NOT IN A BACKGROUND JOB THIS TIME
4. Return success to the user if we were able to delete blocks from the blocks table and entries from the object table
4. Return succes to the user if we were able to delete blocks from the blocks table and entries from the object table
To delete a version:
@@ -92,10 +92,10 @@ Known issue: if someone is reading from a version that we want to delete and the
- file path = /meta/(first 3 hex digits of hash)/(rest of hash)
- map block hash -> set of version UUIDs where it is referenced
Useful metadata:
Usefull metadata:
- list of versions that reference this block in the Casandra table, so that we can do GC by checking in Cassandra that the lines still exist
- list of other nodes that we know have acknowledged a write of this block, useful in the rebalancing algorithm
- list of other nodes that we know have acknowledged a write of this block, usefull in the rebalancing algorithm
Write strategy: have a single thread that does all write IO so that it is serialized (or have several threads that manage independent parts of the hash space). When writing a blob, write it to a temporary file, close, then rename so that a concurrent read gets a consistent result (either not found or found with whole content).
+3 -3
View File
@@ -49,12 +49,12 @@ The ring construction that selects `n_token` random positions for each nodes giv
is not well-balanced: the space between the tokens varies a lot, and some partitions are thus bigger than others.
This problem was demonstrated in the original Dynamo DB paper.
To solve this, we want to apply a better second method for partitioning our dataset:
To solve this, we want to apply a better second method for partitionning our dataset:
1. fix an initially large number of partitions (say 1024) with evenly-spaced delimiters,
2. attribute each partition randomly to a node, with a probability
proportional to its capacity (which `n_tokens` represented in the first
proportionnal to its capacity (which `n_tokens` represented in the first
method)
For now we continue using the multi-DC ring walking described above.
@@ -66,7 +66,7 @@ I have studied two ways to do the attribution of partitions to nodes, in a way t
MagLev provided significantly better balancing, as it guarantees that the exact
same number of partitions is attributed to all nodes that have the same
capacity (and that this number is proportional to the node's capacity, except
capacity (and that this number is proportionnal to the node's capacity, except
for large values), however in both cases:
- the distribution is still bad, because we use the naive multi-DC ring walking
+2 -2
View File
@@ -1,6 +1,6 @@
+++
title = "Migrating from 0.3 to 0.4"
weight = 80
weight = 20
+++
**Migrating from 0.3 to 0.4 is unsupported. This document is only intended to
@@ -68,7 +68,7 @@ The migration steps are as follows:
5. Turn off Garage 0.3
6. Backup metadata folders if you can (i.e. if you have space to do it
somewhere). Backuping data folders could also be useful but that's much
somewhere). Backuping data folders could also be usefull but that's much
harder to do. If your filesystem supports snapshots, this could be a good
time to use them.
+1 -1
View File
@@ -1,6 +1,6 @@
+++
title = "Migrating from 0.5 to 0.6"
weight = 75
weight = 15
+++
**This guide explains how to migrate to 0.6 if you have an existing 0.5 cluster.
+2 -2
View File
@@ -1,6 +1,6 @@
+++
title = "Migrating from 0.6 to 0.7"
weight = 74
weight = 14
+++
**This guide explains how to migrate to 0.7 if you have an existing 0.6 cluster.
We don't recommend trying to migrate to 0.7 directly from 0.5 or older.**
@@ -19,7 +19,7 @@ The migration steps are as follows:
2. Disable API and web access. Garage does not support disabling
these endpoints but you can change the port number or stop your reverse
proxy for instance.
3. Check once again that your cluster is healthy. Run again `garage repair --all-nodes --yes tables` which is quick.
3. Check once again that your cluster is healty. Run again `garage repair --all-nodes --yes tables` which is quick.
Also check your queues are empty, run `garage stats` to query them.
4. Turn off Garage v0.6
5. Backup the metadata folder of all your nodes: `cd /var/lib/garage ; tar -acf meta-v0.6.tar.zst meta/`
+1 -1
View File
@@ -1,6 +1,6 @@
+++
title = "Migrating from 0.7 to 0.8"
weight = 73
weight = 13
+++
**This guide explains how to migrate to 0.8 if you have an existing 0.7 cluster.
@@ -1,72 +0,0 @@
+++
title = "Migrating from 0.8 to 0.9"
weight = 72
+++
**This guide explains how to migrate to 0.9 if you have an existing 0.8 cluster.
We don't recommend trying to migrate to 0.9 directly from 0.7 or older.**
This migration procedure has been tested on several clusters without issues.
However, it is still a *critical procedure* that might cause issues.
**Make sure to back up all your data before attempting it!**
You might also want to read our [general documentation on upgrading Garage](@/documentation/operations/upgrading.md).
The following are **breaking changes** in Garage v0.9 that require your attention when migrating:
- LMDB is now the default metadata db engine and Sled is deprecated. If you were using Sled, make sure to specify `db_engine = "sled"` in your configuration file, or take the time to [convert your database](https://garagehq.deuxfleurs.fr/documentation/reference-manual/configuration/#db-engine-since-v0-8-0).
- Capacity values are now in actual byte units. The translation from the old layout will assign 1 capacity = 1Gb by default, which might be wrong for your cluster. This does not cause any data to be moved around, but you might want to re-assign correct capacity values post-migration.
- Multipart uploads that were started in Garage v0.8 will not be visible in Garage v0.9 and will have to be restarted from scratch.
- Changes to the admin API: some `v0/` endpoints have been replaced by `v1/` counterparts with updated/uniformized syntax. All other endpoints have also moved to `v1/` by default, without syntax changes, but are still available under `v0/` for compatibility.
## Simple migration procedure (takes cluster offline for a while)
The migration steps are as follows:
1. Disable API and web access. You may do this by stopping your reverse proxy or by commenting out
the `api_bind_addr` values in your `config.toml` file and restarting Garage.
2. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`,
check the logs and check that all data seems to be synced correctly between
nodes. If you have time, do additional checks (`versions`, `block_refs`, etc.)
3. Check that the block resync queue and Merkle queue are empty:
run `garage stats -a` to query them or inspect metrics in the Grafana dashboard.
4. Turn off Garage v0.8
5. **Backup the metadata folder of all your nodes!** For instance, use the following command
if your metadata directory is `/var/lib/garage/meta`: `cd /var/lib/garage ; tar -acf meta-v0.8.tar.zst meta/`
6. Install Garage v0.9
7. Update your configuration file if necessary.
8. Turn on Garage v0.9
9. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`.
Wait for a full table sync to run.
10. Your upgraded cluster should be in a working state. Re-enable API and Web
access and check that everything went well.
11. Monitor your cluster in the next hours to see if it works well under your production load, report any issue.
12. You might want to assign correct capacity values to all your nodes. Doing so might cause data to be moved
in your cluster, which should also be monitored carefully.
## Minimal downtime migration procedure
The migration to Garage v0.9 can be done with almost no downtime,
by restarting all nodes at once in the new version.
The migration steps are as follows:
1. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`,
check the logs and check that all data seems to be synced correctly between
nodes. If you have time, do additional checks (`versions`, `block_refs`, etc.)
2. Turn off each node individually; back up its metadata folder (see above); turn it back on again.
This will allow you to take a backup of all nodes without impacting global cluster availability.
You can do all nodes of a single zone at once as this does not impact the availability of Garage.
3. Prepare your binaries and configuration files for Garage v0.9
4. Shut down all v0.8 nodes simultaneously, and restart them all simultaneously in v0.9.
Use your favorite deployment tool (Ansible, Kubernetes, Nomad) to achieve this as fast as possible.
Garage v0.9 should be in a working state as soon as it starts.
5. Proceed with repair and monitoring as described in steps 9-12 above.
-77
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@@ -1,77 +0,0 @@
+++
title = "Migrating from 0.9 to 1.0"
weight = 71
+++
**This guide explains how to migrate to 1.0 if you have an existing 0.9 cluster.
We don't recommend trying to migrate to 1.0 directly from 0.8 or older.**
This migration procedure has been tested on several clusters without issues.
However, it is still a *critical procedure* that might cause issues.
**Make sure to back up all your data before attempting it!**
You might also want to read our [general documentation on upgrading Garage](@/documentation/operations/upgrading.md).
## Changes introduced in v1.0
The following are **breaking changes** in Garage v1.0 that require your attention when migrating:
- The Sled metadata db engine has been **removed**. If your cluster was still
using Sled, you will need to **use a Garage v0.9.x binary** to convert the
database using the `garage convert-db` subcommand. See
[here](@/documentation/reference-manual/configuration.md#db_engine) for the
details of the procedure.
The following syntax changes have been made to the configuration file:
- The `replication_mode` parameter has been split into two parameters:
[`replication_factor`](@/documentation/reference-manual/configuration.md#replication_factor)
and
[`consistency_mode`](@/documentation/reference-manual/configuration.md#consistency_mode).
The old syntax using `replication_mode` is still supported for legacy
reasons and can still be used.
- The parameters `sled_cache_capacity` and `sled_flush_every_ms` have been removed.
## Migration procedure
The migration to Garage v1.0 can be done with almost no downtime,
by restarting all nodes at once in the new version.
The migration steps are as follows:
1. Do a `garage repair --all-nodes --yes tables`, check the logs and check that
all data seems to be synced correctly between nodes. If you have time, do
additional `garage repair` procedures (`blocks`, `versions`, `block_refs`,
etc.)
2. Ensure you have a snapshot of your Garage installation that you can restore
to in case the upgrade goes wrong:
- If you are running Garage v0.9.4 or later, use the `garage meta snapshot
--all` to make a backup snapshot of the metadata directories of your nodes
for backup purposes, and save a copy of the following files in the
metadata directories of your nodes: `cluster_layout`, `data_layout`,
`node_key`, `node_key.pub`.
- If you are running a filesystem such as ZFS or BTRFS that support
snapshotting, you can create a filesystem-level snapshot to be used as a
restoration point if needed.
- In other cases, make a backup using the old procedure: turn off each node
individually; back up its metadata folder (for instance, use the following
command if your metadata directory is `/var/lib/garage/meta`: `cd
/var/lib/garage ; tar -acf meta-v0.9.tar.zst meta/`); turn it back on
again. This will allow you to take a backup of all nodes without
impacting global cluster availability. You can do all nodes of a single
zone at once as this does not impact the availability of Garage.
3. Prepare your updated binaries and configuration files for Garage v1.0
4. Shut down all v0.9 nodes simultaneously, and restart them all simultaneously
in v1.0. Use your favorite deployment tool (Ansible, Kubernetes, Nomad) to
achieve this as fast as possible. Garage v1.0 should be in a working state
as soon as enough nodes have started.
5. Monitor your cluster in the following hours to see if it works well under
your production load.
-70
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@@ -1,70 +0,0 @@
+++
title = "Migrating from 1.0 to 2.0"
weight = 70
+++
**This guide explains how to migrate to v2.x if you have an existing v1.x.x cluster.
We don't recommend trying to migrate to v2.x directly from v0.9.x or older.**
This migration procedure has been tested on several clusters without issues.
However, it is still a *critical procedure* that might cause issues.
**Make sure to back up all your data before attempting it!**
You might also want to read our [general documentation on upgrading Garage](@/documentation/operations/upgrading.md).
## Changes introduced in v2.0
The following are **breaking changes** in Garage v2.0 that require your attention when migrating:
- The administration API has been completely reworked.
Some calls to the `/v1/` endpoints will still work but most will not.
New endpoints are prefixed by `/v2/`. **You will need to update all your code that makes use of the admin API.**
- `replication_mode` is no longer a supported configuration parameter,
please use `replication_factor` and `consistency_mode` instead.
## Migration procedure
The migration to Garage v2.0 can be done with almost no downtime,
by restarting all nodes at once in the new version.
The migration steps are as follows:
1. Do a `garage repair --all-nodes --yes tables`, check the logs and check that
all data seems to be synced correctly between nodes. If you have time, do
additional `garage repair` procedures (`blocks`, `versions`, `block_refs`,
etc.)
2. Ensure you have a snapshot of your Garage installation that you can restore
to in case the upgrade goes wrong, with one of the following options:
- You may use the `garage meta snapshot --all` command
to make a backup snapshot of the metadata directories of your nodes
for backup purposes. Once this command has completed, copy the following
files and directories from the `metadata_dir` of all your nodes
to somewhere safe: `snapshots`, `cluster_layout`, `data_layout`,
`node_key`, `node_key.pub`. (If you have set the `metadata_snapshots_dir`
to a different value in your config file, back up that directory instead.)
- If you are running a filesystem such as ZFS or BTRFS that support
snapshotting, you can create a filesystem-level snapshot of the `metadata_dir`
of all your nodes to be used as a restoration point if needed.
- You may also make a back-up manually: turn off each node
individually; back up its metadata folder (for instance, use the following
command if your metadata directory is `/var/lib/garage/meta`: `cd
/var/lib/garage ; tar -acf meta-v1.0.tar.zst meta/`); turn it back on
again. This will allow you to take a backup of all nodes without
impacting global cluster availability. You can do all nodes of a single
zone at once as this does not impact the availability of Garage.
3. Prepare your updated binaries and configuration files for Garage v2.0.
**Remember to update your configuration file to remove `replication_mode` and replace it by `replication_factor`.**
4. Shut down all v1.0 nodes simultaneously, and restart them all simultaneously
in v2.0. Use your favorite deployment tool (Ansible, Kubernetes, Nomad) to
achieve this as fast as possible. Garage v2.0 should be in a working state
as soon as enough nodes have started.
5. Monitor your cluster in the following hours to see if it works well under
your production load.
@@ -1,6 +1,6 @@
+++
title = "Testing strategy"
weight = 100
weight = 30
+++
@@ -28,16 +28,16 @@ We should try to test in least invasive ways, i.e. minimize the impact of the te
- Not making `garage` a shared library (launch using `execve`, it's perfectly fine)
Instead, we should focus on building a clean outer interface for the `garage` binary,
for example loading configuration using environment variables instead of the configuration file if that's helpful for writing the tests.
for example loading configuration using environnement variables instead of the configuration file if that's helpfull for writing the tests.
There are two reasons for this:
- Keep the source code clean and focused
- Keep the soure code clean and focused
- Test something that is as close as possible as the true garage that will actually be running
Reminder: rules of simplicity, concerning changes to Garage's source code.
Always question what we are doing.
Never do anything just because it looks nice or because we "think" it might be useful at some later point but without knowing precisely why/when.
Never do anything just because it looks nice or because we "think" it might be usefull at some later point but without knowing precisely why/when.
Only do things that make perfect sense in the context of what we currently know.
## References
@@ -71,3 +71,5 @@ Interesting blog posts on the blog of the Sled database:
Misc:
- [mutagen](https://github.com/llogiq/mutagen) - mutation testing is a way to assert our test quality by mutating the code and see if the mutation makes the tests fail
- [fuzzing](https://rust-fuzz.github.io/book/) - cargo supports fuzzing, it could be a way to test our software reliability in presence of garbage data.
+175 -273
View File
@@ -8,22 +8,18 @@ listen address is specified in the `[admin]` section of the configuration
file (see [configuration file
reference](@/documentation/reference-manual/configuration.md))
**WARNING.** At this point, there is no commitment to the stability of the APIs described in this document.
We will bump the version numbers prefixed to each API endpoint each time the syntax
or semantics change, meaning that code that relies on these endpoints will break
**WARNING.** At this point, there is no comittement to stability of the APIs described in this document.
We will bump the version numbers prefixed to each API endpoint at each time the syntax
or semantics change, meaning that code that relies on these endpoint will break
when changes are introduced.
The Garage administration API was introduced in version 0.7.2, and was
changed several times.
**THIS DOCUMENT IS DEPRECATED.** We now have an OpenAPI spec which is automatically generated
from Garage's source code and is always up-to-date. See `doc/api/garage-admin-v2.html`.
Text in this document is no longer kept in sync with the admin API's actual behavior.
The Garage administration API was introduced in version 0.7.2, this document
does not apply to older versions of Garage.
## Access control
The admin API uses two different tokens for access control, that are specified in the config file's `[admin]` section:
The admin API uses two different tokens for acces control, that are specified in the config file's `[admin]` section:
- `metrics_token`: the token for accessing the Metrics endpoint (if this token
is not set in the config file, the Metrics endpoint can be accessed without
@@ -56,132 +52,104 @@ Returns an HTTP status 200 if the node is ready to answer user's requests,
and an HTTP status 503 (Service Unavailable) if there are some partitions
for which a quorum of nodes is not available.
A simple textual message is also returned in a body with content-type `text/plain`.
See `/v2/GetClusterHealth` for an API that also returns JSON output.
### Other special endpoints
#### CheckDomain `GET /check?domain=<domain>`
Checks whether this Garage cluster serves a website for domain `<domain>`.
Returns HTTP 200 Ok if yes, or HTTP 4xx if no website is available for this domain.
See `/v0/health` for an API that also returns JSON output.
### Cluster operations
#### GetClusterStatus `GET /v2/GetClusterStatus`
#### GetClusterStatus `GET /v0/status`
Returns the cluster's current status in JSON, including:
- ID of the node being queried and its version of the Garage daemon
- Live nodes
- Currently configured cluster layout
- Staged changes to the cluster layout
Example response body:
```json
{
"layoutVersion": 5,
"nodes": [
{
"id": "62b218d848e86a64f7fe1909735f29a4350547b54c4b204f91246a14eb0a1a8c",
"role": {
"id": "62b218d848e86a64f7fe1909735f29a4350547b54c4b204f91246a14eb0a1a8c",
"node": "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f",
"garage_version": "git:v0.8.0",
"knownNodes": {
"ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f": {
"addr": "10.0.0.11:3901",
"is_up": true,
"last_seen_secs_ago": 9,
"hostname": "node1"
},
"4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff": {
"addr": "10.0.0.12:3901",
"is_up": true,
"last_seen_secs_ago": 1,
"hostname": "node2"
},
"23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27": {
"addr": "10.0.0.21:3901",
"is_up": true,
"last_seen_secs_ago": 7,
"hostname": "node3"
},
"e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b": {
"addr": "10.0.0.22:3901",
"is_up": true,
"last_seen_secs_ago": 1,
"hostname": "node4"
}
},
"layout": {
"version": 12,
"roles": {
"ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f": {
"zone": "dc1",
"capacity": 100000000000,
"tags": []
"capacity": 4,
"tags": [
"node1"
]
},
"addr": "10.0.0.3:3901",
"hostname": "node3",
"isUp": true,
"lastSeenSecsAgo": 12,
"draining": false,
"dataPartition": {
"available": 660270088192,
"total": 873862266880
"4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff": {
"zone": "dc1",
"capacity": 6,
"tags": [
"node2"
]
},
"metadataPartition": {
"available": 660270088192,
"total": 873862266880
"23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27": {
"zone": "dc2",
"capacity": 10,
"tags": [
"node3"
]
}
},
{
"id": "a11c7cf18af297379eff8688360155fe68d9061654449ba0ce239252f5a7487f",
"role": null,
"addr": "10.0.0.2:3901",
"hostname": "node2",
"isUp": true,
"lastSeenSecsAgo": 11,
"draining": true,
"dataPartition": {
"available": 660270088192,
"total": 873862266880
},
"metadataPartition": {
"available": 660270088192,
"total": 873862266880
}
},
{
"id": "a235ac7695e0c54d7b403943025f57504d500fdcc5c3e42c71c5212faca040a2",
"role": {
"id": "a235ac7695e0c54d7b403943025f57504d500fdcc5c3e42c71c5212faca040a2",
"zone": "dc1",
"capacity": 100000000000,
"tags": []
},
"addr": "127.0.0.1:3904",
"hostname": "lindy",
"isUp": true,
"lastSeenSecsAgo": 2,
"draining": false,
"dataPartition": {
"available": 660270088192,
"total": 873862266880
},
"metadataPartition": {
"available": 660270088192,
"total": 873862266880
}
},
{
"id": "b10c110e4e854e5aa3f4637681befac755154b20059ec163254ddbfae86b09df",
"role": {
"id": "b10c110e4e854e5aa3f4637681befac755154b20059ec163254ddbfae86b09df",
"zone": "dc1",
"capacity": 100000000000,
"tags": []
},
"addr": "10.0.0.1:3901",
"hostname": "node1",
"isUp": true,
"lastSeenSecsAgo": 3,
"draining": false,
"dataPartition": {
"available": 660270088192,
"total": 873862266880
},
"metadataPartition": {
"available": 660270088192,
"total": 873862266880
"stagedRoleChanges": {
"e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b": {
"zone": "dc2",
"capacity": 5,
"tags": [
"node4"
]
}
}
]
}
}
```
#### GetClusterHealth `GET /v2/GetClusterHealth`
#### GetClusterHealth `GET /v0/health`
Returns the cluster's current health in JSON format, with the following variables:
- `status`: one of `healthy`, `degraded` or `unavailable`:
- healthy: Garage node is connected to all storage nodes
- degraded: Garage node is not connected to all storage nodes, but a quorum of write nodes is available for all partitions
- unavailable: a quorum of write nodes is not available for some partitions
- `knownNodes`: the number of nodes this Garage node has had a TCP connection to since the daemon started
- `connectedNodes`: the number of nodes this Garage node currently has an open connection to
- `storageNodes`: the number of storage nodes currently registered in the cluster layout
- `storageNodesOk`: the number of storage nodes to which a connection is currently open
- `status`: one of `Healthy`, `Degraded` or `Unavailable`:
- Healthy: Garage node is connected to all storage nodes
- Degraded: Garage node is not connected to all storage nodes, but a quorum of write nodes is available for all partitions
- Unavailable: a quorum of write nodes is not available for some partitions
- `known_nodes`: the number of nodes this Garage node has had a TCP connection to since the daemon started
- `connected_nodes`: the nubmer of nodes this Garage node currently has an open connection to
- `storage_nodes`: the number of storage nodes currently registered in the cluster layout
- `storage_nodes_ok`: the number of storage nodes to which a connection is currently open
- `partitions`: the total number of partitions of the data (currently always 256)
- `partitionsQuorum`: the number of partitions for which a quorum of write nodes is available
- `partitionsAllOk`: the number of partitions for which we are connected to all storage nodes responsible of storing it
- `partitions_quorum`: the number of partitions for which a quorum of write nodes is available
- `partitions_all_ok`: the number of partitions for which we are connected to all storage nodes responsible of storing it
Contrarily to `GET /health`, this endpoint always returns a 200 OK HTTP response code.
@@ -189,18 +157,18 @@ Example response body:
```json
{
"status": "degraded",
"knownNodes": 3,
"connectedNodes": 3,
"storageNodes": 4,
"storageNodesOk": 3,
"partitions": 256,
"partitionsQuorum": 256,
"partitionsAllOk": 64
"status": "Degraded",
"known_nodes": 3,
"connected_nodes": 2,
"storage_nodes": 3,
"storage_nodes_ok": 2,
"partitions": 256,
"partitions_quorum": 256,
"partitions_all_ok": 0
}
```
#### ConnectClusterNodes `POST /v2/ConnectClusterNodes`
#### ConnectClusterNodes `POST /v0/connect`
Instructs this Garage node to connect to other Garage nodes at specified addresses.
@@ -230,7 +198,7 @@ Example response:
]
```
#### GetClusterLayout `GET /v2/GetClusterLayout`
#### GetClusterLayout `GET /v0/layout`
Returns the cluster's current layout in JSON, including:
@@ -244,54 +212,42 @@ Example response body:
```json
{
"version": 12,
"roles": [
{
"id": "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f",
"roles": {
"ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f": {
"zone": "dc1",
"capacity": 10737418240,
"capacity": 4,
"tags": [
"node1"
]
},
{
"id": "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff",
"4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff": {
"zone": "dc1",
"capacity": 10737418240,
"capacity": 6,
"tags": [
"node2"
]
},
{
"id": "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27",
"23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27": {
"zone": "dc2",
"capacity": 10737418240,
"capacity": 10,
"tags": [
"node3"
]
}
],
"stagedRoleChanges": [
{
"id": "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b",
"remove": false,
},
"stagedRoleChanges": {
"e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b": {
"zone": "dc2",
"capacity": 10737418240,
"capacity": 5,
"tags": [
"node4"
]
}
{
"id": "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27",
"remove": true,
"zone": null,
"capacity": null,
"tags": null,
}
]
}
}
```
#### UpdateClusterLayout `POST /v2/UpdateClusterLayout`
#### UpdateClusterLayout `POST /v0/layout`
Send modifications to the cluster layout. These modifications will
be included in the staged role changes, visible in subsequent calls
@@ -303,9 +259,8 @@ the layout.
Request body format:
```json
[
{
"id": <node_id>,
{
<node_id>: {
"capacity": <new_capacity>,
"zone": <new_zone>,
"tags": [
@@ -313,22 +268,17 @@ Request body format:
...
]
},
{
"id": <node_id_to_remove>,
"remove": true
}
]
<node_id_to_remove>: null,
...
}
```
Contrary to the CLI that may update only a subset of the fields
`capacity`, `zone` and `tags`, when calling this API all of these
values must be specified.
This returns the new cluster layout with the proposed staged changes,
as returned by GetClusterLayout.
#### ApplyClusterLayout `POST /v2/ApplyClusterLayout`
#### ApplyClusterLayout `POST /v0/layout/apply`
Applies to the cluster the layout changes currently registered as
staged layout changes.
@@ -345,22 +295,28 @@ Similarly to the CLI, the body must include the version of the new layout
that will be created, which MUST be 1 + the value of the currently
existing layout in the cluster.
This returns the message describing all the calculations done to compute the new
layout, as well as the description of the layout as returned by GetClusterLayout.
#### RevertClusterLayout `POST /v2/RevertClusterLayout`
#### RevertClusterLayout `POST /v0/layout/revert`
Clears all of the staged layout changes.
This requests contains an empty body.
Request body format:
This returns the new cluster layout with all changes reverted,
as returned by GetClusterLayout.
```json
{
"version": 13
}
```
Reverting the staged changes is done by incrementing the version number
and clearing the contents of the staged change list.
Similarly to the CLI, the body must include the incremented
version number, which MUST be 1 + the value of the currently
existing layout in the cluster.
### Access key operations
#### ListKeys `GET /v2/ListKeys`
#### ListKeys `GET /v0/key`
Returns all API access keys in the cluster.
@@ -379,8 +335,34 @@ Example response:
]
```
#### GetKeyInfo `GET /v2/GetKeyInfo?id=<access key id>`
#### GetKeyInfo `GET /v2/GetKeyInfo?search=<pattern>`
#### CreateKey `POST /v0/key`
Creates a new API access key.
Request body format:
```json
{
"name": "NameOfMyKey"
}
```
#### ImportKey `POST /v0/key/import`
Imports an existing API key.
Request body format:
```json
{
"accessKeyId": "GK31c2f218a2e44f485b94239e",
"secretAccessKey": "b892c0665f0ada8a4755dae98baa3b133590e11dae3bcc1f9d769d67f16c3835",
"name": "NameOfMyKey"
}
```
#### GetKeyInfo `GET /v0/key?id=<acces key id>`
#### GetKeyInfo `GET /v0/key?search=<pattern>`
Returns information about the requested API access key.
@@ -388,9 +370,6 @@ If `id` is set, the key is looked up using its exact identifier (faster).
If `search` is set, the key is looked up using its name or prefix
of identifier (slower, all keys are enumerated to do this).
Optionally, the query parameter `showSecretKey=true` can be set to reveal the
associated secret access key.
Example response:
```json
@@ -454,40 +433,11 @@ Example response:
}
```
#### CreateKey `POST /v2/CreateKey`
#### DeleteKey `DELETE /v0/key?id=<acces key id>`
Creates a new API access key.
Deletes an API access key.
Request body format:
```json
{
"name": "NameOfMyKey"
}
```
This returns the key info, including the created secret key,
in the same format as the result of GetKeyInfo.
#### ImportKey `POST /v2/ImportKey`
Imports an existing API key.
This will check that the imported key is in the valid format, i.e.
is a key that could have been generated by Garage.
Request body format:
```json
{
"accessKeyId": "GK31c2f218a2e44f485b94239e",
"secretAccessKey": "b892c0665f0ada8a4755dae98baa3b133590e11dae3bcc1f9d769d67f16c3835",
"name": "NameOfMyKey"
}
```
This returns the key info in the same format as the result of GetKeyInfo.
#### UpdateKey `POST /v2/UpdateKey?id=<access key id>`
#### UpdateKey `POST /v0/key?id=<acces key id>`
Updates information about the specified API access key.
@@ -503,20 +453,14 @@ Request body format:
}
```
All fields (`name`, `allow` and `deny`) are optional.
All fields (`name`, `allow` and `deny`) are optionnal.
If they are present, the corresponding modifications are applied to the key, otherwise nothing is changed.
The possible flags in `allow` and `deny` are: `createBucket`.
This returns the key info in the same format as the result of GetKeyInfo.
#### DeleteKey `POST /v2/DeleteKey?id=<access key id>`
Deletes an API access key.
### Bucket operations
#### ListBuckets `GET /v2/ListBuckets`
#### ListBuckets `GET /v0/bucket`
Returns all storage buckets in the cluster.
@@ -558,8 +502,8 @@ Example response:
]
```
#### GetBucketInfo `GET /v2/GetBucketInfo?id=<bucket id>`
#### GetBucketInfo `GET /v2/GetBucketInfo?globalAlias=<alias>`
#### GetBucketInfo `GET /v0/bucket?id=<bucket id>`
#### GetBucketInfo `GET /v0/bucket?globalAlias=<alias>`
Returns information about the requested storage bucket.
@@ -591,10 +535,7 @@ Example response:
],
"objects": 14827,
"bytes": 13189855625,
"unfinishedUploads": 1,
"unfinishedMultipartUploads": 1,
"unfinishedMultipartUploadParts": 11,
"unfinishedMultipartUploadBytes": 41943040,
"unfinshedUploads": 0,
"quotas": {
"maxSize": null,
"maxObjects": null
@@ -602,7 +543,7 @@ Example response:
}
```
#### CreateBucket `POST /v2/CreateBucket`
#### CreateBucket `POST /v0/bucket`
Creates a new storage bucket.
@@ -642,7 +583,13 @@ or no alias at all.
Technically, you can also specify both `globalAlias` and `localAlias` and that would create
two aliases, but I don't see why you would want to do that.
#### UpdateBucket `POST /v2/UpdateBucket?id=<bucket id>`
#### DeleteBucket `DELETE /v0/bucket?id=<bucket id>`
Deletes a storage bucket. A bucket cannot be deleted if it is not empty.
Warning: this will delete all aliases associated with the bucket!
#### UpdateBucket `PUT /v0/bucket?id=<bucket id>`
Updates configuration of the given bucket.
@@ -662,7 +609,7 @@ Request body format:
}
```
All fields (`websiteAccess` and `quotas`) are optional.
All fields (`websiteAccess` and `quotas`) are optionnal.
If they are present, the corresponding modifications are applied to the bucket, otherwise nothing is changed.
In `websiteAccess`: if `enabled` is `true`, `indexDocument` must be specified.
@@ -674,38 +621,9 @@ In `quotas`: new values of `maxSize` and `maxObjects` must both be specified, or
to remove the quotas. An absent value will be considered the same as a `null`. It is not possible
to change only one of the two quotas.
#### DeleteBucket `POST /v2/DeleteBucket?id=<bucket id>`
Deletes a storage bucket. A bucket cannot be deleted if it is not empty.
Warning: this will delete all aliases associated with the bucket!
#### CleanupIncompleteUploads `POST /v2/CleanupIncompleteUploads`
Cleanup all incomplete uploads in a bucket that are older than a specified number
of seconds.
Request body format:
```json
{
"bucketId": "e6a14cd6a27f48684579ec6b381c078ab11697e6bc8513b72b2f5307e25fff9b",
"olderThanSecs": 3600
}
```
Response format
```json
{
"uploadsDeleted": 12
}
```
### Operations on permissions for keys on buckets
#### AllowBucketKey `POST /v2/AllowBucketKey`
#### BucketAllowKey `POST /v0/bucket/allow`
Allows a key to do read/write/owner operations on a bucket.
@@ -726,7 +644,7 @@ Request body format:
Flags in `permissions` which have the value `true` will be activated.
Other flags will remain unchanged.
#### DenyBucketKey `POST /v2/DenyBucketKey`
#### BucketDenyKey `POST /v0/bucket/deny`
Denies a key from doing read/write/owner operations on a bucket.
@@ -750,35 +668,19 @@ Other flags will remain unchanged.
### Operations on bucket aliases
#### AddBucketAlias `POST /v2/AddBucketAlias`
#### GlobalAliasBucket `PUT /v0/bucket/alias/global?id=<bucket id>&alias=<global alias>`
Creates an alias for a bucket in the namespace of a specific access key.
To create a global alias, specify the `globalAlias` field.
To create a local alias, specify the `localAlias` and `accessKeyId` fields.
Empty body. Creates a global alias for a bucket.
Request body format:
#### GlobalUnaliasBucket `DELETE /v0/bucket/alias/global?id=<bucket id>&alias=<global alias>`
```json
{
"bucketId": "e6a14cd6a27f48684579ec6b381c078ab11697e6bc8513b72b2f5307e25fff9b",
"globalAlias": "my-bucket"
}
```
Removes a global alias for a bucket.
or:
#### LocalAliasBucket `PUT /v0/bucket/alias/local?id=<bucket id>&accessKeyId=<access key ID>&alias=<local alias>`
```json
{
"bucketId": "e6a14cd6a27f48684579ec6b381c078ab11697e6bc8513b72b2f5307e25fff9b",
"accessKeyId": "GK31c2f218a2e44f485b94239e",
"localAlias": "my-bucket"
}
```
Empty body. Creates a local alias for a bucket in the namespace of a specific access key.
#### RemoveBucketAlias `POST /v2/RemoveBucketAlias`
#### LocalUnaliasBucket `DELETE /v0/bucket/alias/local?id=<bucket id>&accessKeyId<access key ID>&alias=<local alias>`
Removes an alias for a bucket in the namespace of a specific access key.
To remove a global alias, specify the `globalAlias` field.
To remove a local alias, specify the `localAlias` and `accessKeyId` fields.
Removes a local alias for a bucket in the namespace of a specific access key.
Request body format: same as AddBucketAlias.
+8 -8
View File
@@ -35,7 +35,7 @@ Triples in K2V are constituted of three fields:
partition key in which the client wants to read/delete lists of items
- a sort key (`sk`), an utf8 string that defines the index of the triplet inside its
partition; triplets are uniquely identified by their partition key + sort key
partition; triplets are uniquely idendified by their partition key + sort key
- a value (`v`), an opaque binary blob associated to the partition key + sort key;
they are transmitted as binary when possible but in most case in the JSON API
@@ -74,7 +74,7 @@ are obsoleted by the new write.
**Basic insertion.** To insert a new value `v4` with context `[(node1, t2), (node2, t3)]`, in a
simple case where there was no insertion in-between reading the value
mentioned above and writing `v4`, and supposing that node2 receives the
mentionned above and writing `v4`, and supposing that node2 receives the
InsertItem query:
- `node2` generates a timestamp `t4` such that `t4 > t3`.
@@ -146,7 +146,7 @@ in a bucket, as the partition key becomes the sort key in the index.
How indexing works:
- Each node keeps a local count of how many items it stores for each partition,
in a local database tree that is updated atomically when an item is modified.
in a local Sled tree that is updated atomically when an item is modified.
- These local counters are asynchronously stored in the index table which is
a regular Garage table spread in the network. Counters are stored as LWW values,
so basically the final table will have the following structure:
@@ -332,7 +332,7 @@ Inserts a single item. This request does not use JSON, the body is sent directly
To supersede previous values, the HTTP header `X-Garage-Causality-Token` should
be set to the causality token returned by a previous read on this key. This
header can be omitted for the first writes to the key.
header can be ommitted for the first writes to the key.
Example query:
@@ -397,7 +397,7 @@ smallest partition key that exists. It returns partition keys in increasing
order, or decreasing order if `reverse` is set to `true`,
and stops when either of the following conditions is met:
1. if `end` is specified, the partition key `end` is reached or surpassed (if it
1. if `end` is specfied, the partition key `end` is reached or surpassed (if it
is reached exactly, it is not included in the result)
2. if `limit` is specified, `limit` partition keys have been listed
@@ -491,7 +491,7 @@ the triplet is inserted for the first time, the causality token should be set to
The value is expected to be a base64-encoded binary blob. The value `null` can
also be used to delete the triplet while preserving causality information: this
allows to know if a delete has happened concurrently with an insert, in which
allows to know if a delete has happenned concurrently with an insert, in which
case both are preserved and returned on reads (see below).
Partition keys and sort keys are utf8 strings which are stored sorted by
@@ -540,7 +540,7 @@ JSON struct with the following fields:
For each of the searches, triplets are listed and returned separately. The
semantics of `prefix`, `start`, `end`, `limit` and `reverse` are the same as for ReadIndex. The
additional parameter `singleItem` allows to get a single item, whose sort key
additionnal parameter `singleItem` allows to get a single item, whose sort key
is the one given in `start`. Parameters `conflictsOnly` and `tombstones`
control additional filters on the items that are returned.
@@ -562,7 +562,7 @@ token>", v: ["<value1>", ...] }`, with the following fields:
- in case of concurrent update and deletion, a `null` is added to the list of concurrent values
- if the `tombstones` query parameter is set to `true`, tombstones are returned
for items that have been deleted (this can be useful for inserting after an
for items that have been deleted (this can be usefull for inserting after an
item that has been deleted, so that the insert is not considered
concurrent with the delete). Tombstones are returned as tuples in the
same format with only `null` values
-13
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@@ -1,13 +0,0 @@
optimal_layout.aux
optimal_layout.log
optimal_layout.synctex.gz
optimal_layout.bbl
optimal_layout.blg
geodistrib.aux
geodistrib.bbl
geodistrib.blg
geodistrib.log
geodistrib.out
geodistrib.synctex.gz
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\documentclass[]{article}
\usepackage{amsmath,amssymb}
\usepackage{amsthm}
\usepackage{stmaryrd}
\usepackage{graphicx,xcolor}
\usepackage{hyperref}
\usepackage{algorithm,algpseudocode,float}
\renewcommand\thesubsubsection{\Alph{subsubsection})}
\newtheorem{proposition}{Proposition}
%opening
\title{An algorithm for geo-distributed and redundant storage in Garage}
\author{Mendes Oulamara \\ \emph{mendes@deuxfleurs.fr}}
\date{}
\begin{document}
\maketitle
\begin{abstract}
Garage
\end{abstract}
\section{Introduction}
Garage\footnote{\url{https://garagehq.deuxfleurs.fr/}} is an open-source distributed object storage service tailored for self-hosting. It was designed by the Deuxfleurs association\footnote{\url{https://deuxfleurs.fr/}} to enable small structures (associations, collectives, small companies) to share storage resources to reliably self-host their data, possibly with old and non-reliable machines.
To achieve these reliability and availability goals, the data is broken into \emph{partitions} and every partition is replicated over 3 different machines (that we call \emph{nodes}). When the data is queried, a consensus algorithm allows to fetch it from one of the nodes. A \emph{replication factor} of 3 ensures the best guarantees in the consensus algorithm \cite{ADD RREF}, but this parameter can be different.
Moreover, if the nodes are spread over different \emph{zones} (different houses, offices, cities\dots), we can ask the data to be replicated over nodes belonging to different zones, to improve the storage robustness against zone failure (such as power outage). To do so, we set a \emph{redundancy parameter}, that is no more than the replication factor, and we ask that any partition is replicated over this number of zones at least.
In this work, we propose a repartition algorithm that, given the nodes specifications and the replication and redundancy parameters, computes an optimal assignation of partitions to nodes. We say that the assignation is optimal in the sense that it maximizes the size of the partitions, and hence the effective storage capacity of the system.
Moreover, when a former assignation exists, which is not optimal anymore due to nodes or zones updates, our algorithm computes a new optimal assignation that minimizes the amount of data to be transferred during the assignation update (the \emph{transfer load}).
We call the set of nodes cooperating to store the data a \emph{cluster}, and a description of the nodes, zones and the assignation of partitions to nodes a \emph{cluster layout}
\subsection{Notations}
Let $k$ be some fixed parameter value, typically 8, that we call the ``partition bits''.
Every object to be stored in the system is split into data blocks of fixed size. We compute a hash $h(\mathbf{b})$ of every such block $\mathbf{b}$, and we define the $k$ last bits of this hash to be the partition number $p(\mathbf{b})$ of the block. This label can take $P=2^k$ different values, and hence there are $P$ different partitions. We denote $\mathbf{P}$ the set of partition labels (i.e. $\mathbf{P}=\llbracket1,P\rrbracket$).
We are given a set $\mathbf{N}$ of $N$ nodes and a set $\mathbf{Z}$ of $Z$ zones. Every node $n$ has a non-negative storage capacity $c_n\ge 0$ and belongs to a zone $z_n\in \mathbf{Z}$. We are also given a replication parameter $\rho_\mathbf{N}$ and a redundancy parameter $\rho_\mathbf{Z}$ such that $1\le \rho_\mathbf{Z} \le \rho_\mathbf{N}$ (typical values would be $\rho_N=3$ and $\rho_Z=2$).
Our goal is to compute an assignment $\alpha = (\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}})_{p\in \mathbf{P}}$ such that every partition $p$ is associated to $\rho_\mathbf{N}$ distinct nodes $\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}} \in \mathbf{N}$ and these nodes belong to at least $\rho_\mathbf{Z}$ distinct zones. Among the possible assignations, we choose one that \emph{maximizes} the effective storage capacity of the cluster. If the layout contained a previous assignment $\alpha'$, we \emph{minimize} the amount of data to transfer during the layout update by making $\alpha$ as close as possible to $\alpha'$. These maximization and minimization are described more formally in the following section.
\subsection{Optimization parameters}
To link the effective storage capacity of the cluster to partition assignment, we make the following assumption:
\begin{equation}
\tag{H1}
\text{\emph{All partitions have the same size $s$.}}
\end{equation}
This assumption is justified by the dispersion of the hashing function, when the number of partitions is small relative to the number of stored blocks.
Every node $n$ will store some number $p_n$ of partitions (it is the number of partitions $p$ such that $n$ appears in the $\alpha_p$). Hence the partitions stored by $n$ (and hence all partitions by our assumption) have there size bounded by $c_n/p_n$. This remark leads us to define the optimal size that we will want to maximize:
\begin{equation}
\label{eq:optimal}
\tag{OPT}
s^* = \min_{n \in N} \frac{c_n}{p_n}.
\end{equation}
When the capacities of the nodes are updated (this includes adding or removing a node), we want to update the assignment as well. However, transferring the data between nodes has a cost and we would like to limit the number of changes in the assignment. We make the following assumption:
\begin{equation}
\tag{H2}
\text{\emph{Nodes updates happen rarely relatively to block operations.}}
\end{equation}
This assumption justifies that when we compute the new assignment $\alpha$, it is worth to optimize the partition size \eqref{eq:optimal} first, and then, among the possible optimal solution, to try to minimize the number of partition transfers. More formally, we minimize the distance between two assignments defined by
\begin{equation}
d(\alpha, \alpha') := \#\{ (n,p) \in \mathbf{N}\times\mathbf{P} ~|~ n\in \alpha_p \triangle \alpha'_p \}
\end{equation}
where the symmetric difference $\alpha_p \triangle \alpha'_p$ denotes the nodes appearing in one of the assignations but not in both.
\section{Computation of an optimal assignment}
The algorithm that we propose takes as inputs the cluster layout parameters $\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$, that we defined in the introduction, together with the former assignation $\alpha'$ (if any). The computation of the new optimal assignation $\alpha^*$ is done in three successive steps that will be detailed in the following sections. The first step computes the largest partition size $s^*$ that an assignation can achieve. The second step computes an optimal candidate assignment $\alpha$ that achieves $s^*$ and a heuristic is used in the computation to make it hopefully close to $\alpha'$. The third steps modifies $\alpha$ iteratively to reduces $d(\alpha, \alpha')$ and yields an assignation $\alpha^*$ achieving $s^*$, and minimizing $d(\cdot, \alpha')$ among such assignations.
We will explain in the next section how to represent an assignment $\alpha$ by a flow $f$ on a weighted graph $G$ to enable the use of flow and graph algorithms. The main function of the algorithm can be written as follows.
\subsubsection*{Algorithm}
\begin{algorithmic}[1]
\Function{Compute Layout}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$, $\alpha'$}
\State $s^* \leftarrow$ \Call{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$}
\State $G \leftarrow G(s^*)$
\State $f \leftarrow$ \Call{Compute Candidate Assignment}{$G$, $\alpha'$}
\State $f^* \leftarrow$ \Call{Minimize transfer load}{$G$, $f$, $\alpha'$}
\State Build $\alpha^*$ from $f^*$
\State \Return $\alpha^*$
\EndFunction
\end{algorithmic}
\subsubsection*{Complexity}
As we will see in the next sections, the worst case complexity of this algorithm is $O(P^2 N^2)$. The minimization of transfer load is the most expensive step, and it can run with a timeout since it is only an optimization step. Without this step (or with a smart timeout), the worst cas complexity can be $O((PN)^{3/2}\log C)$ where $C$ is the total storage capacity of the cluster.
\subsection{Determination of the partition size $s^*$}
We will represent an assignment $\alpha$ as a flow in a specific graph $G$. We will not compute the optimal partition size $s^*$ a priori, but we will determine it by dichotomy, as the largest size $s$ such that the maximal flow achievable on $G=G(s)$ has value $\rho_\mathbf{N}P$. We will assume that the capacities are given in a small enough unit (say, Megabytes), and we will determine $s^*$ at the precision of the given unit.
Given some candidate size value $s$, we describe the oriented weighted graph $G=(V,E)$ with vertex set $V$ arc set $E$ (see Figure \ref{fig:flowgraph}).
The set of vertices $V$ contains the source $\mathbf{s}$, the sink $\mathbf{t}$, vertices
$\mathbf{p^+, p^-}$ for every partition $p$, vertices $\mathbf{x}_{p,z}$ for every partition $p$ and zone $z$, and vertices $\mathbf{n}$ for every node $n$.
The set of arcs $E$ contains:
\begin{itemize}
\item ($\mathbf{s}$,$\mathbf{p}^+$, $\rho_\mathbf{Z}$) for every partition $p$;
\item ($\mathbf{s}$,$\mathbf{p}^-$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$;
\item ($\mathbf{p}^+$,$\mathbf{x}_{p,z}$, 1) for every partition $p$ and zone $z$;
\item ($\mathbf{p}^-$,$\mathbf{x}_{p,z}$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$ and zone $z$;
\item ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) for every partition $p$, zone $z$ and node $n\in z$;
\item ($\mathbf{n}$, $\mathbf{t}$, $\lfloor c_n/s \rfloor$) for every node $n$.
\end{itemize}
\begin{figure}
\centering
\includegraphics[width=\linewidth]{figures/flow_graph_param}
\caption{An example of graph $G(s)$. Arcs are oriented from left to right, and unlabeled arcs have capacity 1. In this example, nodes $n_1,n_2,n_3$ belong to zone $z_1$, and nodes $n_4,n_5$ belong to zone $z_2$.}
\label{fig:flowgraph}
\end{figure}
In the following complexity calculations, we will use the number of vertices and edges of $G$. Remark from now that $\# V = O(PZ)$ and $\# E = O(PN)$.
\begin{proposition}
An assignment $\alpha$ is realizable with partition size $s$ and the redundancy constraints $(\rho_\mathbf{N},\rho_\mathbf{Z})$ if and only if there exists a maximal flow function $f$ in $G$ with total flow $\rho_\mathbf{N}P$, such that the arcs ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) used are exactly those for which $p$ is associated to $n$ in $\alpha$.
\end{proposition}
\begin{proof}
Given such flow $f$, we can reconstruct a candidate $\alpha$. In $f$, the flow passing through $\mathbf{p^+}$ and $\mathbf{p^-}$ is $\rho_\mathbf{N}$, and since the outgoing capacity of every $\mathbf{x}_{p,z}$ is 1, every partition is associated to $\rho_\mathbf{N}$ distinct nodes. The fraction $\rho_\mathbf{Z}$ of the flow passing through every $\mathbf{p^+}$ must be spread over as many distinct zones as every arc outgoing from $\mathbf{p^+}$ has capacity 1. So the reconstructed $\alpha$ verifies the redundancy constraints. For every node $n$, the flow between $\mathbf{n}$ and $\mathbf{t}$ corresponds to the number of partitions associated to $n$. By construction of $f$, this does not exceed $\lfloor c_n/s \rfloor$. We assumed that the partition size is $s$, hence this association does not exceed the storage capacity of the nodes.
In the other direction, given an assignment $\alpha$, one can similarly check that the facts that $\alpha$ respects the redundancy constraints, and the storage capacities of the nodes, are necessary condition to construct a maximal flow function $f$.
\end{proof}
\textbf{Implementation remark:} In the flow algorithm, while exploring the graph, we explore the neighbours of every vertex in a random order to heuristically spread the associations between nodes and partitions.
\subsubsection*{Algorithm}
With this result mind, we can describe the first step of our algorithm. All divisions are supposed to be integer divisions.
\begin{algorithmic}[1]
\Function{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$}
\State Build the graph $G=G(s=1)$
\State $ f \leftarrow$ \Call{Maximal flow}{$G$}
\If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$}
\State \Return Error: capacities too small or constraints too strong.
\EndIf
\State $s^- \leftarrow 1$
\State $s^+ \leftarrow 1+\frac{1}{\rho_\mathbf{N}}\sum_{n \in \mathbf{N}} c_n$
\While{$s^-+1 < s^+$}
\State Build the graph $G=G(s=(s^-+s^+)/2)$
\State $ f \leftarrow$ \Call{Maximal flow}{$G$}
\If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$}
\State $s^+ \leftarrow (s^- + s^+)/2$
\Else
\State $s^- \leftarrow (s^- + s^+)/2$
\EndIf
\EndWhile
\State \Return $s^-$
\EndFunction
\end{algorithmic}
\subsubsection*{Complexity}
To compute the maximal flow, we use Dinic's algorithm. Its complexity on general graphs is $O(\#V^2 \#E)$, but on graphs with edge capacity bounded by a constant, it turns out to be $O(\#E^{3/2})$. The graph $G$ does not fall in this case since the capacities of the arcs incoming to $\mathbf{t}$ are far from bounded. However, the proof of this complexity function works readily for graphs where we only ask the edges \emph{not} incoming to the sink $\mathbf{t}$ to have their capacities bounded by a constant. One can find the proof of this claim in \cite[Section 2]{even1975network}.
The dichotomy adds a logarithmic factor $\log (C)$ where $C=\sum_{n \in \mathbf{N}} c_n$ is the total capacity of the cluster. The total complexity of this first function is hence
$O(\#E^{3/2}\log C ) = O\big((PN)^{3/2} \log C\big)$.
\subsubsection*{Metrics}
We can display the discrepancy between the computed $s^*$ and the best size we could have hoped for the given total capacity, that is $C/\rho_\mathbf{N}$.
\subsection{Computation of a candidate assignment}
Now that we have the optimal partition size $s^*$, to compute a candidate assignment it would be enough to compute a maximal flow function $f$ on $G(s^*)$. This is what we do if there is no former assignation $\alpha'$.
If there is some $\alpha'$, we add a step that will heuristically help to obtain a candidate $\alpha$ closer to $\alpha'$. We fist compute a flow function $\tilde{f}$ that uses only the partition-to-node associations appearing in $\alpha'$. Most likely, $\tilde{f}$ will not be a maximal flow of $G(s^*)$. In Dinic's algorithm, we can start from a non maximal flow function and then discover improving paths. This is what we do by starting from $\tilde{f}$. The hope\footnote{This is only a hope, because one can find examples where the construction of $f$ from $\tilde{f}$ produces an assignment $\alpha$ that is not as close as possible to $\alpha'$.} is that the final flow function $f$ will tend to keep the associations appearing in $\tilde{f}$.
More formally, we construct the graph $G_{|\alpha'}$ from $G$ by removing all the arcs $(\mathbf{x}_{p,z},\mathbf{n}, 1)$ where $p$ is not associated to $n$ in $\alpha'$. We compute a maximal flow function $\tilde{f}$ in $G_{|\alpha'}$. The flow $\tilde{f}$ is also a valid (most likely non maximal) flow function on $G$. We compute a maximal flow function $f$ on $G$ by starting Dinic's algorithm on $\tilde{f}$.
\subsubsection*{Algorithm}
\begin{algorithmic}[1]
\Function{Compute Candidate Assignment}{$G$, $\alpha'$}
\State Build the graph $G_{|\alpha'}$
\State $ \tilde{f} \leftarrow$ \Call{Maximal flow}{$G_{|\alpha'}$}
\State $ f \leftarrow$ \Call{Maximal flow from flow}{$G$, $\tilde{f}$}
\State \Return $f$
\EndFunction
\end{algorithmic}
~
\textbf{Remark:} The function ``Maximal flow'' can be just seen as the function ``Maximal flow from flow'' called with the zero flow function as starting flow.
\subsubsection*{Complexity}
With the considerations of the last section, we have the complexity of the Dinic's algorithm $O(\#E^{3/2}) = O((PN)^{3/2})$.
\subsubsection*{Metrics}
We can display the flow value of $\tilde{f}$, which is an upper bound of the distance between $\alpha$ and $\alpha'$. It might be more a Debug level display than Info.
\subsection{Minimization of the transfer load}
Now that we have a candidate flow function $f$, we want to modify it to make its corresponding assignation $\alpha$ as close as possible to $\alpha'$. Denote by $f'$ the maximal flow corresponding to $\alpha'$, and let $d(f, \alpha')=d(f, f'):=d(\alpha,\alpha')$\footnote{It is the number of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$ saturated in one flow and not in the other.}.
We want to build a sequence $f=f_0, f_1, f_2 \dots$ of maximal flows such that $d(f_i, \alpha')$ decreases as $i$ increases. The distance being a non-negative integer, this sequence of flow functions must be finite. We now explain how to find some improving $f_{i+1}$ from $f_i$.
For any maximal flow $f$ in $G$, we define the oriented weighted graph $G_f=(V, E_f)$ as follows. The vertices of $G_f$ are the same as the vertices of $G$. $E_f$ contains the arc $(v_1,v_2, w)$ between vertices $v_1,v_2\in V$ with weight $w$ if and only if the arc $(v_1,v_2)$ is not saturated in $f$ (i.e. $c(v_1,v_2)-f(v_1,v_2) \ge 1$, we also consider reversed arcs). The weight $w$ is:
\begin{itemize}
\item $-1$ if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in only one of the two flows $f,f'$;
\item $+1$ if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in either both or none of the two flows $f,f'$;
\item $0$ otherwise.
\end{itemize}
If $\gamma$ is a simple cycle of arcs in $G_f$, we define its weight $w(\gamma)$ as the sum of the weights of its arcs. We can add $+1$ to the value of $f$ on the arcs of $\gamma$, and by construction of $G_f$ and the fact that $\gamma$ is a cycle, the function that we get is still a valid flow function on $G$, it is maximal as it has the same flow value as $f$. We denote this new function $f+\gamma$.
\begin{proposition}
Given a maximal flow $f$ and a simple cycle $\gamma$ in $G_f$, we have $d(f+\gamma, f') - d(f,f') = w(\gamma)$.
\end{proposition}
\begin{proof}
Let $X$ be the set of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$. Then we can express $d(f,f')$ as
\begin{align*}
d(f,f') & = \#\{e\in X ~|~ f(e)\neq f'(e)\}
= \sum_{e\in X} 1_{f(e)\neq f'(e)} \\
& = \frac{1}{2}\big( \#X + \sum_{e\in X} 1_{f(e)\neq f'(e)} - 1_{f(e)= f'(e)} \big).
\end{align*}
We can express the cycle weight as
\begin{align*}
w(\gamma) & = \sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} + 1_{f(e)= f'(e)}.
\end{align*}
Remark that since we passed on unit of flow in $\gamma$ to construct $f+\gamma$, we have for any $e\in X$, $f(e)=f'(e)$ if and only if $(f+\gamma)(e) \neq f'(e)$.
Hence
\begin{align*}
w(\gamma) & = \frac{1}{2}(w(\gamma) + w(\gamma)) \\
&= \frac{1}{2} \Big(
\sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} + 1_{f(e)= f'(e)} \\
& \qquad +
\sum_{e\in X, e\in \gamma} 1_{(f+\gamma)(e)\neq f'(e)} + 1_{(f+\gamma)(e)= f'(e)}
\Big).
\end{align*}
Plugging this in the previous equation, we find that
$$d(f,f')+w(\gamma) = d(f+\gamma, f').$$
\end{proof}
This result suggests that given some flow $f_i$, we just need to find a negative cycle $\gamma$ in $G_{f_i}$ to construct $f_{i+1}$ as $f_i+\gamma$. The following proposition ensures that this greedy strategy reaches an optimal flow.
\begin{proposition}
For any maximal flow $f$, $G_f$ contains a negative cycle if and only if there exists a maximal flow $f^*$ in $G$ such that $d(f^*, f') < d(f, f')$.
\end{proposition}
\begin{proof}
Suppose that there is such flow $f^*$. Define the oriented multigraph $M_{f,f^*}=(V,E_M)$ with the same vertex set $V$ as in $G$, and for every $v_1,v_2 \in V$, $E_M$ contains $(f^*(v_1,v_2) - f(v_1,v_2))_+$ copies of the arc $(v_1,v_2)$. For every vertex $v$, its total degree (meaning its outer degree minus its inner degree) is equal to
\begin{align*}
\deg v & = \sum_{u\in V} (f^*(v,u) - f(v,u))_+ - \sum_{u\in V} (f^*(u,v) - f(u,v))_+ \\
& = \sum_{u\in V} f^*(v,u) - f(v,u) = \sum_{u\in V} f^*(v,u) - \sum_{u\in V} f(v,u).
\end{align*}
The last two sums are zero for any inner vertex since $f,f^*$ are flows, and they are equal on the source and sink since the two flows are both maximal and have hence the same value. Thus, $\deg v = 0$ for every vertex $v$.
This implies that the multigraph $M_{f,f^*}$ is the union of disjoint simple cycles. $f$ can be transformed into $f^*$ by pushing a mass 1 along all these cycles in any order. Since $d(f^*, f')<d(f,f')$, there must exists one of these simple cycles $\gamma$ with $d(f+\gamma, f') < d(f, f')$. Finally, since we can push a mass in $f$ along $\gamma$, it must appear in $G_f$. Hence $\gamma$ is a cycle of $G_f$ with negative weight.
\end{proof}
In the next section we describe the corresponding algorithm. Instead of discovering only one cycle, we are allowed to discover a set $\Gamma$ of disjoint negative cycles.
\subsubsection*{Algorithm}
\begin{algorithmic}[1]
\Function{Minimize transfer load}{$G$, $f$, $\alpha'$}
\State Build the graph $G_f$
\State $\Gamma \leftarrow$ \Call{Detect Negative Cycles}{$G_f$}
\While{$\Gamma \neq \emptyset$}
\ForAll{$\gamma \in \Gamma$}
\State $f \leftarrow f+\gamma$
\EndFor
\State Update $G_f$
\State $\Gamma \leftarrow$ \Call{Detect Negative Cycles}{$G_f$}
\EndWhile
\State \Return $f$
\EndFunction
\end{algorithmic}
\subsubsection*{Complexity}
The distance $d(f,f')$ is bounded by the maximal number of differences in the associated assignment. If these assignment are totally disjoint, this distance is $2\rho_N P$. At every iteration of the While loop, the distance decreases, so there is at most $O(\rho_N P) = O(P)$ iterations.
The detection of negative cycle is done with the Bellman-Ford algorithm, whose complexity should normally be $O(\#E\#V)$. In our case, it amounts to $O(P^2ZN)$. Multiplied by the complexity of the outer loop, it amounts to $O(P^3ZN)$ which is a lot when the number of partitions and nodes starts to be large. To avoid that, we adapt the Bellman-Ford algorithm.
The Bellman-Ford algorithm runs $\#V$ iterations of an outer loop, and an inner loop over $E$. The idea is to compute the shortest paths from a source vertex $v$ to all other vertices. After $k$ iterations of the outer loop, the algorithm has computed all shortest path of length at most $k$. All simple paths have length at most $\#V-1$, so if there is an update in the last iteration of the loop, it means that there is a negative cycle in the graph. The observation that will enable us to improve the complexity is the following:
\begin{proposition}
In the graph $G_f$ (and $G$), all simple paths have a length at most $4N$.
\end{proposition}
\begin{proof}
Since $f$ is a maximal flow, there is no outgoing edge from $\mathbf{s}$ in $G_f$. One can thus check than any simple path of length 4 must contain at least two node of type $\mathbf{n}$. Hence on a path, at most 4 arcs separate two successive nodes of type $\mathbf{n}$.
\end{proof}
Thus, in the absence of negative cycles, shortest paths in $G_f$ have length at most $4N$. So we can do only $4N+1$ iterations of the outer loop in the Bellman-Ford algorithm. This makes the complexity of the detection of one set of cycle to be $O(N\#E) = O(N^2 P)$.
With this improvement, the complexity of the whole algorithm is, in the worst case, $O(N^2P^2)$. However, since we detect several cycles at once and we start with a flow that might be close to the previous one, the number of iterations of the outer loop might be smaller in practice.
\subsubsection*{Metrics}
We can display the node and zone utilization ratio, by dividing the flow passing through them divided by their outgoing capacity. In particular, we can pinpoint saturated nodes and zones (i.e. used at their full potential).
We can display the distance to the previous assignment, and the number of partition transfers.
\bibliography{optimal_layout}
\bibliographystyle{ieeetr}
\end{document}
@@ -1,11 +0,0 @@
@article{even1975network,
title={Network flow and testing graph connectivity},
author={Even, Shimon and Tarjan, R Endre},
journal={SIAM journal on computing},
volume={4},
number={4},
pages={507--518},
year={1975},
publisher={SIAM}
}
Binary file not shown.
@@ -1,709 +0,0 @@
\documentclass[]{article}
\usepackage{amsmath,amssymb}
\usepackage{amsthm}
\usepackage{graphicx,xcolor}
\usepackage{algorithm,algpseudocode,float}
\renewcommand\thesubsubsection{\Alph{subsubsection})}
\newtheorem{proposition}{Proposition}
%opening
\title{Optimal partition assignment in Garage}
\author{Mendes}
\begin{document}
\maketitle
\section{Introduction}
\subsection{Context}
Garage is an open-source distributed storage service blablabla$\dots$
Every object to be stored in the system falls in a partition given by the last $k$ bits of its hash. There are $P=2^k$ partitions. Every partition will be stored on distinct nodes of the system. The goal of the assignment of partitions to nodes is to ensure (nodes and zone) redundancy and to be as efficient as possible.
\subsection{Formal description of the problem}
We are given a set of nodes $\mathbf{N}$ and a set of zones $\mathbf{Z}$. Every node $n$ has a non-negative storage capacity $c_n\ge 0$ and belongs to a zone $z\in \mathbf{Z}$. We are also given a number of partition $P>0$ (typically $P=256$).
We would like to compute an assignment of nodes to partitions. We will impose some redundancy constraints to this assignment, and under these constraints, we want our system to have the largest storage capacity possible. To link storage capacity to partition assignment, we make the following assumption:
\begin{equation}
\tag{H1}
\text{\emph{All partitions have the same size $s$.}}
\end{equation}
This assumption is justified by the dispersion of the hashing function, when the number of partitions is small relative to the number of stored large objects.
Every node $n$ will store some number $k_n$ of partitions. Hence the partitions stored by $n$ (and hence all partitions by our assumption) have there size bounded by $c_n/k_n$. This remark leads us to define the optimal size that we will want to maximize:
\begin{equation}
\label{eq:optimal}
\tag{OPT}
s^* = \min_{n \in N} \frac{c_n}{k_n}.
\end{equation}
When the capacities of the nodes are updated (this includes adding or removing a node), we want to update the assignment as well. However, transferring the data between nodes has a cost and we would like to limit the number of changes in the assignment. We make the following assumption:
\begin{equation}
\tag{H2}
\text{\emph{Updates of capacity happens rarely relatively to object storing.}}
\end{equation}
This assumption justifies that when we compute the new assignment, it is worth to optimize the partition size \eqref{eq:optimal} first, and then, among the possible optimal solution, to try to minimize the number of partition transfers.
For now, in the following, we ask the following redundancy constraint:
\textbf{Parametric node and zone redundancy:} Given two integer parameters $1\le \rho_\mathbf{Z} \le \rho_\mathbf{N}$, we ask every partition to be stored on $\rho_\mathbf{N}$ distinct nodes, and these nodes must belong to at least $\rho_\mathbf{Z}$ distinct zones.
\textbf{Mode 3-strict:} every partition needs to be assignated to three nodes belonging to three different zones.
\textbf{Mode 3:} every partition needs to be assignated to three nodes. We try to spread the three nodes over different zones as much as possible.
\textbf{Warning:} This is a working document written incrementally. The last version of the algorithm is the \textbf{parametric assignment} described in the next section.
\section{Computation of a parametric assignment}
\textbf{Attention : }We change notations in this section.
Notations : let $P$ be the number of partitions, $N$ the number of nodes, $Z$ the number of zones. Let $\mathbf{P,N,Z}$ be the label sets of, respectively, partitions, nodes and zones.
Let $s^*$ be the largest partition size achievable with the redundancy constraints. Let $(c_n)_{n\in \mathbf{N}}$ be the storage capacity of every node.
In this section, we propose a third specification of the problem. The user inputs two redundancy parameters $1\le \rho_\mathbf{Z} \le \rho_\mathbf{N}$. We compute an assignment $\alpha = (\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}})_{p\in \mathbf{P}}$ such that every partition $p$ is associated to $\rho_\mathbf{N}$ distinct nodes $\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}}$ and these nodes belong to at least $\rho_\mathbf{Z}$ distinct zones.
If the layout contained a previous assignment $\alpha'$, we try to minimize the amount of data to transfer during the layout update by making $\alpha$ as close as possible to $\alpha'$.
In the following subsections, we describe the successive steps of the algorithm we propose to compute $\alpha$.
\subsubsection*{Algorithm}
\begin{algorithmic}[1]
\Function{Compute Layout}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$, $\alpha'$}
\State $s^* \leftarrow$ \Call{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$}
\State $G \leftarrow G(s^*)$
\State $f \leftarrow$ \Call{Compute Candidate Assignment}{$G$, $\alpha'$}
\State $f^* \leftarrow$ \Call{Minimize transfer load}{$G$, $f$, $\alpha'$}
\State Build $\alpha^*$ from $f^*$
\State \Return $\alpha^*$
\EndFunction
\end{algorithmic}
\subsubsection*{Complexity}
As we will see in the next sections, the worst case complexity of this algorithm is $O(P^2 N^2)$. The minimization of transfer load is the most expensive step, and it can run with a timeout since it is only an optimization step. Without this step (or with a smart timeout), the worst cas complexity can be $O((PN)^{3/2}\log C)$ where $C$ is the total storage capacity of the cluster.
\subsection{Determination of the partition size $s^*$}
Again, we will represent an assignment $\alpha$ as a flow in a specific graph $G$. We will not compute the optimal partition size $s^*$ a priori, but we will determine it by dichotomy, as the largest size $s$ such that the maximal flow achievable on $G=G(s)$ has value $\rho_\mathbf{N}P$. We will assume that the capacities are given in a small enough unit (say, Megabytes), and we will determine $s^*$ at the precision of the given unit.
Given some candidate size value $s$, we describe the oriented weighted graph $G=(V,E)$ with vertex set $V$ arc set $E$.
The set of vertices $V$ contains the source $\mathbf{s}$, the sink $\mathbf{t}$, vertices
$\mathbf{p^+, p^-}$ for every partition $p$, vertices $\mathbf{x}_{p,z}$ for every partition $p$ and zone $z$, and vertices $\mathbf{n}$ for every node $n$.
The set of arcs $E$ contains:
\begin{itemize}
\item ($\mathbf{s}$,$\mathbf{p}^+$, $\rho_\mathbf{Z}$) for every partition $p$;
\item ($\mathbf{s}$,$\mathbf{p}^-$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$;
\item ($\mathbf{p}^+$,$\mathbf{x}_{p,z}$, 1) for every partition $p$ and zone $z$;
\item ($\mathbf{p}^-$,$\mathbf{x}_{p,z}$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$ and zone $z$;
\item ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) for every partition $p$, zone $z$ and node $n\in z$;
\item ($\mathbf{n}$, $\mathbf{t}$, $\lfloor c_n/s \rfloor$) for every node $n$.
\end{itemize}
In the following complexity calculations, we will use the number of vertices and edges of $G$. Remark from now that $\# V = O(PZ)$ and $\# E = O(PN)$.
\begin{proposition}
An assignment $\alpha$ is realizable with partition size $s$ and the redundancy constraints $(\rho_\mathbf{N},\rho_\mathbf{Z})$ if and only if there exists a maximal flow function $f$ in $G$ with total flow $\rho_\mathbf{N}P$, such that the arcs ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) used are exactly those for which $p$ is associated to $n$ in $\alpha$.
\end{proposition}
\begin{proof}
Given such flow $f$, we can reconstruct a candidate $\alpha$. In $f$, the flow passing through $\mathbf{p^+}$ and $\mathbf{p^-}$ is $\rho_\mathbf{N}$, and since the outgoing capacity of every $\mathbf{x}_{p,z}$ is 1, every partition is associated to $\rho_\mathbf{N}$ distinct nodes. The fraction $\rho_\mathbf{Z}$ of the flow passing through every $\mathbf{p^+}$ must be spread over as many distinct zones as every arc outgoing from $\mathbf{p^+}$ has capacity 1. So the reconstructed $\alpha$ verifies the redundancy constraints. For every node $n$, the flow between $\mathbf{n}$ and $\mathbf{t}$ corresponds to the number of partitions associated to $n$. By construction of $f$, this does not exceed $\lfloor c_n/s \rfloor$. We assumed that the partition size is $s$, hence this association does not exceed the storage capacity of the nodes.
In the other direction, given an assignment $\alpha$, one can similarly check that the facts that $\alpha$ respects the redundancy constraints, and the storage capacities of the nodes, are necessary condition to construct a maximal flow function $f$.
\end{proof}
\textbf{Implementation remark:} In the flow algorithm, while exploring the graph, we explore the neighbours of every vertex in a random order to heuristically spread the association between nodes and partitions.
\subsubsection*{Algorithm}
With this result mind, we can describe the first step of our algorithm. All divisions are supposed to be integer division.
\begin{algorithmic}[1]
\Function{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$}
\State Build the graph $G=G(s=1)$
\State $ f \leftarrow$ \Call{Maximal flow}{$G$}
\If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$}
\State \Return Error: capacities too small or constraints too strong.
\EndIf
\State $s^- \leftarrow 1$
\State $s^+ \leftarrow 1+\frac{1}{\rho_\mathbf{N}}\sum_{n \in \mathbf{N}} c_n$
\While{$s^-+1 < s^+$}
\State Build the graph $G=G(s=(s^-+s^+)/2)$
\State $ f \leftarrow$ \Call{Maximal flow}{$G$}
\If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$}
\State $s^+ \leftarrow (s^- + s^+)/2$
\Else
\State $s^- \leftarrow (s^- + s^+)/2$
\EndIf
\EndWhile
\State \Return $s^-$
\EndFunction
\end{algorithmic}
\subsubsection*{Complexity}
To compute the maximal flow, we use Dinic's algorithm. Its complexity on general graphs is $O(\#V^2 \#E)$, but on graphs with edge capacity bounded by a constant, it turns out to be $O(\#E^{3/2})$. The graph $G$ does not fall in this case since the capacities of the arcs incoming to $\mathbf{t}$ are far from bounded. However, the proof of this complexity works readily for graph where we only ask the edges \emph{not} incoming to the sink $\mathbf{t}$ to have their capacities bounded by a constant. One can find the proof of this claim in \cite[Section 2]{even1975network}.
The dichotomy adds a logarithmic factor $\log (C)$ where $C=\sum_{n \in \mathbf{N}} c_n$ is the total capacity of the cluster. The total complexity of this first function is hence
$O(\#E^{3/2}\log C ) = O\big((PN)^{3/2} \log C\big)$.
\subsubsection*{Metrics}
We can display the discrepancy between the computed $s^*$ and the best size we could hope for a given total capacity, that is $C/\rho_\mathbf{N}$.
\subsection{Computation of a candidate assignment}
Now that we have the optimal partition size $s^*$, to compute a candidate assignment, it would be enough to compute a maximal flow function $f$ on $G(s^*)$. This is what we do if there was no previous assignment $\alpha'$.
If there was some $\alpha'$, we add a step that will heuristically help to obtain a candidate $\alpha$ closer to $\alpha'$. to do so, we fist compute a flow function $\tilde{f}$ that uses only the partition-to-node association appearing in $\alpha'$. Most likely, $\tilde{f}$ will not be a maximal flow of $G(s^*)$. In Dinic's algorithm, we can start from a non maximal flow function and then discover improving paths. This is what we do in starting from $\tilde{f}$. The hope\footnote{This is only a hope, because one can find examples where the construction of $f$ from $\tilde{f}$ produces an assignment $\alpha$ that is not as close as possible to $\alpha'$.} is that the final flow function $f$ will tend to keep the associations appearing in $\tilde{f}$.
More formally, we construct the graph $G_{|\alpha'}$ from $G$ by removing all the arcs $(\mathbf{x}_{p,z},\mathbf{n}, 1)$ where $p$ is not associated to $n$ in $\alpha'$. We compute a maximal flow function $\tilde{f}$ in $G_{|\alpha'}$. $\tilde{f}$ is also a valid (most likely non maximal) flow function in $G$. We compute a maximal flow function $f$ on $G$ by starting Dinic's algorithm on $\tilde{f}$.
\subsubsection*{Algorithm}
\begin{algorithmic}[1]
\Function{Compute Candidate Assignment}{$G$, $\alpha'$}
\State Build the graph $G_{|\alpha'}$
\State $ \tilde{f} \leftarrow$ \Call{Maximal flow}{$G_{|\alpha'}$}
\State $ f \leftarrow$ \Call{Maximal flow from flow}{$G$, $\tilde{f}$}
\State \Return $f$
\EndFunction
\end{algorithmic}
\textbf{Remark:} The function ``Maximal flow'' can be just seen as the function ``Maximal flow from flow'' called with the zero flow function as starting flow.
\subsubsection*{Complexity}
From the consideration of the last section, we have the complexity of the Dinic's algorithm $O(\#E^{3/2}) = O((PN)^{3/2})$.
\subsubsection*{Metrics}
We can display the flow value of $\tilde{f}$, which is an upper bound of the distance between $\alpha$ and $\alpha'$. It might be more a Debug level display than Info.
\subsection{Minimization of the transfer load}
Now that we have a candidate flow function $f$, we want to modify it to make its associated assignment as close as possible to $\alpha'$. Denote by $f'$ the maximal flow associated to $\alpha'$, and let $d(f, f')$ be distance between the associated assignments\footnote{It is the number of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$ saturated in one flow and not in the other.}.
We want to build a sequence $f=f_0, f_1, f_2 \dots$ of maximal flows such that $d(f_i, \alpha')$ decreases as $i$ increases. The distance being a non-negative integer, this sequence of flow functions must be finite. We now explain how to find some improving $f_{i+1}$ from $f_i$.
For any maximal flow $f$ in $G$, we define the oriented weighted graph $G_f=(V, E_f)$ as follows. The vertices of $G_f$ are the same as the vertices of $G$. $E_f$ contains the arc $(v_1,v_2, w)$ between vertices $v_1,v_2\in V$ with weight $w$ if and only if the arc $(v_1,v_2)$ is not saturated in $f$ (i.e. $c(v_1,v_2)-f(v_1,v_2) \ge 1$, we also consider reversed arcs). The weight $w$ is:
\begin{itemize}
\item $-1$ if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in only one of the two flows $f,f'$;
\item $+1$ if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in either both or none of the two flows $f,f'$;
\item $0$ otherwise.
\end{itemize}
If $\gamma$ is a simple cycle of arcs in $G_f$, we define its weight $w(\gamma)$ as the sum of the weights of its arcs. We can add $+1$ to the value of $f$ on the arcs of $\gamma$, and by construction of $G_f$ and the fact that $\gamma$ is a cycle, the function that we get is still a valid flow function on $G$, it is maximal as it has the same flow value as $f$. We denote this new function $f+\gamma$.
\begin{proposition}
Given a maximal flow $f$ and a simple cycle $\gamma$ in $G_f$, we have $d(f+\gamma, f') - d(f,f') = w(\gamma)$.
\end{proposition}
\begin{proof}
Let $X$ be the set of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$. Then we can express $d(f,f')$ as
\begin{align*}
d(f,f') & = \#\{e\in X ~|~ f(e)\neq f'(e)\}
= \sum_{e\in X} 1_{f(e)\neq f'(e)} \\
& = \frac{1}{2}\big( \#X + \sum_{e\in X} 1_{f(e)\neq f'(e)} - 1_{f(e)= f'(e)} \big).
\end{align*}
We can express the cycle weight as
\begin{align*}
w(\gamma) & = \sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} + 1_{f(e)= f'(e)}.
\end{align*}
Remark that since we passed on unit of flow in $\gamma$ to construct $f+\gamma$, we have for any $e\in X$, $f(e)=f'(e)$ if and only if $(f+\gamma)(e) \neq f'(e)$.
Hence
\begin{align*}
w(\gamma) & = \frac{1}{2}(w(\gamma) + w(\gamma)) \\
&= \frac{1}{2} \Big(
\sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} + 1_{f(e)= f'(e)} \\
& \qquad +
\sum_{e\in X, e\in \gamma} 1_{(f+\gamma)(e)\neq f'(e)} + 1_{(f+\gamma)(e)= f'(e)}
\Big).
\end{align*}
Plugging this in the previous equation, we find that
$$d(f,f')+w(\gamma) = d(f+\gamma, f').$$
\end{proof}
This result suggests that given some flow $f_i$, we just need to find a negative cycle $\gamma$ in $G_{f_i}$ to construct $f_{i+1}$ as $f_i+\gamma$. The following proposition ensures that this greedy strategy reaches an optimal flow.
\begin{proposition}
For any maximal flow $f$, $G_f$ contains a negative cycle if and only if there exists a maximal flow $f^*$ in $G$ such that $d(f^*, f') < d(f, f')$.
\end{proposition}
\begin{proof}
Suppose that there is such flow $f^*$. Define the oriented multigraph $M_{f,f^*}=(V,E_M)$ with the same vertex set $V$ as in $G$, and for every $v_1,v_2 \in V$, $E_M$ contains $(f^*(v_1,v_2) - f(v_1,v_2))_+$ copies of the arc $(v_1,v_2)$. For every vertex $v$, its total degree (meaning its outer degree minus its inner degree) is equal to
\begin{align*}
\deg v & = \sum_{u\in V} (f^*(v,u) - f(v,u))_+ - \sum_{u\in V} (f^*(u,v) - f(u,v))_+ \\
& = \sum_{u\in V} f^*(v,u) - f(v,u) = \sum_{u\in V} f^*(v,u) - \sum_{u\in V} f(v,u).
\end{align*}
The last two sums are zero for any inner vertex since $f,f^*$ are flows, and they are equal on the source and sink since the two flows are both maximal and have hence the same value. Thus, $\deg v = 0$ for every vertex $v$.
This implies that the multigraph $M_{f,f^*}$ is the union of disjoint simple cycles. $f$ can be transformed into $f^*$ by pushing a mass 1 along all these cycles in any order. Since $d(f^*, f')<d(f,f')$, there must exists one of these simple cycles $\gamma$ with $d(f+\gamma, f') < d(f, f')$. Finally, since we can push a mass in $f$ along $\gamma$, it must appear in $G_f$. Hence $\gamma$ is a cycle of $G_f$ with negative weight.
\end{proof}
In the next section we describe the corresponding algorithm. Instead of discovering only one cycle, we are allowed to discover a set $\Gamma$ of disjoint negative cycles.
\subsubsection*{Algorithm}
\begin{algorithmic}[1]
\Function{Minimize transfer load}{$G$, $f$, $\alpha'$}
\State Build the graph $G_f$
\State $\Gamma \leftarrow$ \Call{Detect Negative Cycles}{$G_f$}
\While{$\Gamma \neq \emptyset$}
\ForAll{$\gamma \in \Gamma$}
\State $f \leftarrow f+\gamma$
\EndFor
\State Update $G_f$
\State $\Gamma \leftarrow$ \Call{Detect Negative Cycles}{$G_f$}
\EndWhile
\State \Return $f$
\EndFunction
\end{algorithmic}
\subsubsection*{Complexity}
The distance $d(f,f')$ is bounded by the maximal number of differences in the associated assignment. If these assignment are totally disjoint, this distance is $2\rho_N P$. At every iteration of the While loop, the distance decreases, so there is at most $O(\rho_N P) = O(P)$ iterations.
The detection of negative cycle is done with the Bellman-Ford algorithm, whose complexity should normally be $O(\#E\#V)$. In our case, it amounts to $O(P^2ZN)$. Multiplied by the complexity of the outer loop, it amounts to $O(P^3ZN)$ which is a lot when the number of partitions and nodes starts to be large. To avoid that, we adapt the Bellman-Ford algorithm.
The Bellman-Ford algorithm runs $\#V$ iterations of an outer loop, and an inner loop over $E$. The idea is to compute the shortest paths from a source vertex $v$ to all other vertices. After $k$ iterations of the outer loop, the algorithm has computed all shortest path of length at most $k$. All simple paths have length at most $\#V-1$, so if there is an update in the last iteration of the loop, it means that there is a negative cycle in the graph. The observation that will enable us to improve the complexity is the following:
\begin{proposition}
In the graph $G_f$ (and $G$), all simple paths have a length at most $4N$.
\end{proposition}
\begin{proof}
Since $f$ is a maximal flow, there is no outgoing edge from $\mathbf{s}$ in $G_f$. One can thus check than any simple path of length 4 must contain at least two node of type $\mathbf{n}$. Hence on a path, at most 4 arcs separate two successive nodes of type $\mathbf{n}$.
\end{proof}
Thus, in the absence of negative cycles, shortest paths in $G_f$ have length at most $4N$. So we can do only $4N+1$ iterations of the outer loop in Bellman-Ford algorithm. This makes the complexity of the detection of one set of cycle to be $O(N\#E) = O(N^2 P)$.
With this improvement, the complexity of the whole algorithm is, in the worst case, $O(N^2P^2)$. However, since we detect several cycles at once and we start with a flow that might be close to the previous one, the number of iterations of the outer loop might be smaller in practice.
\subsubsection*{Metrics}
We can display the node and zone utilization ratio, by dividing the flow passing through them divided by their outgoing capacity. In particular, we can pinpoint saturated nodes and zones (i.e. used at their full potential).
We can display the distance to the previous assignment, and the number of partition transfers.
\section{Properties of an optimal 3-strict assignment}
\subsection{Optimal assignment}
\label{sec:opt_assign}
For every zone $z\in Z$, define the zone capacity $c_z = \sum_{v, z_v=z} c_v$ and define $C = \sum_v c_v = \sum_z c_z$.
One can check that the best we could be doing to maximize $s^*$ would be to use the nodes proportionally to their capacity. This would yield $s^*=C/(3N)$. This is not possible because of (i) redundancy constraints and (ii) integer rounding but it gives and upper bound.
\subsubsection*{Optimal utilization}
We call an \emph{utilization} a collection of non-negative integers $(n_v)_{v\in V}$ such that $\sum_v n_v = 3N$ and for every zone $z$, $\sum_{v\in z} n_v \le N$. We call such utilization \emph{optimal} if it maximizes $s^*$.
We start by computing a node sub-utilization $(\hat{n}_v)_{v\in V}$ such that for every zone $z$, $\sum_{v\in z} \hat{n}_v \le N$ and we show that there is an optimal utilization respecting the constraints and such that $\hat{n}_v \le n_v$ for every node.
Assume that there is a zone $z_0$ such that $c_{z_0}/C \ge 1/3$. Then for any $v\in z_0$, we define
$$\hat{n}_v = \left\lfloor\frac{c_v}{c_{z_0}}N\right\rfloor.$$
This choice ensures for any such $v$ that
$$
\frac{c_v}{\hat{n}_v} \ge \frac{c_{z_0}}{N} \ge \frac{C}{3N}
$$
which is the universal upper bound on $s^*$. Hence any optimal utilization $(n_v)$ can be modified to another optimal utilization such that $n_v\ge \hat{n}_v$
Because $z_0$ cannot store more than $N$ partition occurrences, in any assignment, at least $2N$ partitions must be assignated to the zones $Z\setminus\{z_0\}$. Let $C_0 = C-c_{z_0}$. Suppose that there exists a zone $z_1\neq z_0$ such that $c_{z_1}/C_0 \ge 1/2$. Then, with the same argument as for $z_0$, we can define
$$\hat{n}_v = \left\lfloor\frac{c_v}{c_{z_1}}N\right\rfloor$$
for every $v\in z_1$.
Now we can assign the remaining partitions. Let $(\hat{N}, \hat{C})$ to be
\begin{itemize}
\item $(3N,C)$ if we did not find any $z_0$;
\item $(2N,C-c_{z_0})$ if there was a $z_0$ but no $z_1$;
\item $(N,C-c_{z_0}-c_{z_1})$ if there was a $z_0$ and a $z_1$.
\end{itemize}
Then at least $\hat{N}$ partitions must be spread among the remaining zones. Hence $s^*$ is upper bounded by $\hat{C}/\hat{N}$ and without loss of generality, we can define, for every node that is not in $z_0$ nor $z_1$,
$$\hat{n}_v = \left\lfloor\frac{c_v}{\hat{C}}\hat{N}\right\rfloor.$$
We constructed a sub-utilization $\hat{n}_v$. Now notice that $3N-\sum_v \hat{n}_v \le \# V$ where $\# V$ denotes the number of nodes. We can iteratively pick a node $v^*$ such that
\begin{itemize}
\item $\sum_{v\in z_{v^*}} \hat{n}_v < N$ where $z_{v^*}$ is the zone of $v^*$;
\item $v^*$ maximizes the quantity $c_v/(\hat{n}_v+1)$ among the vertices satisfying the first condition (i.e. not in a saturated zone).
\end{itemize}
We iterate these instructions until $\sum_v \hat{n}_v= 3N$, and at this stage we define $(n_v) = (\hat{n}_v)$. It is easy to prove by induction that at every step, there is an optimal utilization that is pointwise larger than $\hat{n}_v$, and in particular, that $(n_v)$ is optimal.
\subsubsection*{Existence of an optimal assignment}
As for now, the \emph{optimal utilization} that we obtained is just a vector of numbers and it is not clear that it can be realized as the utilization of some concrete assignment. Here is a way to get a concrete assignment.
Define $3N$ tokens $t_1,\ldots, t_{3N}\in V$ as follows:
\begin{itemize}
\item Enumerate the zones $z$ of $Z$ in any order;
\item enumerate the nodes $v$ of $z$ in any order;
\item repeat $n_v$ times the token $v$.
\end{itemize}
Then for $1\le i \le N$, define the triplet $T_i$ to be
$(t_i, t_{i+N}, t_{i+2N})$. Since the same nodes of a zone appear contiguously, the three nodes of a triplet must belong to three distinct zones.
However simple, this solution to go from an utilization to an assignment has the drawback of not spreading the triplets: a node will tend to be associated to the same two other nodes for many partitions. Hence, during data transfer, it will tend to use only two link, instead of spreading the bandwidth use over many other links to other nodes. To achieve this goal, we will reframe the search of an assignment as a flow problem. and in the flow algorithm, we will introduce randomness in the order of exploration. This will be sufficient to obtain a good dispersion of the triplets.
\begin{figure}
\centering
\includegraphics[width=0.9\linewidth]{figures/naive}
\caption{On the left, the creation of a concrete assignment with the naive approach of repeating tokens. On the right, the zones containing the nodes.}
\end{figure}
\subsubsection*{Assignment as a maximum flow problem}
We describe the flow problem via its graph $(X,E)$ where $X$ is a set of vertices, and $E$ are directed weighted edges between the vertices. For every zone $z$, define $n_z=\sum_{v\in z} n_v$.
The set of vertices $X$ contains the source $\mathbf{s}$ and the sink $\mathbf{t}$; a vertex $\mathbf{x}_z$ for every zone $z\in Z$, and a vertex $\mathbf{y}_i$ for every partition index $1\le i\le N$.
The set of edges $E$ contains
\begin{itemize}
\item the edge $(\mathbf{s}, \mathbf{x}_z, n_z)$ for every zone $z\in Z$;
\item the edge $(\mathbf{x}_z, \mathbf{y}_i, 1)$ for every zone $z\in Z$ and partition $1\le i\le N$;
\item the edge $(\mathbf{y}_i, \mathbf{t}, 3)$ for every partition $1\le i\le N$.
\end{itemize}
\begin{figure}[b]
\centering
\includegraphics[width=0.6\linewidth]{figures/flow}
\caption{Flow problem to compute and optimal assignment.}
\end{figure}
We first show the equivalence between this problem and and the construction of an assignment. Given some optimal assignment $(n_v)$, define the flow $f:E\to \mathbb{N}$ that saturates every edge from $\mathbf{s}$ or to $\mathbf{t}$, takes value $1$ on the edge between $\mathbf{x}_z$ and $\mathbf{y}_i$ if partition $i$ is stored in some node of the zone $z$, and $0$ otherwise. One can easily check that $f$ thus defined is indeed a flow and is maximum.
Reciprocally, by the existence of maximum flows constructed from optimal assignments, any maximum flow must saturate the edges linked to the source or the sink. It can only take value 0 or 1 on the other edge, and every partition vertex is associated to exactly three distinct zone vertices. Every zone is associated to exactly $n_z$ partitions.
A maximum flow can be constructed using, for instance, Dinic's algorithm. This algorithm works by discovering augmenting path to iteratively increase the flow. During the exploration of the graph to find augmenting path, we can shuffle the order of enumeration of the neighbours to spread the associations between zones and partitions.
Once we have such association, we can randomly distribute the $n_z$ edges picked for every zone $z$ to its nodes $v\in z$ such that every such $v$ gets $n_z$ edges. This defines an optimal assignment of partitions to nodes.
\subsection{Minimal transfer}
Assume that there was a previous assignment $(T'_i)_{1\le i\le N}$ corresponding to utilizations $(n'_v)_{v\in V}$. We would like the new computed assignment $(T_i)_{1\le i\le N}$ from some $(n_v)_{v\in V}$ to minimize the number of partitions that need to be transferred. We can imagine two different objectives corresponding to different hypotheses:
\begin{equation}
\tag{H3A}
\label{hyp:A}
\text{\emph{Transfers between different zones cost much more than inside a zone.}}
\end{equation}
\begin{equation}
\tag{H3B}
\label{hyp:B}
\text{\emph{Changing zone is not the largest cost when transferring a partition.}}
\end{equation}
In case $A$, our goal will be to minimize the number of changes of zone in the assignment of partitions to zone. More formally, we will maximize the quantity
$$
Q_Z :=
\sum_{1\le i\le N}
\#\{z\in Z ~|~ z\cap T_i \neq \emptyset, z\cap T'_i \neq \emptyset \}
.$$
In case $B$, our goal will be to minimize the number of changes of nodes in the assignment of partitions to nodes. We will maximize the quantity
$$
Q_V :=
\sum_{1\le i\le N} \#(T_i \cap T'_i).
$$
It is tempting to hope that there is a way to maximize both quantity, that having the least discrepancy in terms of nodes will lead to the least discrepancy in terms of zones. But this is actually wrong! We propose the following counter-example to convince the reader:
We consider eight nodes $a, a', b, c, d, d', e, e'$ belonging to five different zones $\{a,a'\}, \{b\}, \{c\}, \{d,d'\}, \{e, e'\}$. We take three partitions ($N=3$), that are originally assigned with some utilization $(n'_v)_{v\in V}$ as follows:
$$
T'_1=(a,b,c) \qquad
T'_2=(a',b,d) \qquad
T'_3=(b,c,e).
$$
This assignment, with updated utilizations $(n_v)_{v\in V}$ minimizes the number of zone changes:
$$
T_1=(d,b,c) \qquad
T_2=(a,b,d) \qquad
T_3=(b,c,e').
$$
This one, with the same utilization, minimizes the number of node changes:
$$
T_1=(a,b,c) \qquad
T_2=(e',b,d) \qquad
T_3=(b,c,d').
$$
One can check that in this case, it is impossible to minimize both the number of zone and node changes.
Because of the redundancy constraint, we cannot use a greedy algorithm to just replace nodes in the triplets to try to get the new utilization rate: this could lead to blocking situation where there is still a hole to fill in a triplet but no available node satisfies the zone separation constraint. To circumvent this issue, we propose an algorithm based on finding cycles in a graph encoding of the assignment. As in section \ref{sec:opt_assign}, we can explore the neighbours in a random order in the graph algorithms, to spread the triplets distribution.
\subsubsection{Minimizing the zone discrepancy}
First, notice that, given an assignment of partitions to \emph{zones}, it is easy to deduce an assignment to \emph{nodes} that minimizes the number of transfers for this zone assignment: For every zone $z$ and every node $v\in z$, pick in any way a set $P_v$ of partitions that where assigned to $v$ in $T'$, to $z_v$ in $T$, with the cardinality of $P_v$ smaller than $n_v$. Once all these sets are chosen, complement the assignment to reach the right utilization for every node. If $\#P_v > n_v$, it means that all the partitions that could stay in $v$ (i.e. that were already in $v$ and are still assigned to its zone) do stay in $v$. If $\#P_v = n_v$, then $n_v$ partitions stay in $v$, which is the number of partitions that need to be in $v$ in the end. In both cases, we could not hope for better given the partition to zone assignment.
Our goal now is to find a assignment of partitions to zones that minimizes the number of zone transfers. To do so we are going to represent an assignment as a graph.
Let $G_T=(X,E_T)$ be the directed weighted graph with vertices $(\mathbf{x}_i)_{1\le i\le N}$ and $(\mathbf{y}_z)_{z\in Z}$. For any $1\le i\le N$ and $z\in Z$, $E_T$ contains the arc:
\begin{itemize}
\item $(\mathbf{x}_i, \mathbf{y}_z, +1)$, if $z$ appears in $T_i'$ and $T_i$;
\item $(\mathbf{x}_i, \mathbf{y}_z, -1)$, if $z$ appears in $T_i$ but not in $T'_i$;
\item $(\mathbf{y}_z, \mathbf{x}_i, -1)$, if $z$ appears in $T'_i$ but not in $T_i$;
\item $(\mathbf{y}_z, \mathbf{x}_i, +1)$, if $z$ does not appear in $T'_i$ nor in $T_i$.
\end{itemize}
In other words, the orientation of the arc encodes whether partition $i$ is stored in zone $z$ in the assignment $T$ and the weight $\pm 1$ encodes whether this corresponds to what happens in the assignment $T'$.
\begin{figure}[t]
\centering
\begin{minipage}{.40\linewidth}
\centering
\includegraphics[width=.8\linewidth]{figures/mini_zone}
\end{minipage}
\begin{minipage}{.55\linewidth}
\centering
\includegraphics[width=.8\linewidth]{figures/mini_node}
\end{minipage}
\caption{On the left: the graph $G_T$ encoding an assignment to minimize the zone discrepancy. On the right: the graph $G_T$ encoding an assignment to minimize the node discrepancy.}
\end{figure}
Notice that at every partition, there are three outgoing arcs, and at every zone, there are $n_z$ incoming arcs. Moreover, if $w(e)$ is the weight of an arc $e$, define the weight of $G_T$ by
\begin{align*}
w(G_T) := \sum_{e\in E} w(e) &= \#Z \times N - 4 \sum_{1\le i\le N} \#\{z\in Z ~|~ z\cap T_i = \emptyset, z\cap T'_i \neq \emptyset\} \\
&=\#Z \times N - 4 \sum_{1\le i\le N} 3- \#\{z\in Z ~|~ z\cap T_i \neq \emptyset, z\cap T'_i \neq \emptyset\} \\
&= (\#Z-12)N + 4 Q_Z.
\end{align*}
Hence maximizing $Q_Z$ is equivalent to maximizing $w(G_T)$.
Assume that their exist some assignment $T^*$ with the same utilization $(n_v)_{v\in V}$. Define $G_{T^*}$ similarly and consider the set $E_\mathrm{Diff} = E_T \setminus E_{T^*}$ of arcs that appear only in $G_T$. Since all vertices have the same number of incoming arcs in $G_T$ and $G_{T^*}$, the vertices of the graph $(X, E_\mathrm{Diff})$ must all have the same number number of incoming and outgoing arrows. So $E_\mathrm{Diff}$ can be expressed as a union of disjoint cycles. Moreover, the edges of $E_\mathrm{Diff}$ must appear in $E_{T^*}$ with reversed orientation and opposite weight. Hence, we have
$$
w(G_T) - w(G_{T^*}) = 2 \sum_{e\in E_\mathrm{Diff}} w(e).
$$
Hence, if $T$ is not optimal, there exists some $T^*$ with $w(G_T) < w(G_{T^*})$, and by the considerations above, there must exist a cycle in $E_\mathrm{Diff}$, and hence in $G_T$, with negative weight. If we reverse the edges and weights along this cycle, we obtain some graph. Since we did not change the incoming degree of any vertex, this is the graph encoding of some valid assignment $T^+$ such that $w(G_{T^+}) > w(G_T)$. We can iterate this operation until there is no other assignment $T^*$ with larger weight, that is until we obtain an optimal assignment.
\subsubsection{Minimizing the node discrepancy}
We will follow an approach similar to the one where we minimize the zone discrepancy. Here we will directly obtain a node assignment from a graph encoding.
Let $G_T=(X,E_T)$ be the directed weighted graph with vertices $(\mathbf{x}_i)_{1\le i\le N}$, $(\mathbf{y}_{z,i})_{z\in Z, 1\le i\le N}$ and $(\mathbf{u}_v)_{v\in V}$. For any $1\le i\le N$ and $z\in Z$, $E_T$ contains the arc:
\begin{itemize}
\item $(\mathbf{x}_i, \mathbf{y}_{z,i}, 0)$, if $z$ appears in $T_i$;
\item $(\mathbf{y}_{z,i}, \mathbf{x}_i, 0)$, if $z$ does not appear in $T_i$.
\end{itemize}
For any $1\le i\le N$ and $v\in V$, $E_T$ contains the arc:
\begin{itemize}
\item $(\mathbf{y}_{z_v,i}, \mathbf{u}_v, +1)$, if $v$ appears in $T_i'$ and $T_i$;
\item $(\mathbf{y}_{z_v,i}, \mathbf{u}_v, -1)$, if $v$ appears in $T_i$ but not in $T'_i$;
\item $(\mathbf{u}_v, \mathbf{y}_{z_v,i}, -1)$, if $v$ appears in $T'_i$ but not in $T_i$;
\item $(\mathbf{u}_v, \mathbf{y}_{z_v,i}, +1)$, if $v$ does not appear in $T'_i$ nor in $T_i$.
\end{itemize}
Every vertex $\mathbb{x}_i$ has outgoing degree 3, every vertex $\mathbf{y}_{z,v}$ has outgoing degree 1, and every vertex $\mathbf{u}_v$ has incoming degree $n_v$.
Remark that any graph respecting these degree constraints is the encoding of a valid assignment with utilizations $(n_v)_{v\in V}$, in particular no partition is stored in two nodes of the same zone.
We define $w(G_T)$ similarly:
\begin{align*}
w(G_T) := \sum_{e\in E_T} w(e) &= \#V \times N - 4\sum_{1\le i\le N} 3-\#(T_i\cap T'_i) \\
&= (\#V-12)N + 4Q_V.
\end{align*}
Exactly like in the previous section, the existence of an assignment with larger weight implies the existence of a negatively weighted cycle in $G_T$. Reversing this cycle gives us the encoding of a valid assignment with a larger weight. Iterating this operation yields an optimal assignment.
\subsubsection{Linear combination of both criteria}
In the graph $G_T$ defined in the previous section, instead of having weights $0$ and $\pm 1$, we could be having weights $\pm\alpha$ between $\mathbf{x}$ and $\mathbf{y}$ vertices, and weights $\pm\beta$ between $\mathbf{y}$ and $\mathbf{u}$ vertices, for some $\alpha,\beta>0$ (we have positive weight if the assignment corresponds to $T'$ and negative otherwise). Then
\begin{align*}
w(G_T) &= \sum_{e\in E_T} w(e) =
\alpha \big( (\#Z-12)N + 4 Q_Z\big) +
\beta \big( (\#V-12)N + 4 Q_V\big) \\
&= \mathrm{const}+ 4(\alpha Q_Z + \beta Q_V).
\end{align*}
So maximizing the weight of such graph encoding would be equivalent to maximizing a linear combination of $Q_Z$ and $Q_V$.
\subsection{Algorithm}
We give a high level description of the algorithm to compute an optimal 3-strict assignment. The operations appearing at lines 1,2,4 are respectively described by Algorithms \ref{alg:util},\ref{alg:opt} and \ref{alg:mini}.
\begin{algorithm}[H]
\caption{Optimal 3-strict assignment}
\label{alg:total}
\begin{algorithmic}[1]
\Function{Optimal 3-strict assignment}{$N$, $(c_v)_{v\in V}$, $T'$}
\State $(n_v)_{v\in V} \leftarrow$ \Call{Compute optimal utilization}{$N$, $(c_v)_{v\in V}$}
\State $(T_i)_{1\le i\le N} \leftarrow$ \Call{Compute candidate assignment}{$N$, $(n_v)_{v\in V}$}
\If {there was a previous assignment $T'$}
\State $T \leftarrow$ \Call{Minimization of transfers}{$(T_i)_{1\le i\le N}$, $(T'_i)_{1\le i\le N}$}
\EndIf
\State \Return $T$.
\EndFunction
\end{algorithmic}
\end{algorithm}
We give some considerations of worst case complexity for these algorithms. In the following, we assume $N>\#V>\#Z$. The complexity of Algorithm \ref{alg:total} is $O(N^3\# Z)$ if we assume \eqref{hyp:A} and $O(N^3 \#Z \#V)$ if we assume \eqref{hyp:B}.
Algorithm \ref{alg:util} can be implemented with complexity $O(\#V^2)$. The complexity of the function call at line \ref{lin:subutil} is $O(\#V)$. The difference between the sum of the subutilizations and $3N$ is at most the sum of the rounding errors when computing the $\hat{n}_v$. Hence it is bounded by $\#V$ and the loop at line \ref{lin:loopsub} is iterated at most $\#V$ times. Finding the minimizing $v$ at line \ref{lin:findmin} takes $O(\#V)$ operations (naively, we could also use a heap).
Algorithm \ref{alg:opt} can be implemented with complexity $O(N^3\times \#Z)$. The flow graph has $O(N+\#Z)$ vertices and $O(N\times \#Z)$ edges. Dinic's algorithm has complexity $O(\#\mathrm{Vertices}^2\#\mathrm{Edges})$ hence in our case it is $O(N^3\times \#Z)$.
Algorithm \ref{alg:mini} can be implemented with complexity $O(N^3\# Z)$ under \eqref{hyp:A} and $O(N^3 \#Z \#V)$ under \eqref{hyp:B}.
The graph $G_T$ has $O(N)$ vertices and $O(N\times \#Z)$ edges under assumption \eqref{hyp:A} and respectively $O(N\times \#Z)$ vertices and $O(N\times \#V)$ edges under assumption \eqref{hyp:B}. The loop at line \ref{lin:repeat} is iterated at most $N$ times since the distance between $T$ and $T'$ decreases at every iteration. Bellman-Ford algorithm has complexity $O(\#\mathrm{Vertices}\#\mathrm{Edges})$, which in our case amounts to $O(N^2\# Z)$ under \eqref{hyp:A} and $O(N^2 \#Z \#V)$ under \eqref{hyp:B}.
\begin{algorithm}
\caption{Computation of the optimal utilization}
\label{alg:util}
\begin{algorithmic}[1]
\Function{Compute optimal utilization}{$N$, $(c_v)_{v\in V}$}
\State $(\hat{n}_v)_{v\in V} \leftarrow $ \Call{Compute subutilization}{$N$, $(c_v)_{v\in V}$} \label{lin:subutil}
\While{$\sum_{v\in V} \hat{n}_v < 3N$} \label{lin:loopsub}
\State Pick $v\in V$ minimizing $\frac{c_v}{\hat{n}_v+1}$ and such that
$\sum_{v'\in z_v} \hat{n}_{v'} < N$ \label{lin:findmin}
\State $\hat{n}_v \leftarrow \hat{n}_v+1$
\EndWhile
\State \Return $(\hat{n}_v)_{v\in V}$
\EndFunction
\State
\Function{Compute subutilization}{$N$, $(c_v)_{v\in V}$}
\State $R \leftarrow 3$
\For{$v\in V$}
\State $\hat{n}_v \leftarrow \mathrm{unset}$
\EndFor
\For{$z\in Z$}
\State $c_z \leftarrow \sum_{v\in z} c_v$
\EndFor
\State $C \leftarrow \sum_{z\in Z} c_z$
\While{$\exists z \in Z$ such that $R\times c_{z} > C$}
\For{$v\in z$}
\State $\hat{n}_v \leftarrow \left\lfloor \frac{c_v}{c_z} N \right\rfloor$
\EndFor
\State $C \leftarrow C-c_z$
\State $R\leftarrow R-1$
\EndWhile
\For{$v\in V$}
\If{$\hat{n}_v = \mathrm{unset}$}
\State $\hat{n}_v \leftarrow \left\lfloor \frac{Rc_v}{C} N \right\rfloor$
\EndIf
\EndFor
\State \Return $(\hat{n}_v)_{v\in V}$
\EndFunction
\end{algorithmic}
\end{algorithm}
\begin{algorithm}
\caption{Computation of a candidate assignment}
\label{alg:opt}
\begin{algorithmic}[1]
\Function{Compute candidate assignment}{$N$, $(n_v)_{v\in V}$}
\State Compute the flow graph $G$
\State Compute the maximal flow $f$ using Dinic's algorithm with randomized neighbours enumeration
\State Construct the assignment $(T_i)_{1\le i\le N}$ from $f$
\State \Return $(T_i)_{1\le i\le N}$
\EndFunction
\end{algorithmic}
\end{algorithm}
\begin{algorithm}
\caption{Minimization of the number of transfers}
\label{alg:mini}
\begin{algorithmic}[1]
\Function{Minimization of transfers}{$(T_i)_{1\le i\le N}$, $(T'_i)_{1\le i\le N}$}
\State Construct the graph encoding $G_T$
\Repeat \label{lin:repeat}
\State Find a negative cycle $\gamma$ using Bellman-Ford algorithm on $G_T$
\State Reverse the orientations and weights of edges in $\gamma$
\Until{no negative cycle is found}
\State Update $(T_i)_{1\le i\le N}$ from $G_T$
\State \Return $(T_i)_{1\le i\le N}$
\EndFunction
\end{algorithmic}
\end{algorithm}
\newpage
\section{Computation of a 3-non-strict assignment}
\subsection{Choices of optimality}
In this mode, we primarily want to store every partition on three nodes, and only secondarily try to spread the nodes among different zone. So we make the choice of not taking the zone repartition in the criterion of optimality.
We try to maximize $s^*$ defined in \eqref{eq:optimal}. So we can compute the optimal utilizations $(n_v)_{v\in V}$ with the only constraint that $n_v \le N$ for every node $v$. As in the previous section, we start with a sub-utilization proportional to $c_v$ (and capped at $N$), and we iteratively increase the $\hat{n}_v$ that is less than $N$ and maximizes the quantity $c_v/(\hat{n}_v+1)$, until the total sum is $3N$.
\subsection{Computation of a candidate assignment}
To compute a candidate assignment (that does not optimize zone spreading nor distance to a previous assignment yet), we can use the following flow problem.
Define the oriented weighted graph $(X,E)$. The set of vertices $X$ contains the source $\mathbf{s}$, the sink $\mathbf{t}$, vertices
$\mathbf{x}_p, \mathbf{u}^+_p, \mathbf{u}^-_p$ for every partition $p$, vertices $\mathbf{y}_{p,z}$ for every partition $p$ and zone $z$, and vertices $\mathbf{z}_v$ for every node $v$.
The set of edges is composed of the following arcs:
\begin{itemize}
\item ($\mathbf{s}$,$\mathbf{x}_p$, 3) for every partition $p$;
\item ($\mathbf{x}_p$,$\mathbf{u}^+_p$, 3) for every partition $p$;
\item ($\mathbf{x}_p$,$\mathbf{u}^-_p$, 2) for every partition $p$;
\item ($\mathbf{u}^+_p$,$\mathbf{y}_{p,z}$, 1) for every partition $p$ and zone $z$;
\item ($\mathbf{u}^-_p$,$\mathbf{y}_{p,z}$, 2) for every partition $p$ and zone $z$;
\item ($\mathbf{y}_{p,z}$,$\mathbf{z}_v$, 1) for every partition $p$, zone $z$ and node $v\in z$;
\item ($\mathbf{z}_v$, $\mathbf{t}$, $n_v$) for every node $v$;
\end{itemize}
One can check that any maximal flow in this graph corresponds to an assignment of partitions to nodes. In such a flow, all the arcs from $\mathbf{s}$ and to $\mathbf{t}$ are saturated. The arc from $\mathbf{y}_{p,z}$ to $\mathbf{z}_v$ is saturated if and only if $p$ is associated to~$v$.
Finally the flow from $\mathbf{x}_p$ to $\mathbf{y}_{p,z}$ can go either through $\mathbf{u}^+_p$ or $\mathbf{u}^-_p$.
\subsection{Maximal spread and minimal transfers}
Notice that if the arc $\mathbf{u}_p^+\mathbf{y}_{p,z}$ is not saturated but there is some flow in $\mathbf{u}_p^-\mathbf{y}_{p,z}$, then it is possible to transfer a unit of flow from the path $\mathbf{x}_p\mathbf{u}_p^-\mathbf{y}_{p,z}$ to the path $\mathbf{x}_p\mathbf{u}_p^+\mathbf{y}_{p,z}$. So we can always find an equivalent maximal flow $f^*$ that uses the path through $\mathbf{u}_p^-$ only if the path through $\mathbf{u}_p^+$ is saturated.
We will use this fact to consider the amount of flow going through the vertices $\mathbf{u}^+$ as a measure of how well the partitions are spread over nodes belonging to different zones. If the partition $p$ is associated to 3 different zones, then a flow of 3 will cross $\mathbf{u}_p^+$ in $f^*$ (i.e. a flow of 0 will cross $\mathbf{u}_p^+$). If $p$ is associated to two zones, a flow of $2$ will cross $\mathbf{u}_p^+$. If $p$ is associated to a single zone, a flow of $1$ will cross $\mathbf{u}_p^+$.
Let $N_1, N_2, N_3$ be the number of partitions associated to respectively 1,2 and 3 distinct zones. We will optimize a linear combination of these variables using the discovery of positively weighted circuits in a graph.
At the same step, we will also optimize the distance to a previous assignment $T'$. Let $\alpha> \beta> \gamma \ge 0$ be three parameters.
Given the flow $f$, let $G_f=(X',E_f)$ be the multi-graph where $X' = X\setminus\{\mathbf{s},\mathbf{t}\}$. The set $E_f$ is composed of the arcs:
\begin{itemize}
\item As many arcs from $(\mathbf{x}_p, \mathbf{u}^+_p,\alpha), (\mathbf{x}_p, \mathbf{u}^+_p,\beta), (\mathbf{x}_p, \mathbf{u}^+_p,\gamma)$ (selected in this order) as there is flow crossing $\mathbf{u}^+_p$ in $f$;
\item As many arcs from $(\mathbf{u}^+_p, \mathbf{x}_p,-\gamma), (\mathbf{u}^+_p, \mathbf{x}_p,-\beta), (\mathbf{u}^+_p, \mathbf{x}_p,-\alpha)$ (selected in this order) as there is flow crossing $\mathbf{u}^-_p$ in $f$;
\item As many copies of $(\mathbf{x}_p, \mathbf{u}^-_p,0)$ as there is flow through $\mathbf{u}^-_p$;
\item As many copies of $(\mathbf{u}^-_p,\mathbf{x}_p,0)$ so that the number of arcs between these two vertices is 2;
\item $(\mathbf{u}^+_p,\mathbf{y}_{p,z}, 0)$ if the flow between these vertices is 1, and the opposite arc otherwise;
\item as many copies of $(\mathbf{u}^-_p,\mathbf{y}_{p,z}, 0)$ as the flow between these vertices, and as many copies of the opposite arc as 2~$-$~the flow;
\item $(\mathbf{y}_{p,z},\mathbf{z}_v, \pm1)$ if it is saturated in $f$, with $+1$ if $v\in T'_p$ and $-1$ otherwise;
\item $(\mathbf{z}_v,\mathbf{y}_{p,z}, \pm1)$ if it is not saturated in $f$, with $+1$ if $v\notin T'_p$ and $-1$ otherwise.
\end{itemize}
To summarize, arcs are oriented left to right if they correspond to a presence of flow in $f$, and right to left if they correspond to an absence of flow. They are positively weighted if we want them to stay at their current state, and negatively if we want them to switch. Let us compute the weight of such graph.
\begin{multiline*}
w(G_f) = \sum_{e\in E_f} w(e_f) \\
=
(\alpha - \beta -\gamma) N_1 + (\alpha +\beta - \gamma) N_2 + (\alpha+\beta+\gamma) N_3
\\ +
\#V\times N - 4 \sum_p 3-\#(T_p\cap T'_p) \\
=(\#V-12+\alpha-\beta-\gamma)\times N + 4Q_V + 2\beta N_2 + 2(\beta+\gamma) N_3 \\
\end{multiline*}
As for the mode 3-strict, one can check that the difference of two such graphs corresponding to the same $(n_v)$ is always eulerian. Hence we can navigate in this class with the same greedy algorithm that discovers positive cycles and flips them.
The function that we optimize is
$$
2Q_V + \beta N_2 + (\beta+\gamma) N_3.
$$
The choice of parameters $\beta$ and $\gamma$ should be lead by the following question: For $\beta$, where to put the tradeoff between zone dispersion and distance to the previous configuration? For $\gamma$, do we prefer to have more partitions spread between 2 zones, or have less between at least 2 zones but more between 3 zones.
The quantity $Q_V$ varies between $0$ and $3N$, it should be of order $N$. The quantity $N_2+N_3$ should also be of order $N$ (it is exactly $N$ in the strict mode). So the two terms of the function are comparable.
\bibliography{optimal_layout}
\bibliographystyle{ieeetr}
\end{document}
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