Josh Siviour
cae76ba1b6
* test(volume): assert chunk GC stays wired on in CreateVolume GCEnabled was zero-valued at every viperblock construction site for a long time and no test noticed. It is not part of viperblock.VBState, so it never round-trips through a saved config.json and cannot be observed by reading volume state back. Extract the viperblock.VB assembly out of CreateVolume into buildVBConfig so the GC wiring is assertable directly against the returned config, without a live viperblock or S3 backend. The config is returned by pointer because viperblock.VB carries atomic.Uint64 fields that vet's copylocks check rightly refuses to see copied. * test(e2e): snapshot backend byte accounting before volume purge DeleteVolume purges a volume's entire backend prefix, including any chunks a leak left behind, before anything measures it. That is the same masking that hid the storage-growth leak in production: a passing E2E cannot fail on backend growth when the evidence is deleted first. Snapshot the volume's backend chunk footprint in EnsureVolume's cleanup closure, immediately before DeleteVolume, so every volume the shared teardown path purges is measured rather than silently discarded. The snapshot is always taken and logged; the hard ratio check additionally runs for callers that registered a guest-written-bytes baseline, since most callers never attach or write to the volume they create and so have no baseline to compare against. The tolerance is the RS(2,1) erasure floor widened for per-chunk header and tail-chunk overhead. It is sized to distinguish unbounded growth from a footprint settling at the floor, not to catch bounded residual garbage. The check is non-fatal inside the cleanup callback: t.Fatalf's runtime.Goexit would abort the DeleteVolume call queued behind it and turn a reported leak into a real one. * test(e2e): add memory-constrained concurrent-write durability regression The existing durability tests write one 4MiB sentinel, sequentially, on a comfortably sized guest, which is the exact inverse of the known-open data-loss bug: acked writes read back zero-filled after a cold reread when a guest is memory-starved during concurrent writeback. No happy-path test can reach it, because the fault lives in the intersection of memory pressure, write concurrency and cache-cold reread. Add a suite that encodes those three conditions together: a guest discovered at or below the working set, N parallel large writers launched as background jobs in a single command so they genuinely overlap, swap disabled, then sync and drop_caches before rereading. Assertions are per stream rather than aggregate so a failure names the losing writer instead of leaving whoever reads it to re-derive which of N writers lost data from one combined digest. GuestExec gains a timeout-parameterised variant. Its fixed two-minute default is sized for sub-second payloads, and a multi-gigabyte write to a network-backed volume would exceed it, so the suite would have failed by timeout while looking like it had caught the corruption. The budget scales with the working set, and a deadline is reported distinctly from a data mismatch so the two red states are never confused. The suite is dispatchable but deliberately absent from the default SUITES: the bug it reproduces is still open, so it is expected to fail and must not sit in a merge-gating path. It is registered in the workflow allow-list so it stays discoverable rather than being buried behind a skip. Also record on the live IAM instance-profile test why its assertions were not moved down to the integration tier, so the trace is not repeated. * test(e2e): drop backend byte accounting, assert a node-wide delta instead The accounting helper listed the internal predastore bucket to attribute bytes per volume. That listing is refused unconditionally: predastore authorises bucket access by same-account ownership, and the bucket belongs to the service account, so a test caller gets 403 no matter what it holds. Granting the test a service credential would invert the trust boundary to buy a measurement, which is the wrong trade. Replace it with what the S3 surface actually permits: sample node-wide allocated bytes either side of the write and bound the delta against the bytes the guest wrote. Coarser, but it measures something real rather than depending on a call that cannot succeed. The tolerance moves into the suite that uses it. It encodes RS(2,1)'s 1.5x expansion floor plus headroom; a cluster running the recommended RS(3,2) has a 1.667x floor and only ~12% of margin left, so the constant needs revisiting if the encoding changes. * revert: drop memdurability e2e suite The suite asserted the guest read back what it wrote after a memory-constrained concurrent write, but the assertion could not fail for the reason it claimed: it compared the guest's own read against the guest's own write with the page cache still warm, so it passed whether or not the data reached the backend. A test that is green on a build with a known-open durability bug is worse than no test — it advertises coverage that does not exist. Removes the suite and its Makefile/workflow wiring, plus DiscoverInstanceTypeAtLeastMemory, which had no other caller. GuestExecTimeout stays: GuestExec now delegates to it, and the old two-minute hard cap it replaced was a latent trap for any long guest command. * test(e2e): add partial-block concurrent-write durability suite Replaces the removed memdurability suite, which passed on a build that still carried the bug it claimed to test. The engine reaches its read-modify-write path only for a partial block; a fully covered block takes a full-overwrite branch that reads nothing and can lose nothing. The old workload wrote through ext4 with 1 MiB buffers, which the filesystem coalesced into aligned full-block requests: block-layer tracing recorded zero unaligned and zero sub-4096 requests, so the path under test never ran, and writers 4 MiB apart could not collide on a block even in principle. This suite writes the shape the defect needs. Two writers issue concurrent O_DIRECT writes into disjoint halves of the same 4096-byte blocks on a raw, unformatted device, stamping every half with the round number, then drop the page cache and reread with O_DIRECT asserting every half carries the final round. One half reading back at an earlier round is the signature of the lost update. The old suite also could not fail even had it reached the path: its write phase ended in 'wait; sync; sha256sum' and reported sha256sum's exit status, while bare wait returns 0 unconditionally, so writer errors were invisible and a backend ENOSPC presented as a pass. Here each writer's exit status and exact byte count are asserted before any durability claim is made. Working set is 8 MiB rather than 2048 MiB, and the volume is deleted on teardown; the predecessor left roughly 3 GiB of backend per run and twice drove a node under the nearfull watermark. Dispatchable but not in the default suite list until a green run and a demonstrated fail-first against a pre-fix engine exist. * test(e2e): let the fixture own the working-set volume delete The suite deleted the volume in its own cleanup and the fixture deleted it again on close, so every run ended with an InvalidVolume.NotFound from the second attempt. Detach stays — DeleteVolume against a still attached volume is what leaks volumes on teardown — and the delete is left to the fixture so the volume is released exactly once. * test(e2e): gate merges on the partial-block durability suite Verified on one node with the same test binary and workload, varying only the engine: 1758 of 8192 halves reverted a generation against the pre-fix build, 0 of 8192 against the fixed one. That is the fail-first evidence the suite needed before it could be trusted to gate anything. Adding it to the default suite list rather than leaving it dispatchable is the point. Its predecessor sat outside every path that runs, which is how it survived long enough to be discovered green on a build that still lost data. * test(integration): cover the ECR data plane in the front gate The live ecr/ suite drove docker, crane and skopeo against a real registry, yet none of it boots a guest: it needs a registry, an object store and an HTTP client. The in-process gateway already serves the OCI Distribution v2 surface on an ephemeral port with a memory-backed object store, so these run here in 0.18s instead of behind full provisioning. Covers the three claims the live tests made beyond authorization, which is already down here: a push/pull round trip asserting blobs and manifests read back byte-identical, refusal to auto-create a repository on push, and retagging an existing manifest without disturbing the original tag. Content is compared rather than status codes alone. A registry that stores a blob under the wrong digest, truncates it, or serves a different one answers 200 to every request in the sequence. The capacity/load leg deliberately stays live: it exists to put real parallel pressure on a real predastore, and a memory-backed object store cannot make that claim. * fix(e2e): make volume teardown release the volume before deleting it Fixture cleanups drain LIFO, so a suite that creates its instance before its volume tears the volume down first, while it is still attached. DeleteVolume answered VolumeInUse, nothing retried, and the volume was stranded on the node. Reordering the chain cannot fix this — registration order has no way to express the instance/volume dependency. Instead teardown is now self-sufficient for any creation order: it force-detaches, waits for the volume to reach available, and only then deletes. Instance teardown waits for terminated for the same reason, since TerminateInstances returns as soon as the request is accepted. Two things kept the leak invisible. A failing cleanup was logged and forgotten, so a run stayed green with resources left behind; failures are now reported as leaks, failing the bound test or surfacing through Close() for TestMain to fail the run. And a panic in one cleanup aborted the whole chain, stranding every resource behind it; each callback is now isolated. RegisterVolumeTeardown and the fixture had grown separate teardown paths, only one of which detached. Both now share it.
What is Spinifex? · Platform · Deploy · AWS services · Components · Architecture · Installation · Docs
Spinifex: the open, AWS-compatible cloud you run yourself
Spinifex, built by Mulga, recreates the AWS services your software already uses (EC2, EBS, S3, VPC, IAM) on infrastructure you control. Move workloads off the hyperscalers, run AI at a fraction of the cost, or take the cloud to the edge, without rewriting a line. The exact build you ship to AWS, Spinifex serves on your own hardware: same APIs, same Terraform, same SDKs.
What is Spinifex?
Spinifex is an open-source infrastructure platform that recreates the AWS service surface (EC2, EBS, S3, VPC, IAM) on bare-metal, edge, and on-premises environments. Run cloud-native software without a hyperscaler.
Most AWS alternatives wrap an API and call it a cloud. We rebuilt the engineering underneath: distributed object storage with erasure coding, block storage built to survive failure, and compute on bare metal. That depth is the reason your software runs unchanged, instead of rewritten.
It's built for teams that need:
- The AWS tooling they already use (AWS CLI, SDKs, Terraform), with nothing to rewrite
- Full control of the stack: your hardware, your network, your data, your keys
- A cloud that keeps running offline, through disconnection, with no external control plane
- An open core (AGPL-3.0), auditable and yours to keep, with no lock-in
You change where your software runs, not what it is.
The Platform
From commodity hardware up to unmodified AWS tooling, every layer is replaceable and yours to own.
Three ways to deploy
One AWS-compatible surface, three deployment shapes. Pick the one that matches your reality; the platform on top is the same.
Neocloud
Lift and shift onto a partner Neocloud. Move workloads off the hyperscalers and onto our Neocloud partner ecosystem without rewriting them. GPU capacity (H100 / H200 / B200), cheaper, available now. Change an endpoint, keep the software.
On-premise
Bring your own hardware and host Spinifex in your own data centre. A real multi-node HA cluster integrated with your storage and networking, with full control of stack, data, and jurisdiction. A predictable bill, no egress surprises, an auditable open-source core.
Edge
Cloud where the cloud can't reach. Air-gapped sites, vehicles, vessels, factories, and clinics. Compute next to the data, running through disconnection, on hardware you own. The same AWS APIs your software already uses.
AWS compatibility
Speak the AWS API surface, natively. The AWS SDKs, AWS CLI, and Terraform: everything you deploy on AWS deploys on Spinifex unchanged. At the edge, on-premise, or on a partner Neocloud.
| Service | What it is | Status |
|---|---|---|
| EC2 | Compute | Available |
| EBS | Block storage | Available |
| S3 | Object storage | Available |
| VPC | Networking | Available |
| IAM | Identity & auth | Available |
| ALB / NLB | Load balancers | Available |
| EKS | Kubernetes | Available |
| ECR | Container registry | Available |
| ECS | Container service | Available |
| RDS | Databases | Q3 2026 |
Roadmap items (Q3 2026) ship under the same AWS API surface. Code written for AWS today keeps working the moment they land. Track what's shipped in the release notes.
Core Components
Spinifex (Compute Service – EC2 Alternative)
Spinifex is a minimal VM orchestration layer built on top of QEMU, exposing APIs similar to EC2. It manages lifecycle operations like start, stop, and terminate, using QEMU's QMP interface. Designed to be straightforward and scriptable, Spinifex lets you launch VMs using the AWS CLI, SDKs, or Terraform—without needing Kubernetes or heavyweight orchestrators. Keep in mind, you can also setup a Kubernetes environment using Spinifex with underlying instances.
- EC2-like VM management on bare metal
- Launches with cloud-init metadata support
- Works with standard AWS tooling
Viperblock (Block Storage – EBS Alternative)
Viperblock is a high-performance, WAL-backed block storage service that replicates volumes across multiple nodes. It's built for reliability and speed, with support for snapshots, recovery, and direct connection to QEMU instances using NBD or virtio-blk.
- Fast, durable virtual disks
- Replication for resilience
- Exposed over NBD or embedded in VMs
- Supports high performance WAL logs using local NVMe drives to reduce IO traffic to S3.
- In memory read/write block cache for blazing performance.
Predastore (Object Storage – S3-Compatible)
Predastore is a fully S3-compatible object storage system. It supports the AWS S3 API, including Signature V4 authentication, multipart uploads, and Terraform provisioning. Data is chunked and distributed across nodes using Reed-Solomon erasure coding, making it fault-tolerant and ideal for large-scale or low-bandwidth scenarios.
- S3-compatible API and auth
- Multipart uploads, streaming reads/writes
- Data redundancy with Reed-Solomon encoding
Architecture at a Glance
Every AWS API call is authenticated at the gateway, published to a NATS subject,
and answered by whichever daemon claims it. Daemons are stateless: scale
horizontally by starting more. No etcd, no Kubernetes, no external control plane.
Just systemd units, a NATS cluster, and your hardware. Deep dive:
docs/DESIGN.md.
Key Features
- AWS-compatible APIs. Use the AWS CLI, SDKs, and Terraform you already know. Repoint your endpoint and ship; nothing to rewrite.
- Zero cloud dependency. Runs entirely on your hardware. No phone-home, no control plane, no external authority. Works fully offline.
- Bare-metal compute. QEMU-based with direct hardware access. No hypervisor tax, no abstraction overhead.
- Built-in storage. Block and object storage included: NVMe caching, Reed-Solomon erasure coding, and replication out of the box.
- Edge-first architecture. Designed for disconnected, contested, and resource-constrained environments from day one.
- Open core, no lock-in. AGPL-3.0 with a commercial option. Inspect it, modify it, deploy it. The platform is yours to keep.
Installation
Installation requires an Ubuntu / Debian system. See the detailed documentation at docs.mulgadc.com for maintaining and installing Spinifex.
Bare Metal ISO
The recommended installation is a bootable x86 installer for bare-metal hardware.
curl -fLO https://iso.mulgadc.com/spinifex.iso
Follow the USB install guide to write the ISO to USB and install on your hardware. The install guide walks through the full process.
Single Node Install
The installation is straightforward to set up and running on a single node for testing purposes. Debian 13 is currently supported, additional Linux distributions are on the immediate roadmap.
Prerequisite: Linux bridge for networking.
Spinifex requires a Linux bridge configured on the host for VM networking. See the single-node install guide prerequisites for setup details.
curl -fsSL https://install.mulgadc.com | bash
sudo /usr/local/share/spinifex/setup-ovn.sh --management
sudo spx admin init --node node1 --nodes 1
sudo systemctl start spinifex.target
export AWS_PROFILE=spinifex
aws ec2 describe-instance-types
Development Setup
For a complete development environment see the Source Install documentation
Component Repositories
Spinifex coordinates these independent components:
- Predastore - S3-compatible object storage
- Viperblock - EBS-compatible block storage
Each component can be developed independently. See component-specific documentation for focused development guides.
Spinifex UI
Spinifex ships with a built-in web console — an optional alternative to the AWS CLI, SDKs, and Terraform. If you're familiar with the AWS Management Console, the Spinifex UI fills the same role: a browser-based view of your instances, volumes, buckets, VPCs, and IAM resources, without leaving your own network.
The console is served by each node on port 3000 over TLS, and becomes available as soon as spinifex.target is up:
open https://YOUR_NODE_IP:3000
- Same API, different surface. Every action in the UI is the same AWS SigV4 call the CLI makes — so RBAC, audit trails, and IAM policies apply uniformly.
- Single sign-on against your AWS credentials. Log in with the access keys from
~/.aws/credentialson the node where Spinifex is installed — no separate user database. - Self-hosted, works offline. The UI is embedded in the Spinifex binary and served from the node itself. No external CDN, no analytics calls, no cloud dependency.
For the full walkthrough — first-time TLS certificate trust, login, and feature tour — see Launching the Web UI in the cluster setup guide.
Development Philosophy
Built by Engineers, For Engineers
Spinifex is developed by experienced infrastructure engineers with deep AWS expertise, including former AWS team members who understand the intricacies of building production-grade cloud services. Our team brings decades of combined experience from AWS, enterprise infrastructure, and edge computing environments.
Real-World Experience:
- Production AWS service development and operations
- Large-scale infrastructure deployment and management
- Edge computing and resource-constrained environments
- Enterprise security and compliance requirements
AI-Assisted Development
While Spinifex is architected and implemented by experienced engineers, we leverage Claude Code (Anthropic's AI coding assistant) to accelerate certain development tasks. This approach combines human expertise with AI efficiency:
How We Use Claude Code:
- Code Generation: Boilerplate AWS API structures and handlers
- Documentation: Comprehensive development guides and API documentation
- Testing: Test case generation and validation scenarios
- Refactoring: Large-scale code restructuring and optimization
What Remains Human-Driven:
- Architecture Decisions: Core system design and scalability choices
- Security Implementation: Authentication, encryption, and threat modeling
- Performance Optimization: Real-world performance tuning and benchmarking
- Production Operations: Deployment strategies and operational procedures
This hybrid approach ensures Spinifex benefits from both proven engineering expertise and modern development acceleration, while maintaining the quality and reliability standards required for production infrastructure.
Trademarks
"AWS", "Amazon Web Services", and all related service names (EC2, EBS, S3, VPC, IAM, and others) are trademarks of Amazon.com, Inc. or its affiliates. Mulga Defense Corporation and Spinifex are independent and not affiliated with, endorsed by, or sponsored by Amazon.com, Inc. or Amazon Web Services, Inc. References to AWS services describe interoperability and compatibility only.
License
Spinifex is open source under the GNU Affero General Public License v3.0. You're free to use, modify, and deploy it anywhere you need reliable infrastructure without depending on centralized cloud platforms.