Raj Singh f34a7db48a fix: bound known_addrs growth
known_addrs in PeerInfoInternal is append-only — addresses accumulate
via add_addr() and PeerList gossip but are never removed. In dynamic
environments (k8s pod restarts, DHCP, NAT traversal), this list grows
unboundedly with stale addresses.

Combined with sequential iteration in try_connect() and no TCP connect
timeout in netapp.rs, each unreachable address blocks reconnection for
the kernel's TCP SYN timeout (75-130s on Linux). With 10+ stale
addresses, worst-case reconnection exceeds 750s — a full outage for
replication_factor=3 clusters.

This commit contains the two following changes:

1. Address failure tracking and pruning (peering.rs): Track consecutive
   connection failures per address in PeerInfoInternal. After 3 failures,
   prune from known_addrs. Reset count when address is re-advertised via
   gossip or incoming connection. Prevents unbounded list growth.

2. Shuffle before connecting (peering.rs): Randomize address order in
   try_connect() so the valid address (often appended last) gets a fair
   chance instead of always trying stale addresses first.
2026-04-15 11:42:38 +00:00
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2026-04-15 11:42:38 +00:00
2020-06-30 17:18:42 +02:00
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2020-04-10 22:01:48 +02:00

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Garage is an S3-compatible distributed object storage service designed for self-hosting at a small-to-medium scale.

Garage is designed for storage clusters composed of nodes running at different physical locations, in order to easily provide a storage service that replicates data at these different locations and stays available even when some servers are unreachable. Garage also focuses on being lightweight, easy to operate, and highly resilient to machine failures.

Garage is built by Deuxfleurs, an experimental small-scale self hosted service provider, which has been using it in production since its first release in 2020.

Learn more on our dedicated documentation pages:

Garage is entirely free software released under the terms of the AGPLv3.

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S3-compatible object store for small self-hosted geo-distributed deployments.
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