* s3api: map ambiguous filer transport errors to retryable 503
Canceled, DeadlineExceeded and Unavailable can be returned after the
filer applied the write, so the outcome is ambiguous. Reporting them as
a 4xx tells the client not to retry; report ServiceUnavailable instead.
* s3api: verify entry existence before deleting orphaned chunks
A failed CreateEntry can still have landed on the filer when the error
is a transport failure, and entryCreated=false would tombstone chunks a
live entry references, leaving a dangling pointer that survives only
because reads pass readDeleted=true until vacuum reclaims the needle.
Before deleting, look the entry up: if it is stored with the same
chunks, the write succeeded; if the lookup cannot be answered, keep the
chunks for vacuum to reclaim; only a confirmed absence still cleans up.
* s3api: regression tests for ambiguous CreateEntry outcomes
Covers the three post-create-failure cases in putToFiler: the entry
landed despite the error (treat as success, keep chunks), the entry is
confirmed absent (delete orphans), and the outcome is unverifiable
(keep chunks, return error).
* volume: count reads served from deleted needles
A readDeleted read succeeding on a tombstoned needle is the signal that
metadata still points at deleted data. Count it under a
readDeletedNeedle handler label in both the Go and Rust volume servers
so the condition is visible before vacuum turns it into a 404.
* s3api: never delete chunks on an ambiguous create error
Review feedback on the first fix showed verification could still go
wrong in both directions: a stale or lagged lookup could report
not-found for a committed entry, a prefix object stores its chunks on a
directory entry, and filer-side manifestization rewrites the top-level
chunk ids the comparison relied on.
Rework the rule so the outcome classes are asymmetric:
- A transport-level error (anything filerErrorToS3Error maps to a
retryable 503) is ambiguous and never deletes chunks; the lookup can
only upgrade the write to success.
- Any other error is a definitive filer refusal and still cleans up.
confirmCreateLanded asks the write owner first, resolves the stored
entry through chunk manifests, requires an exact match of the uploaded
file ids, and on success runs the finalize callback the failed create
skipped (under the object write lock, with the same rmObject undo the
create path uses). Zero-chunk writes stay ambiguous since they cannot
be told apart by chunks.
* s3api: cover definitive refusals and stale entries in put tests
The confirmed-failure case now uses a definitive refusal so it still
exercises orphan cleanup, and a new case keeps chunks when the stored
entry belongs to an older object rather than this PUT.
* volume: count deleted-needle reads once per request
Streamed Go reads ran the deleted check in readNeedle and again in
readNeedleDataInto, and non-streamed Rust reads in stream_info and the
full-read fallback, double-counting one request. Count at the single
entry probe each implementation takes per GET: readNeedle in Go,
read_needle_stream_info in Rust.
* s3api: run recovered-write rollback under the object lock
Two follow-ups from review: ResolveChunkManifest returns traversed
manifest blobs in its manifestChunks output, so requiring it empty
rejected every manifestized landing; and the rmObject undo ran after
the object write lock was released, so a concurrent newer write could
be deleted between finalize failure and rollback. Compare only the
resolved data chunks and keep the undo inside the lock.
* s3api: verify, finalize and roll back recovered creates in one lock
A lookup done before the object write lock let a concurrent PUT replace
the entry between the chunk comparison and the finalize/rollback
section, so a failed afterCreate could rmObject a newer write. Run the
owner lookup, manifest resolution, chunk comparison, afterCreate and
the conditional undo inside a single withObjectWriteLock section.
Reads of remote-backed entries now record hit or miss in
SeaweedFS_remote_cache_read_total{source,bucket,result} on the filer HTTP
path and the S3 gateway, so cache effectiveness of mounted buckets can be
graphed. Inline-content entries count as hits since they are served
locally without chunks. The filer purges the per-bucket series when the
bucket directory is deleted, so a standalone filer does not accumulate
series across bucket delete/recreate churn.
* feat: add Prometheus metrics for replication operations
Adds 5 metrics to instrument volume server replication (write/delete):
- Operations counter with success/failure labels
- Duration histogram for latency tracking
- Targets gauge for replica fanout
- Failures counter with error reason labels
- Under-replicated volumes gauge on master
* fix: record replication duration histogram only when replicaCount > 0
* fix: update replication targets gauge for all operations including zero
* fix: ensure symmetric replication success/failure counting and proper metrics updates
* fix: change VolumeServerReplicationTargets from Gauge to Histogram
- Replace .Set() with .Observe() in store_replicate.go (2 occurrences)
- Update test to use CollectAndCount for histogram assertion
- Rename TestReplicationTargetsGauge -> TestReplicationTargetsHistogram
- Update documentation to reflect Histogram type and PromQL examples
* Add comments to replication metrics and improve test coverage
* metrics: add replication panels to grafana dashboard
Master row gets an under-replicated volumes timeseries; Volume Servers
row gets replication operations, failures-by-reason, p99 duration, and
average fan-out panels for the new replication metrics.
* metrics: name the replication duration histogram replication_seconds
Match the volumeServer convention (request_seconds, vacuuming_seconds)
rather than the admin/lifecycle _duration_seconds spelling.
* metrics: guard replication fan-out panel against divide-by-zero
clamp_min the _count rate so the avg-targets ratio reads 0 instead of
NaN when there are no replication events in the window.
---------
Co-authored-by: Ubuntu User <ubuntu@example.com>
Co-authored-by: Chris Lu <chris.lu@gmail.com>
* grow volumes if no writable volumes in current dataCenter
https://github.com/seaweedfs/seaweedfs/issues/3886
* fix tests with volume grow
* automatic volume grow one volume
* add ErrorChunkAssign metrics
Chris Lu