Repoints WOODPECKER_BACKEND_K8S_STORAGE_CLASS at ceph-filesystem-ci, the
dedicated filesystem added in #542 whose pools are both size 1.
Measured 2026-08-21, polling both CephFS pools every 15s:
CI active 1.5 min (6 intervals): data0 143.2 MB metadata 17.2 MB
CI idle 16.0 min (63 intervals): data0 0.0 MB metadata 11.0 MB
CI share of writes: data0 100%, metadata 61%
data0 takes zero bytes across 16 minutes without a pipeline, so its entire
write volume is CI. The 15s cadence is what made this visible: a pipeline
creates, uses and deletes its PVC inside ~2 minutes, so a 5-minute sample
reported no CI pods during bursts CI was causing.
Per pipeline this moves the drive cost from 71.6x2 + 8.2x3 = ~168 MB to
~80 MB, since neither pool is replicated on the new filesystem.
RWX is unchanged and still required: pipeline steps share the workspace PVC
and the k8s backend can schedule them on different nodes, so an RWO volume
fails to mount on the second node. Only the filesystem underneath changes.
Also corrects the justification written into #542 for leaving
ceph-filesystem-ephemeral alone. That commit claimed restore-test.sh handles
"REAL data which must not land on unreplicated pools". That is wrong: its
probe PVCs are as throwaway as a CI workspace -- the authoritative copy is the
backup on Hetzner, and losing a probe just means re-running the test.
The actual reason it cannot move is technical: those probes are snapshot
CLONES, and `ceph fs subvolume snapshot clone` operates within a single
filesystem, so a snapshot taken in `cephfs` cannot be cloned into `cephfs-ci`.
Landing them unreplicated would require a second size-1 data pool inside
`cephfs`; restore-test runs weekly against CI's ~96 pipelines/day, so that is
not worth the complexity.
cephfs-ci verified healthy before this change: PHASE Ready, MDS Running, both
pools reporting size 1.
Woodpecker's Kubernetes backend creates a PVC per pipeline, fills it with a
checkout plus build output, and deletes it when the pipeline ends. Those
workspaces currently live on the shared `cephfs`, so throwaway data is
replicated as if it mattered: 2x in cephfs-data0 and 3x in cephfs-metadata.
Measured 2026-08-21 by polling both pools every 15s. The interval matters --
at 5 minutes a whole pipeline is invisible, because its PVC is created, used
and deleted inside ~2 minutes. Sampling that slowly reported zero CI pods
during bursts CI was causing, which sent this investigation down three wrong
paths before the cadence was fixed.
one pipeline, a single 15s interval: data0 +71.6 MB metadata +8.2 MB
every interval with no CI pod: data0 ~0 metadata ~0
So CI accounts for essentially all CephFS write volume; between pipelines the
metadata pool is quiet at ~4 MB/day. On the shared filesystem one pipeline
costs 71.6x2 + 8.2x3 = ~168 MB of drive writes. On this one it costs ~80 MB.
size 1 is correct here even though it was rejected for `cephfs`. There,
metadataPool stays at 3 because losing it destroys the entire filesystem
rather than the objects on one OSD, and 550 GiB of real data depends on it.
Here every byte is a fresh git clone: total loss means in-flight pipelines
fail and get re-run. Replicating throwaway data was the cost, so it is what
gets removed.
`ceph-filesystem-ephemeral` is deliberately NOT repointed. It has a second
consumer -- velero/restore-test.sh restores REAL data through it for
verification, which must not land on unreplicated pools. A new class also
sidesteps StorageClass.parameters being immutable.
Nothing uses ceph-filesystem-ci yet, so this commit is inert: it provisions
the filesystem and its MDS and changes no existing workload. Repointing the
Woodpecker agent is a separate change, once this is confirmed healthy.
Known consequence: size 1 raises POOL_NO_REDUNDANCY, so cluster health will
warn until that is addressed. Silencing it via mon_warn_on_pool_no_redundancy
is cluster-wide and would also hide a production pool dropping to 1, so it
wants a targeted alert instead -- deliberately left out of this commit rather
than switching the warning off blind.
The MDS is 512Mi/1Gi with no standby, not the 4Gi active+standby that `cephfs`
runs. That figure is driven by immich's cached inode count; a CI workspace is
a few thousand files that vanish with the pipeline, and a second daemon to
protect throwaway work is not worth its memory.
A WAL segment is a fixed 16 MiB file. archive_timeout forces a switch on a
timer, and the switched-out segment is written and archived at its full size
no matter how little real WAL it holds. CNPG defaults to 5min, permitting
288 segments/day per cluster of largely padding.
gf-pg went first as a staged rollout and is now verified: 211 -> 41 MB/hour,
an 81% cut, with archived segments falling from ~12/hour to ~1.5/hour in
step. Two independent signals moving together is what confirms the volume
was padding rather than data, and the measured result matched the ~35
MB/hour predicted beforehand.
Fleet-wide this is worth roughly 18 GB/day of logical writes, which at
size=2 with ~1.27x BlueStore overhead is ~45 GB/day at the drives -- about
14% of the 328 GB/day the three OSD NVMes currently take.
ak-pg gets 15min rather than 30min. It holds credentials, sessions and
enrolment state, and the extra 15min would save only a further 0.3 GB/day,
which does not justify doubling the worst-case loss window on that data.
ha-pg saves least in relative terms: its segments are already 63% full of
real WAL (4.9 GB/day), so the timer is not what drives most of its switches.
Also corrects two comments in ha-pg-cluster.yaml that this work falsified.
wal_compression: the claim that these clusters "were not getting compression"
was wrong -- "on" is pglz, which was already compressing. Switching to zstd
moved the WAL rate not at all (4911/4976 -> 5002 MB/day, by LSN advance over
20min windows). Full-page images genuinely are ~62% of WAL here (61.9%
measured as a steady-state delta, against 62.4% lifetime -- so the migration
did not skew it, which was my first guess and it was wrong). There was simply
no headroom between pglz and zstd on this data. zstd is kept because it is
not worse and costs nothing, but it is not a lever.
checkpoint_timeout: 15min -> 30min likewise did not move WAL. Probable reason
is that a recorder is append-mostly -- a page is dirtied while it fills and
then not touched again, so it pays its full-page image once whatever the
checkpoint interval. Kept, but flagged as unjustified pending a data-file
measurement: this volume takes ~11 GB/day against 4.9 GB/day of WAL, so most
of its traffic is outside what a WAL measurement can see.
Context: drive-endurance work on three QLC NVMe OSDs at 81-87% wear.
A WAL segment is a fixed 16 MiB file. archive_timeout forces a segment
switch on a timer so the archive never trails reality by more than that
interval, and the switched-out segment is written and archived at its full
16 MiB no matter how few bytes of real WAL it holds. CNPG defaults this to
5min, which permits up to 288 segments/day = 4.6 GB/day per cluster.
Measured on gf-pg: the database is 21 MB and generates 4.5 MB/day of actual
WAL, while its RBD volume takes 211 MB/hour -- against 192 MB/hour predicted
from 12 switches of 16 MiB. Essentially every byte written to this volume is
padding, roughly 1100x amplification.
This resolves an anomaly that has been open since the start of the endurance
work: gf-pg appeared to write gigabytes per day for a 21 MB database, and
neither WAL volume nor data changes could account for it. Segment padding
does, exactly.
Applied to gf-pg alone as a staged rollout. It is the lowest-risk cluster
and gives the cleanest signal -- its real WAL is small enough that any change
in volume is unambiguously attributable to this parameter. The same default
affects all seven clusters and is worth an estimated ~24 GB/day of logical
writes fleet-wide, but that only goes ahead once this one is verified.
The cost is RPO. On total loss of the cluster, up to 30min of Grafana state
becomes unrecoverable instead of 5min. That state is dashboards, annotations
and preferences, changing at ~4.5 MB/day, so the window is nearly always
empty. Clusters holding credentials or job state get evaluated separately
rather than inheriting this value by default.
archive_timeout is in CNPG's GlobalDefaultSettings, not its
FixedConfigurationParameters, so it is user-overridable -- verified against
pkg/postgres/configuration.go rather than assumed.
Context: drive-endurance work on three QLC NVMe OSDs at 81-87% wear.
`wal_compression: "on"` resolves to pglz, PostgreSQL's original 2016-era
algorithm. Every CNPG cluster here was set that way, so none of them were
getting the compression actually available to them: all seven builds accept
lz4 and zstd (verified via pg_settings.enumvals on each, including immich's
custom pgvector image and trmnl's PostgreSQL 18).
This matters because of what dominates recorder-style write volume. A page
is written to WAL in full -- all 8 KiB -- on its first modification after a
checkpoint, for torn-page protection. Measured on ha-pg, those full-page
images are 62.4% of WAL bytes. Compressing them is therefore the single
largest lever available on WAL volume, and pglz was the weakest option for
the job.
ha-pg additionally moves checkpoint_timeout 15min -> 30min. Full-page images
are emitted once per page per checkpoint interval, so doubling the interval
roughly halves how often each hot page pays the 8 KiB toll. max_wal_size
stays at 2GB deliberately: it must remain well above what one interval
generates, or checkpoints would trigger on size and the interval change
would do nothing. Recovery replays at most one interval of WAL -- under
200MB at the measured rate, i.e. seconds.
The other six clusters keep checkpoint_timeout at 15min. Their measured
write rates do not justify trading recovery time: gf-pg generates 4.5 MB/day
of WAL and wp-pg 62 MB/day, against ak-pg's 604 MB/day.
full_page_writes stays on everywhere. Disabling it would remove the
overhead entirely but RBD can tear a page across an object boundary, and
the trade is write volume against an unrecoverable database.
Both parameters are sighup-reloadable, so this does not restart any cluster.
Context: drive-endurance work on three QLC NVMe OSDs at 81-87% wear.
Prometheus held 298,236 active series. ~108,000 of them -- over a third -- were
apiserver/etcd `_bucket` histograms. Each fans out to one series per bucket x
verb x resource x scope, so a single metric was 23,810 series on its own. Every
Home Assistant metric combined is ~4,100 for comparison.
That cardinality is the dominant driver of Prometheus write volume (~11 GB/day of
TSDB + WAL, doubled again by Ceph replication) and none of it is observable value
on three nodes: per-bucket apiserver latency quantiles are for clusters with SLAs
and dozens of nodes.
Dropped, all verified to have ZERO rule dependencies by checking each metric
against the live alert and recording rules:
apiserver_request_duration_seconds_bucket rules=0 23,810 series
apiserver_request_body_size_bytes_bucket rules=0 23,200
etcd_request_duration_seconds_bucket rules=0 15,840
apiserver_watch_list_duration_seconds_bucket rules=0 11,538
apiserver_watch_cache_read_wait_seconds_bucket rules=0 8,232
apiserver_response_sizes_bucket rules=0 7,592
apiserver_watch_events_sizes_bucket rules=0 5,220
-------
95,432
KEPT deliberately: apiserver_request_sli_duration_seconds_bucket (12,144 series).
23 recording rules depend on it, including the apiserver availability SLO and the
KubeAPIErrorBudgetBurn burn-rate series. Dropping it would silently break that
alerting -- the manifest says so inline, so a later "tidy up" of the regex does
not remove it by accident.
Only `_bucket` series are dropped. The matching `_count` and `_sum` remain, so
request rates and mean latencies still work; what is lost is per-bucket
quantiles.
etcd_* is included even though kubeEtcd is disabled: those are the apiserver's
own etcd-client metrics on the apiserver endpoint, not a separate etcd scrape.
Expected: ~32% fewer active series, so roughly 11 -> 7 GB/day of Prometheus
writes, ~8 GB/day off the drives once replication is counted. Will verify against
prometheus_tsdb_head_series rather than assume.
Refs #434
Co-Authored-By: Claude Bot <noreply@anthropic.com>
An image reference is not a secret. Encoding it as base64 `data` had two real
costs: no reviewer sees a version change in a diff, and no $imagepolicy marker
can attach to a base64 blob.
The result was a two-minor version skew in the component that performs every
base backup and WAL archive for seven Postgres clusters (#535):
controller plugin-barman-cloud:v0.14.0 <- auto-bumped by Flux
sidecar plugin-barman-cloud-sidecar:v0.12.0 <- invisible, never moved
Not stale pods: ha-pg-1 was created hours ago during the recorder migration and
still received v0.12.0.
Three changes:
1. The Secret now uses stringData with the tag in plaintext, carrying an
$imagepolicy marker. The Secret KIND is kept because the controller reads it
via secretKeyRef; switching to a ConfigMap would need a matching edit to that
reference and diverge further from upstream. stringData is accepted
identically by the API server.
2. ImageRepository + ImagePolicy added for the sidecar image, with the same
filter and 0.x range as the controller, so the two cannot drift apart again.
Only the controller was tracked before.
3. Tag aligned to v0.14.0 to match the controller.
The Secret name carries a kustomize hash suffix from upstream's secretGenerator
but is static here, so editing the value does not change the name and the
deployment's secretKeyRef stays valid — verified in the render, which still shows
the name twice (Secret + reference).
Verified the tag EXISTS before pinning it: pulling
plugin-barman-cloud-sidecar:v0.14.0 succeeds (the pod fails later on a missing
`true` binary in that minimal image, which is the container command, not the
pull). Pinning a non-existent tag would have put all seven Postgres clusters into
ImagePullBackOff.
EXPECTED IMPACT: bumping the sidecar changes every Postgres pod spec, so all
seven CNPG clusters roll. CNPG handles this as a normal rolling restart. Backups
should be confirmed working afterwards — 113 Backup CRs exist today, newest ~3h
old and completed.
Note for future re-imports: upstream ships this Secret as base64 `data` with no
marker, so a wholesale re-import silently reintroduces the skew. The manifest now
says so inline.
Refs #535
Co-Authored-By: Claude Bot <noreply@anthropic.com>
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