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claude-botandClaude Opus 5 11cd02ec44 refactor(paperless): retire paperless-data, the CephFS predecessor volume
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The `data` volume moved from paperless-data (RWX, ceph-filesystem) to
paperless-data-block (RWO, ceph-block) on 2026-08-28. paperless-data was
kept as the rollback, on the condition that search be confirmed working
first — the point being to prove the Whoosh index survived the copy, not
merely that paperless started.

Both halves of that condition are now settled. index_optimize succeeded on
every night between the repoint and 2026-09-01, and that task opens and
rewrites the index rather than just reading it. Then the 3.1.2 upgrade
replaced Whoosh with Tantivy outright, so the index paperless-data was
preserving no longer exists in a form anything can read.

Removed: the PVC, the migration record, and the comments that described the
volume as in-flight. The rationale for RWO-on-RBD stays where it is useful,
on the PVC and on the Deployment's volume list, since it is the reason not
to move this back onto a shared filesystem later.

paperless-data carries kustomize.toolkit.fluxcd.io/prune: disabled, so this
commit does not delete anything by itself. The PVC, its Retain-policy PV and
the backing CephFS subvolume have to be removed by hand.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-02 07:13:07 +02:00
6 changed files with 18 additions and 227 deletions
+1 -26
View File
@@ -44,37 +44,12 @@ spec:
- Qwen/Qwen3-Embedding-0.6B-GGUF:Q8_0
# Serves POST /v1/embeddings.
- --embeddings
# A short, stable id for consumers. Without it the model is
# advertised as the whole --hf-repo string, which would end up
# verbatim in Paperless's config and break on the next model swap.
# One name only: llama-server keeps aliases in a sorted set and
# reports the first as the id, so a second name can steal it.
- --alias
- qwen3-embedding-0.6b
# Qwen3-Embedding is trained for last-token pooling. Left
# unspecified llama-server takes the GGUF's default, which is not
# visible from outside and would silently produce vectors the model
# was not trained to emit. Set before anything is indexed: changing
# pooling later invalidates every stored embedding.
- --pooling
- last
- --n-gpu-layers
- "99"
- --threads
- "2"
# Paperless chunks documents at 1024 tokens. The defaults are
# batch 2048 / ubatch 512, and with --embeddings llama-server
# clamps both down to 512 rather than run them mismatched — below
# the chunk size. Matching both to 1024 fits a whole chunk in one
# pass; 2048 is deliberately avoided, since that is where this
# Vulkan stack fails with ErrorDeviceLost.
- --batch-size
- "1024"
- --ubatch-size
- "1024"
# Room for a full chunk plus overhead rather than exactly one.
- --ctx-size
- "4096"
- "2048"
# No browser ever talks to this Service, so the WebUI is dead weight
# and one more unauthenticated surface.
- --no-webui
@@ -1,97 +0,0 @@
# paperless-data: CephFS → RBD
## Why
`paperless-data` is `ReadWriteMany` on `ceph-filesystem`, but **only the paperless
Deployment mounts it**. Verified 2026-08-20:
```
$ pods mounting paperless-data
paperless-68cb8b8744-7hjb8 <- one, and only one
paperless-data ReadWriteMany ceph-filesystem
paperless-media ReadWriteMany ceph-filesystem <- genuinely shared (ftp-scanner)
paperless-consume ReadWriteMany ceph-filesystem <- genuinely shared (ftp-scanner)
```
Its contents are single-writer state — the 50 MB Whoosh index,
`classification_model.pickle`, `celerybeat-schedule.db`, `log/`,
`migration_lock`, `protonmail.pem`. 75 files. Nothing else reads or writes them.
It is on CephFS by default, not by requirement.
## What it costs
Every access goes through the MDS. Measured with **zero CI pipelines running**:
```
paperless-data client request_load_avg 22 (all other sessions 0-1)
MDS over 180s 4,052 client requests = 22.5/s
2,718 journal events = 15/s
2 dir commits <- almost none: not file writes
```
So it is cap/inode churn from repeated access, not data being written. That is
most of the constant **7-8 GB/day** written to `cephfs-metadata`, and since that
pool is `size: 3`, roughly **21-24 GB/day** reaches the drives.
`cephfs-metadata` deliberately stays at size 3. Losing it destroys the entire
filesystem rather than the objects on one OSD, and the 275 GiB in `cephfs-data0`
depends on it. Cutting the writes at source is correct; cutting the replication
is not.
## Sequence
Staged deliberately: the PVC lands first and empty, so merging it changes
nothing. The copy and the repoint are separate.
### Phase 1 — provision (this PR)
`paperless-data-block` (RWO, `ceph-block`, 10Gi) is created and mounted by
nothing. Inert.
Verify: `kubectl -n paperless get pvc paperless-data-block` → Bound.
### Phase 2 — copy
The Whoosh index must come across intact. Paperless *can* rebuild it
(`document_index reindex`), but that reprocesses every document, so copying is
both faster and less disruptive.
1. Scale paperless to 0. The source must be quiescent — `celerybeat-schedule.db`
and the Whoosh index are both live-written, and copying them under an active
writer gives a torn read.
2. Run a one-off pod that mounts BOTH PVCs and copies:
```
cp -a /src/. /dst/
```
The RWO target pins the pod to one node; the RWX source will follow.
3. Verify file count and index size match:
```
find /src -type f | wc -l == find /dst -type f | wc -l
du -sh /src/index == du -sh /dst/index
```
### Phase 3 — repoint
Change the Deployment's `data` volume to `claimName: paperless-data-block`,
merge, let it roll.
Verify afterwards:
- paperless starts, search returns results (proves the Whoosh index survived)
- `ceph tell mds.cephfs-b session ls` no longer shows a busy `paperless-data`
client
- `rate(ceph_pool_wr_bytes{pool_id="3"})` drops from its 7-8 GB/day baseline
**Do not delete `paperless-data` until search has been confirmed working.** It is
the rollback, and it is `prune: disabled` so Flux will not remove it.
## Expected effect
~7-8 GB/day off `cephfs-metadata`, so ~21-24 GB/day off the drives once
replication is counted. Against ~432 GB/day cluster-wide that is roughly 5% —
worth doing, but it is a correctness fix (a single-writer volume does not belong
on a shared filesystem) more than a large win.
It also removes 22 req/sec of MDS load, which benefits the workloads that
genuinely need CephFS — Woodpecker CI workspaces share the same MDS.
@@ -57,20 +57,6 @@ spec:
protocol: UDP
- port: "53"
protocol: TCP
# The cluster's own LLM, for AI suggestions and RAG embeddings. Scoped to
# the two pods and the one port rather than the ai namespace as a whole, so
# this grant cannot widen if something else is ever placed there.
- toEndpoints:
- matchLabels:
"k8s:io.kubernetes.pod.namespace": ai
app.kubernetes.io/name: llama-server
- matchLabels:
"k8s:io.kubernetes.pod.namespace": ai
app.kubernetes.io/name: llama-embed
toPorts:
- ports:
- port: "8080"
protocol: TCP
# External HTTPS only — Tika model downloads, runtime image
# fetches, etc. RFC1918 + ULA are excluded from `world` via the
# CIDR-deny pattern. `world` covers public IPs / DNS-resolvable
+7 -51
View File
@@ -46,44 +46,6 @@ data:
PAPERLESS_TIKA_ENABLED: "1"
PAPERLESS_TIKA_ENDPOINT: "http://tika:9998"
PAPERLESS_TIKA_GOTENBERG_ENDPOINT: "http://gotenberg:3000"
# AI suggestions against the cluster's own LLM (kubernetes/apps/llama-server).
# Nothing leaves the cluster: both endpoints are ClusterIP Services, so
# document text is never sent to a third party and there is no API key to
# rotate — llama-server has no authentication, and the ai namespace's network
# policy is what restricts who may reach it.
#
# CAVEAT, and it is a real one: paperless reads these from an
# ApplicationConfiguration row in the database and falls back to the
# environment only when that row is empty. A value set in the admin UI
# therefore overrides this ConfigMap silently. Configure AI in ONE place —
# here — and leave those fields untouched in the UI.
PAPERLESS_AI_ENABLED: "true"
PAPERLESS_AI_LLM_BACKEND: "openai-like"
PAPERLESS_AI_LLM_ENDPOINT: "http://llama-server.ai.svc.cluster.local:8080/v1"
# Must match --alias in kubernetes/apps/llama-server/deployment.yaml. The
# server ignores the field on the wire, but paperless sends it and the value
# is what appears in its logs.
PAPERLESS_AI_LLM_MODEL: "qwen3.6-35b-a3b"
# ClusterIP addresses are private, and paperless blocks non-public endpoints
# unless this is set. Default is already true; explicit because the whole
# integration silently stops working if it ever flips.
PAPERLESS_AI_LLM_ALLOW_INTERNAL_ENDPOINTS: "true"
# Under llama-server's own 16384, leaving room for the response.
PAPERLESS_AI_LLM_CONTEXT_SIZE: "12288"
# The 120s default is too tight at ~11 tok/s: a classification is roughly
# 2-4k prompt tokens plus a second round trip for localisation.
PAPERLESS_AI_LLM_REQUEST_TIMEOUT: "300"
# Matched against Django's settings.LANGUAGES, so the region is required —
# "de" alone does not resolve. Without it the model returns German tags but
# English document types, which was reproducible against this endpoint.
PAPERLESS_AI_LLM_OUTPUT_LANGUAGE: "de-de"
# RAG embeddings from llama-embed. Its Qwen3-Embedding covers 100+ languages,
# where paperless's default all-MiniLM-L6-v2 is documented as suited to
# primarily English archives — the better fit for a German corpus.
PAPERLESS_AI_LLM_EMBEDDING_BACKEND: "openai-like"
PAPERLESS_AI_LLM_EMBEDDING_ENDPOINT: "http://llama-embed.ai.svc.cluster.local:8080/v1"
PAPERLESS_AI_LLM_EMBEDDING_MODEL: "qwen3-embedding-0.6b"
PAPERLESS_AI_LLM_EMBEDDING_CHUNK_SIZE: "1024"
---
apiVersion: apps/v1
kind: Deployment
@@ -279,22 +241,16 @@ spec:
seccompProfile:
type: RuntimeDefault
volumes:
# paperless-data-block (RWO, ceph-block), NOT paperless-data
# (RWX, ceph-filesystem). Only this Deployment ever mounted the volume,
# and its contents are single-writer state — the Whoosh index,
# classification model, celerybeat schedule, logs. Being on CephFS meant
# every access went through the MDS: 22 requests/sec sustained with zero
# CI running, ~15 journal events/sec against 2 directory commits per
# 180s, i.e. cap/inode churn rather than file writes. That was most of
# the constant 7-8 GB/day on cephfs-metadata, and that pool is size 3.
# `data` is RWO on ceph-block, not RWX on ceph-filesystem. Only this
# Deployment mounts it and its contents are single-writer state — the
# search index, classification model, celerybeat schedule, logs. On
# CephFS every access went through the MDS: 22 requests/sec sustained
# with zero CI running, ~15 journal events/sec against 2 directory
# commits per 180s, i.e. cap/inode churn rather than file writes. That
# was most of the constant 7-8 GB/day on cephfs-metadata, a size 3 pool.
#
# `consume` and `media` below STAY on CephFS: the ftp-scanner writes to
# those from another node, so they genuinely need RWX.
#
# paperless-data is retained (prune: disabled) as the rollback. Do not
# delete it until search has been confirmed working — that is what
# proves the Whoosh index survived the copy, not merely that paperless
# starts. Migration record: MIGRATION-data-to-block.md.
- name: data
persistentVolumeClaim:
claimName: paperless-data-block
+10 -29
View File
@@ -3,33 +3,18 @@
# (e.g. when the seed initContainer or the Garage migration creds are
# removed once we're done with the migration phase). Velero's
# bootstrap-restore then owns their contents.
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: paperless-data
namespace: paperless
annotations:
kustomize.toolkit.fluxcd.io/prune: disabled
spec:
accessModes:
- ReadWriteMany
storageClassName: ceph-filesystem
resources:
requests:
storage: 10Gi
---
# Replacement for paperless-data, on RBD instead of CephFS.
# paperless's single-writer state, on RBD rather than CephFS.
#
# WHY: paperless-data is declared ReadWriteMany on ceph-filesystem, but only ONE
# pod ever mounts it — the paperless Deployment itself. Its contents are all
# single-writer state: the 50 MB Whoosh index, classification_model.pickle,
# celerybeat-schedule.db, logs, migration_lock. Nothing shares it. Only `consume`
# and `media` genuinely need RWX, because the FTP scanner writes to those from a
# different node.
# WHY RWO: only ONE pod mounts it — the paperless Deployment itself. Its
# contents are all single-writer state: the Tantivy search index,
# classification_model.pickle, celerybeat-schedule.db, logs, migration_lock.
# Nothing shares it. Only `consume` and `media` genuinely need RWX, because the
# FTP scanner writes to those from a different node.
#
# COST OF LEAVING IT: every access goes through the MDS. Measured 2026-08-20 with
# zero CI running, this volume's client was doing 22 MDS requests/sec sustained,
# and the MDS logged ~15 journal events/sec against only 2 directory commits per
# WHY NOT CEPHFS: every access goes through the MDS. With zero CI running, this
# volume's client sustained 22 MDS requests/sec, and the MDS logged ~15 journal
# events/sec against only 2 directory commits per
# 180s — i.e. cap and inode churn from repeated access, not file writes. That is
# most of the constant 7-8 GB/day written to cephfs-metadata, which is a size 3
# pool, so ~21-24 GB/day actually hits the drives.
@@ -38,10 +23,6 @@ spec:
# the metadata pool destroys the whole filesystem, not just the objects on one
# OSD, so the 275 GiB in cephfs-data0 rides on it. Reducing the writes at source
# is the right fix; reducing the replication is not.
#
# MIGRATION: this PVC is created EMPTY and nothing mounts it yet. The data copy
# and the deployment repoint are a separate, staged step — see
# MIGRATION-data-to-block.md. Merging this alone is inert.
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
@@ -24,16 +24,6 @@ spec:
- ports:
- port: "8080"
protocol: TCP
# Paperless calls both models for AI suggestions and RAG embeddings. The
# matching egress grant on its side is scoped to these two pods on :8080.
- fromEndpoints:
- matchLabels:
"k8s:io.kubernetes.pod.namespace": paperless
app.kubernetes.io/name: paperless
toPorts:
- ports:
- port: "8080"
protocol: TCP
- fromEndpoints:
- matchLabels:
"k8s:io.kubernetes.pod.namespace": monitoring