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3 Commits

Author SHA1 Message Date
unkinben 1202aae06f Pull images via artifactapi; make transform tier stateless
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Three changes from review:

1. Pull every container image through the artifactapi dockerhub remote instead
   of direct upstream: clickhouse-server, altinity operator + metrics-exporter,
   bitnami/kubectl (crdHook), nats + nats-server-config-reloader, nats-box
   (bootstrap Job), and vector (all tiers + the CI image). Requires
   terraform-artifactapi#16 (dockerhub allowlist patterns) merged first.

2. Keep upstream official images (no Docker Hardened Images). DHI exists for
   clickhouse-server and vector but is subscription-gated and served from a
   private org namespace not reachable via the anonymous artifactapi dockerhub
   proxy; its shell-less images would also break the bash bootstrap Jobs and the
   shell-based vector-test CI step. Use vector's distroless-libc for runtime
   pods (near-hardened) and the debian variant only for CI.

3. Make the transform tier a stateless Deployment (was a StatefulSet): no PVC,
   no disk buffer — JetStream is the sole durability layer. The ClickHouse sink
   uses an in-memory block buffer so a ClickHouse outage back-pressures the
   JetStream pull source (unpulled messages are retained/redelivered). Add a CPU
   HPA (2-8) — safe because JetStream pull consumers distribute work across N
   replicas on the one durable consumer. Caveat documented: vector's NATS source
   has no end-to-end acks (acks on receipt), so a pod killed mid-outage can lose
   its in-memory buffer window; accepted trade for a stateless autoscaling tier.

Claude-Session: https://claude.ai/code/session_015ur3i7D2azsMAWTSVABApv
2026-07-27 21:19:44 +10:00
unkinben c39af2f9c3 Insert NATS JetStream log bus + S3 raw archive
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Rework the logging pipeline around a durable message bus so logs survive a
ClickHouse outage, can be replayed after a bad transform, and fan out to
multiple independent consumers. Add long-term raw-log backup to S3.

Topology becomes edge -> JetStream -> consumers -> sinks:
- Dedicated JetStream NATS cluster (3 replicas, file storage) in the logging
  namespace. Deliberately separate from app messaging (streamstack) for
  blast-radius isolation. Stream LOGS (subjects logs.>, retention=limits, 40GiB
  / 72h) is the outage buffer; durable consumers give independent offsets.
- Edge publishers (thin): the k8s DaemonSet and a new VM-ingest Deployment
  (HTTP NDJSON front door behind the logs-ingest Gateway) publish into JetStream
  (logs.k8s.<ns>.<container> / logs.vm.<host>). No parsing on the edge.
- Transform tier (StatefulSet): pulls the whole stream via the durable
  `transform` consumer, routes by subject, shapes, and remains the sole
  ClickHouse writer. Its disk buffer shrinks (JetStream is the outage buffer).
- Archiver (Deployment): its OWN durable `archiver` consumer (independent
  offsets — archive lag never affects the ClickHouse path) writes RAW,
  pre-transform events to a Ceph RGW S3 bucket (cephrgw-operator ObjectStoreUser
  + Bucket + BucketAccess) as gzipped NDJSON keyed by raw/<subject>/YYYY/MM/DD/.
  Default subject filter is Vault audit (logs.k8s.vault.>), configurable.

Auth: distinct NATS users (producer publish-only, consumer pull+ack, admin for
the stream/consumer bootstrap Job) with passwords from Vault (nats-auth Secret);
S3 creds from the BucketAccess Secret. Streams/consumers are provisioned by an
idempotent PostSync bootstrap Job.

Add local kubeconform schemas for the ceph.unkin.net CRDs (datreeio lacks them)
and extend the vector-test CI to cover the agent, VM-ingest and archiver
configs. Verified end-to-end locally: NATS ACLs, vector JetStream publish, and
durable-consumer pull+ack (at-least-once) all work.

Claude-Session: https://claude.ai/code/session_015ur3i7D2azsMAWTSVABApv
2026-07-27 20:23:55 +10:00
unkinben 10020033d9 Add ClickHouse + Vector centralized logging stack
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ci/woodpecker/pr/kubeconform Pipeline was successful
Stand up a centralized logging estate that captures ALL logs from k8s pods and
(via a reachable ingestion endpoint) puppet-managed VMs, storing them in
ClickHouse for query/retention. Metrics already live in VictoriaMetrics; this
adds the logs pillar under a dedicated `logging` ArgoCD project.

Deploy the Altinity clickhouse-operator (clickhouse-system) and a single-shard
ClickHouseInstallation (logging) on cephrbd-fast-delete with a MergeTree
logs.raw table (30d TTL) bootstrapped by an idempotent PostSync Job.

Deploy Vector as an explicit two tiers:
- Edge (thin): a DaemonSet tails every node's pod logs and forwards over the
  Vector-native protocol to the aggregator; no parsing at the edge. Future VM
  agents follow the same thin pattern.
- Aggregator (brain): HA StatefulSet that is the sole ClickHouse writer, holds
  the only ClickHouse credentials, owns all transforms, batches into few fat
  inserts (avoid too-many-parts), and buffers to disk (PVC) to ride out a
  ClickHouse outage. Its pipeline is a single source-of-truth config validated
  by `vector test` in CI; per-app pipelines become aggregator-only changes.

Expose the VM ingestion endpoint at logs-ingest.k8s.syd1.au.unkin.net via the
internal Traefik gateway (cert-manager + external-dns), routing to the
aggregator's HTTP source so puppet VMs can reach it over TLS.

Source ClickHouse credentials from Vault via the existing VaultStaticSecret
pattern (templated k8s auth policy already grants the logging namespace);
password hash never lands in git.

Claude-Session: https://claude.ai/code/session_015ur3i7D2azsMAWTSVABApv
2026-07-27 19:49:17 +10:00