unkinben
c39af2f9c3
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
63 lines
1.8 KiB
YAML
63 lines
1.8 KiB
YAML
---
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# Vector ARCHIVER tier — long-term raw-log backup to S3 (Ceph RGW). Independent
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# durable JetStream consumer (`archiver`) so its offsets/lag are fully isolated
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# from the ClickHouse transform path (archive lag can never stall ingest — true
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# fan-out). Writes RAW, pre-transform events (as they sit in JetStream) as
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# gzipped NDJSON, partitioned by subject + date. This is the long-horizon replay
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# source beyond JetStream's 72h retention window.
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data_dir: /vector-data-dir
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api:
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enabled: true
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address: 0.0.0.0:8686
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sources:
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js_archive:
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type: nats
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url: nats://nats.logging.svc.cluster.local:4222
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connection_name: vector-archiver
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subject: "logs.>"
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jetstream:
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stream: LOGS
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consumer: archiver
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auth:
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strategy: user_password
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user_password:
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user: log-consumer
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password: ${NATS_CONSUMER_PASSWORD}
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decoding:
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codec: json
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sinks:
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s3:
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type: aws_s3
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inputs:
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- js_archive
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bucket: logs-archive
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endpoint: https://s3.ceph.unkin.net
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region: us-east-1
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force_path_style: true
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tls:
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ca_file: /etc/vault-ca/ca.crt
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# AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY come from the logs-archive-s3
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# Secret (cephrgw-operator) via envFrom on the deployment.
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key_prefix: "raw/{{ subject }}/%Y/%m/%d/"
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compression: gzip
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encoding:
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codec: json
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framing:
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method: newline_delimited
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filename_time_format: "%Y%m%dT%H%M%SZ"
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filename_append_uuid: true
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batch:
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max_bytes: 134217728
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timeout_secs: 300
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buffer:
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type: memory
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max_events: 5000
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when_full: block
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# Disabled so slow BucketAccess credential propagation doesn't crash-loop
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# the pod; RGW reachability is proven by the operator's own health.
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healthcheck:
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enabled: false
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