Sienna Meridian Satterwhite
e4987b4c58
The Longhorn memory leak went undetected for 14 days because alerting was broken (email receiver, missing label selector, no node alerts). This overhaul brings alerting to production grade. Fixes: - Alloy Loki URL pointed to deleted loki-gateway, now loki:3100 - seaweedfs-bucket-init crash on unsupported `mc versioning` command - All PrometheusRules now have `release: kube-prometheus-stack` label - Removed broken email receiver, Matrix-only alerting New alert coverage: - Node: memory, CPU, swap, filesystem, inodes, network, clock skew, OOM - Kubernetes: deployment down, CronJob failed, pod crash-looping, PVC full - Backups: Postgres barman stale/failed, WAL archiving, SeaweedFS mirror - Observability: Prometheus WAL/storage/rules, Loki/Tempo/AlertManager down - Services: Stalwart, Bulwark, Tuwunel, Sol, Valkey, OpenSearch (smart) - SLOs: auth stack 99.9% burn rate, Matrix 99.5%, latency p95 < 2s - Recording rules for Linkerd RED metrics and node aggregates - Watchdog heartbeat → Matrix every 12h (dead pipeline detection) - Inhibition: critical suppresses warning for same alert+namespace - OpenSearchClusterYellow only fires with >1 data node (single-node aware)
46 lines
1.8 KiB
YAML
46 lines
1.8 KiB
YAML
apiVersion: monitoring.coreos.com/v1
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kind: PrometheusRule
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metadata:
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name: linkerd-mesh-alerts
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namespace: mesh
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labels:
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role: alert-rules
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release: kube-prometheus-stack
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spec:
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groups:
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- name: linkerd-mesh
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rules:
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- alert: ServiceHighErrorRate
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expr: |
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sum(rate(response_total{classification="failure",direction="inbound"}[5m])) by (deployment, namespace)
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/ sum(rate(response_total{direction="inbound"}[5m])) by (deployment, namespace)
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> 0.05
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for: 5m
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labels:
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severity: warning
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annotations:
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summary: "Service has high error rate"
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description: "{{ $labels.deployment }} in {{ $labels.namespace }} has {{ $value | humanizePercentage }} error rate"
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- alert: ServiceHighErrorRateCritical
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expr: |
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sum(rate(response_total{classification="failure",direction="inbound"}[5m])) by (deployment, namespace)
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/ sum(rate(response_total{direction="inbound"}[5m])) by (deployment, namespace)
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> 0.25
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for: 2m
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labels:
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severity: critical
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annotations:
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summary: "Service has critically high error rate"
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description: "{{ $labels.deployment }} in {{ $labels.namespace }} has {{ $value | humanizePercentage }} error rate"
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- alert: ServiceHighLatency
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expr: |
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histogram_quantile(0.95, sum(rate(response_latency_ms_bucket{direction="inbound"}[5m])) by (le, deployment, namespace)) > 2000
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for: 5m
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labels:
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severity: warning
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annotations:
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summary: "Service has high p95 latency"
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description: "{{ $labels.deployment }} in {{ $labels.namespace }} p95 latency is {{ $value }}ms"
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