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Implement liveness, readiness, and dependency health checks
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Baseado na classificação ocupacional SOC
| name | health-checks |
| description | Implement liveness, readiness, and dependency health checks |
| triggers | ["health check endpoints","liveness probe","readiness probe","kubernetes health checks"] |
| priority | 1 |
Different checks serve different purposes. Don't conflate them.
| Endpoint | Purpose | On Failure | Should Check |
|---|---|---|---|
/health/live | Process alive? | K8s restarts pod | Only process responsiveness |
/health/ready | Can handle traffic? | K8s removes from LB | DB, cache, critical deps |
/health/startup | Init complete? | K8s waits | Initialization status |
Return 200 OK immediately. Never check dependencies.
Checking DB in liveness = pod restarts when DB is down = cascading failure.
For each dependency:
→ Check with timeout (1-2s)
→ Record healthy/unhealthy status
Return 503 if any critical dependency unhealthy
{
"status": "healthy|unhealthy",
"version": "1.2.3",
"dependencies": {
"database": "healthy",
"cache": "unhealthy: connection refused"
}
}
livenessProbe:
httpGet: { path: /health/live, port: 8080 }
periodSeconds: 10
failureThreshold: 3
readinessProbe:
httpGet: { path: /health/ready, port: 8080 }
periodSeconds: 5
failureThreshold: 3
startupProbe:
httpGet: { path: /health/startup, port: 8080 }
periodSeconds: 5
failureThreshold: 30 # 150s max startup
references/platforms/{platform}/health-checks.mdTrack cache hit rates, latency, and detect cache-related issues
Instrument database queries, connection pools, and detect N+1 queries
Capture errors with rich context for debugging and alerting
Plan backend observability using RED + USE + 4 Golden Signals + JTBD
Monitor message queues, job processing, and detect backpressure
Instrument HTTP/gRPC endpoints with distributed tracing and RED metrics