Production Best Practices
Every earlier module built or hardened one piece correctly in isolation. This module is the checklist for whether they're ALL actually turned on together before real users depend on this service.
Learning objectives
- Beginner: Run through a production-readiness checklist against a real Spring Boot service.
- Intermediate: Identify which of this course's modules a given production incident traces back to.
- Advanced: Prioritize which production-hardening gaps to fix first when several are missing at once.
| Concern | Covered in | Common mistake if skipped |
|---|---|---|
| Structured logging + correlation IDs | Module 22 | Impossible to trace one request across log noise |
| Actuator health/metrics exposed and secured | Module 27 | Kubernetes can't tell if a pod is actually healthy |
| Connection pool sized for real load | Module 29 | Intermittent slowness under concurrent traffic |
| N+1 queries eliminated | Module 09 | Response time scales badly with data growth |
| Secrets out of source control | Spring AI category, Module 18 | A leaked API key or database password |
| Transactions correctly scoped | Module 23 | Partial writes on failure, silent data corruption |
| Rate limiting on public endpoints | DevOps Mastery — Kubernetes | One abusive client can degrade service for everyone |
◆ The problem
When Kubernetes replaces a pod during a deployment, it sends a termination signal and expects the process to exit soon after — a service that hard-kills in-flight requests instead of finishing them produces user-visible errors on every single deployment, forever, as a matter of routine.
server.shutdown=graceful spring.lifecycle.timeout-per-shutdown-phase=30s
This tells the embedded server to stop accepting NEW requests immediately on shutdown signal, while letting already-in-flight requests finish within the configured timeout — the difference between deployments being invisible to users and deployments causing a small wave of errors every single time.
Module 05's profiles mechanism exists precisely for this: a production deployment needs a different database URL, different log levels, different external API endpoints, and different feature flags than a local or staging environment — encoding these as application-prod.properties (not scattered if checks in code) keeps environment-specific behavior in configuration, where it's visible and auditable, not buried in logic.
✓ Quick recap
- Production readiness isn't one new mechanic — it's confirming every earlier module's hardening is actually turned ON together.
- Graceful shutdown prevents in-flight requests from being killed mid-response on every routine deployment.
- Environment-specific configuration belongs in profile-specific properties files, not conditional logic in code.
- When several gaps exist at once, prioritize by blast radius: data-corruption risks (transactions, N+1 under load) before cosmetic ones (log format).
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