System reliability isn’t about avoiding failures—it’s about making them visible and recoverable before they become catastrophic.
Green metrics hide decay. A service running for months without restart appears stable until failures surface under load. Long-lived state accumulates: memory fragmentation, stale caches, configuration drift, dead task loops. Good reliability practices force systems to prove they’re healthy through intentional disruption.
Key Practices
Regular Restarts: Every 24-72 hours, services restart and prove they can start cleanly. Dead loops surface. Configuration mismatches become visible. Memory resets.
Startup Validation: Systems answer three questions on boot: Can you read config? Connect to the database? Reach critical services? Failure blocks traffic—problems are discovered during planned restarts, not production outages.
Reproducibility: Configuration lives in code and version control, not SSH sessions. Infrastructure is rebuilt from scratch in minutes, not days.
Bounded State: Explicit TTLs (Time-To-Live) on caches and connections. Hours, not months. Stale assumptions expire automatically.
Reliability isn’t heroic recovery. It’s boring practices that catch problems early.
Related
- Architecture – Observable, testable system design
- Technical Debt – How deferred maintenance compounds
- DevOps – Measurable flow and reproducible delivery
