System Reliability and Resilience

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.

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