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.
Related
- Architecture – Observable, testable system design
- Technical Debt – How deferred maintenance compounds
- DevOps – Measurable flow and reproducible delivery

AKS Disaster Recovery: Why Your Untested Backup Will Fail
Your cluster will fail. The question is not if, but when, and whether you can recover before customers notice. Most organizations discover their backup strategy does not work during an actual outage, when recovery time matters most and manual heroics cannot save you.
If you run Azure Kubernetes Service (AKS) in production, you need a recovery plan that engineers can execute half asleep at 2 AM. We will go through what to back up, how Velero works in day-to-day operations, when Azure Backup for AKS is enough, and how to design realistic failover with measurable Recovery Time Objective (RTO) and Recovery Point Objective (RPO).
The goal is simple: repeatable recovery procedures you have already tested, not a document that looks good in Confluence but fails during an incident.

Storage Architecture & Stateful Workloads in AKS

AKS Cluster Upgrades: Zero-Downtime Operations That Actually Work
