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Microsoft Azure Well-Architected Framework - Reliability


Reliability is a foundational pillar when building resilient systems, especially for critical components. Outages and malfunctions pose serious risks to any workload, so a truly reliable system must be designed to detect, withstand, and recover from failures within an acceptable timeframe. It must ensure continued functionality and maintain availability so that users can access services as expected, both in terms of uptime and quality.

🔧 Aligned with Azure’s Reliability Checklist

  1. Keep it simple and efficient
    Strive for a solution that meets requirements without unnecessary complexity—simplicity simplifies reliability

  2. Identify and prioritize flows
    Map out user and system flows, assess their criticality, and focus engineering efforts on those with the highest business impact

  3. Conduct failure mode analysis (FMA)
    Investigate every dependency and component with a methodical FMA to uncover weak points, and design mitigation strategies accordingly

  4. Define clear reliability and recovery targets
    Establish specific SLOs, RTOs, RPOs, MTBF, MTTR for each critical flow—use these metrics to guide architecture and health models

  5. Build redundancy at every layer
    Enable failover by replicating compute, network, and data; deploy across zones/regions or use active‑active/passive setups to meet availability goals 

  6. Implement scalable and automated strategies
    Use autoscaling tied to real usage patterns and predictive loads to avoid bottlenecks or resource exhaustion 

  7. Enable self-preservation and self-healing
    Integrate cloud-native resilience patterns—bulkheads, circuit breakers, deployment stamps—and automate recovery when faults occur 

  8. Test resiliency actively (chaos engineering)
    Simulate failures, load spikes, and degradation scenarios to validate graceful degradation and healing mechanisms

  9. Maintain comprehensive BCDR plans
    Document, routinely test, and align business continuity and disaster recovery procedures with recovery metrics

  10. Monitor health continuously
    Build a health model for both individual components and end‑to‑end flows. Capture telemetry, logs, traces, uptime, and alerts on state transitions so operations can respond instantly

Building truly reliable systems is foundational for critical workloads, ensuring they can withstand and recover from failures to maintain continuous availability and service quality. This is achieved through a systematic approach that includes defining clear recovery targets, implementing redundancy and automated scaling, and actively testing for resilience. Ultimately, a reliable system is one that is proactively designed to be simple, self-healing, and continuously monitored, ensuring it can respond effectively to any challenge.

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