Delivering Reliable High-Performance Microservices
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11/4/2018
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One-minute read
- Design for Failure: Build redundancy, limit blast radius, and enforce timeouts/backoffs at every network boundary.
- Keep Services Cohesive: Align APIs to clear business capabilities to reduce cross-service chatter.
- Choose Fit-for-Purpose Protocols: gRPC or binary messaging can lower latency versus verbose HTTP payloads.
- Automation: Use CI/CD pipelines with progressive delivery (canaries, blue/green) to minimise deployment risk.
- Observability: Instrument latency, saturation, and error rates; provide log aggregation and distributed tracing from day one.
- Service Mesh / Orchestrators: Meshes (Istio, Linkerd) and orchestrators (Kubernetes, Nomad) add traffic management, mTLS, and auto-healing, but introduce operational overhead—adopt them deliberately.
- Load-test against realistic data and concurrency; monitor tail (p99/p999) latency, not just averages.
- Implement circuit breakers and bulkheads to prevent cascading outages when dependencies degrade.
- Co-locate services and data stores to minimise cross-region hops; understand trade-offs with redundancy requirements.
Incident Response
- Maintain runbooks with clear escalation paths and rollback strategies.
- Run regular game days to validate on-call readiness and ensure monitoring alerts trigger real responses.
- Capture post-incident learnings and feed them into design reviews and automation backlogs.
Continuous Improvement
- Track error budgets to balance reliability work against feature delivery.
- Treat security and compliance requirements as first-class constraints—embed scanning, policy checks, and audit logging into pipelines.