Problem-first architecture: clarify read vs. write volumes, acceptable latency bounds, consistency requirements, and SLA invariants before choosing components.
System Design & Architecture
Design for the messy reality of distributed failure.
System design is not an abstract architecture diagram competition. It is the practical discipline of understanding real-world constraints, failure modes, data flows, operational cost, and concrete system guarantees.
Design for inevitable failure: network partitions, timeouts, duplicate requests, stale cache hits, cascading retries, and database failovers are normal states.
Explicit messaging semantics: understand the exact trade-offs between message queues (point-to-point, task distribution) and event streams (immutable logs, pub/sub replay).
Observability as an architectural pillar: end-to-end distributed tracing, high-cardinality metrics, structured logs, and proactive circuit breakers.
Simplicity over premature complexity: start monolithic or modular, profile bottlenecks with telemetry, and extract distributed services only when required by scale.
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