Behavioral: Improving a Production Service's Performance

Describe a challenging time you improved the performance of a production service.

Include the following:

1. Context
   • What the service does, who it serves, and why performance mattered.
   • The target metric(s): p99/p95 latency, throughput (RPS), error rate, CPU/memory, cost, etc.
2. Diagnosis
   • How you identified the bottleneck(s): metrics, logs, traces, profiling, experiments.
   • What tools and measurements you used.
3. Experiments and Changes
   • The experiments or measurements you ran to validate hypotheses.
   • The specific changes you implemented (e.g., caching, indexing, parallelization, connection pooling, GC tuning).
4. Impact (Before/After)
   • Quantified results on the target metric(s).
   • Any secondary effects (e.g., cost, reliability, resource usage).
5. Trade-offs and Risks
   • What you chose not to optimize, potential regressions you guarded against, and how you mitigated risk.
6. Learnings
   • Key takeaways, patterns, or playbooks you’d reuse.