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