IntermediateSITUATIONAL
You’re on call and receive alerts that your main API’s p95 latency has suddenly doubled, but error rates look normal. What are the first three concrete things you check, and in what order? Explain the reasoning behind your investigation steps.
Backend Developer
General

Sample Answer

Situation: During a peak traffic window, our p95 latency on a Node.js/Express API jumped from ~180ms to ~400ms while error rates stayed <0.5%. Task: Quickly identify the bottleneck and restore SLA (<250ms p95) without causing downtime. Action: First, I check traffic patterns and recent deploys in Datadog/Grafana (RPS, instance CPU/memory, autoscaling events) to rule out overload or bad release. Second, I inspect per-endpoint latency and downstream dependency timings (PostgreSQL, Redis, external APIs) using APM traces to see where time is spent. Third, I examine database/query metrics (slow query log, connection pool saturation, lock waits). Result: In one incident, this sequence exposed a new unindexed filter causing 3× slower queries; adding an index brought p95 back to 190ms within 20 minutes.

Keywords

Check infra + deploys first: traffic spikes, autoscaling, recent releasesUse APM to localize latency to endpoint and downstream dependencyDrill into DB: slow queries, locks, connection pool metricsAim to restore SLA within minutes with minimal rollback scope
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