IntermediateBEHAVIORAL
Describe a time when a production backend issue impacted users (e.g., slow responses, errors, or downtime). How did you detect it, debug it, and prevent it from happening again?
Backend Developer
General

Sample Answer

At my last company, our checkout API suddenly spiked from a P95 of ~400ms to over 3s, and error rate hit about 6%, impacting a few thousand users in a morning. We caught it through a Datadog alert tied to latency, not customer tickets, which helped. I jumped into the logs and APM traces and saw all slow paths hitting a new promotion endpoint we’d just shipped behind a feature flag. The code was doing an extra unindexed join on a large orders table. Short term, we hot-fixed by bypassing that code path for low-value promos and rolled the feature flag back to 0%. That brought P95 back under 500ms within minutes. Then I worked with our DBA to add the right composite index, wrote a regression test around the query plan, and added a load-test step in CI. After that, similar issues dropped off, and we didn’t see another promo-related incident for the next 9 months.

Keywords

Proactive detection via monitoring/alerts, not just user complaintsClear debugging path using logs, traces, and recent changesImmediate mitigation plus longer-term fixes (indexes, tests, process)Concrete impact and recovery metrics
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