IntermediateBEHAVIORAL
Tell me about a production incident where you were on the hook to debug a critical backend failure (e.g., 5xx spike, data inconsistency, or outage). What specific debugging steps and tools did you use, and what did you change to prevent recurrence?
Backend Developer
General

Sample Answer

At a fintech startup, our payments service saw a sudden 8x spike in 5xx errors, blocking ~30% of card transactions over 20 minutes. As on-call backend engineer, I needed to restore service and protect data integrity. I first checked Grafana dashboards and Kubernetes pod logs, then used Kibana to correlate 5xxs with a recent deployment. Tracing via Jaeger showed timeouts on a downstream fraud-check gRPC call. I rolled back, put the service in partial-degraded mode with a circuit breaker (Resilience4j), and reprocessed failed messages from a Kafka DLQ. Post-mortem, I added request-level timeouts, bulkheads, and a read-only cache for fraud rules, plus SLO-based alerts on error rate and p95 latency. Result: reduced similar 5xx incidents by 90% over 6 months and cut mean time to recovery from 25 to 8 minutes.

Keywords

Used observability stack (Grafana, Kibana, Jaeger) to localize the fault quicklyApplied safe rollback and circuit breaker to restore partial serviceReprocessed failed messages from Kafka DLQ to avoid data lossImplemented timeouts, bulkheads, and SLO-based alerting to prevent recurrence
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