Sample Answer
When our Spring Boot service started failing under 800 req/s after a deploy, I first rolled back to confirm the deploy was the trigger and observed error rate drop from 4% to 0.2%. Next I checked deployment logs and app startup metrics in Prometheus: CPU, heap, GC pause times, and thread pool saturation — the GC pause jumped 200ms under load. Third, I looked at application logs (structured JSON in ELK) for stack traces and saw connection pool timeouts. Fourth, I examined downstream latency graphs (Postgres and Redis) and found DB p99 spiked 3x. Fifth, I ran a focused load test against staging with profiling enabled and reproduced the thread contention tied to a synchronous batch call; I then implemented async batching and increased DB pool from 20 to 50, which brought error rate back under 0.5% and reduced p99 by ~40%.
Keywords
On your resume you mention working on a cross-functional project (e.g., involving multiple teams or stakeholders). Describe a situation from that project where priorities conflicted—how did you navigate the trade-offs and what was the final outcome?
Walk me through a recent multi-channel digital marketing campaign you managed end-to-end. How did you set objectives, choose channels, allocate budget, and measure success?
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Based on your hydrology and irrigation engineering background, explain how you would estimate the irrigation water requirement for a kharif crop in a semi-arid region of Gujarat. Walk me through each step: from reference evapotranspiration estimation, crop coefficient selection, effective rainfall calculation, to arriving at canal discharge for a given command area.