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mediumDevOps Engineer interview question

Users report that one service on Kubernetes became slow since this morning. Walk me through how you would investigate.

What the interviewer wants to hear

  • Confirm impact and scope with latency metrics and SLO dashboards
  • Check recent changes: deploys, config, node or cluster events
  • Use traces to find which span or dependency is slow
  • Check resources: CPU throttling, memory, restarts, node pressure
  • Check dependencies such as database, DNS and network
  • Mitigate first, for example rollback or scale, then find root cause

Model answer

First I confirm and size the problem: which endpoints are slow, from what percentile, since when, and for which users, using latency histograms and the SLO dashboard. Next I look at what changed around that time: deploys, config or feature flag changes, node upgrades, autoscaling events. If a deploy lines up and impact is serious, I roll back first and investigate after. To locate the slowness I open traces for slow requests and see which span grows, for example a database query, an external API or time spent in the service itself. Then I check the Pods: CPU throttling, memory near limits, restarts, garbage collection, and whether they are spread across healthy nodes. I also check dependencies such as database load and connection pools, DNS latency and network errors. Once service is stable, I write up the cause and add an alert or dashboard that would have caught it sooner.

Can you answer it under time pressure?

Take a timed medium round and get scored on every answer.

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