TCS Incident Response & Production Debugging interview questions

The most-asked scenario question in DevOps interviews, and the one where candidates most often list commands instead of reasoning. Empty logs is the clue, not the obstacle.

The gentlest scheduling question there is, and it still separates people who read the events from people who guess. Check whether the pod has a node before choosing between scheduling and startup diagnosis.

Tests the mitigate-before-diagnose reflex under time pressure, plus whether you know the two ways a disk can be full and the trap that makes freed space not come back.

Automation can renew a certificate without deploying it correctly. Check the served leaf and chain, the client trust store and the exact verification failure.

An idle database with a starved application is the tell. The connections are held, not used. More database capacity does not release leaked connections.

Emergency mode after a storage change is usually one line in fstab. What interviewers score is your order of operations and whether your recovery preserves data-mount dependencies.

One saturated core on a proxy is rarely about raw traffic volume. It is a parallelism failure with three usual suspects, and the per-thread view names the culprit in minutes.

A hang suggests missing progress; a refusal suggests an explicit error. Packet evidence distinguishes firewall behavior from routing failures and closed listeners. Then rule counters, not eyeballs, finger the guilty line.

Everyone reaches for reinstall. The disciplined path is one journal file, four failure signatures, and an explicit decision about whether this host deserves surgery at all.

The reflex is rollback and it is usually right. There is exactly one class of failure where undo makes things worse, and knowing it is the entire interview.

An unchanged pipeline failing in one environment means the environment moved, not the code. Failures that start on an expiry boundary narrow the field to two suspects fast.

This one separates people who read journals from people who restart harder. The exit code and signal systemd already recorded usually name the disease.

Nothing errors because dropping unmatched lines is documented behaviour. Counting the tagged failures converts an invisible leak into a number, and numbers have owners.

Duplicate-IP claims need evidence, and one command provides it. Then the real skill: telling a genuine two-owner clash apart from ARP flux, because the fixes could not be more different.

Exit codes said green while the warehouse went hollow. Where detection should have sat, why retries could not help, and the backfill discipline finance will actually accept.

The pods are Running, the dashboard is green, and users get errors. The gap between Running and receiving traffic is where this question lives, and it has a precise answer.

A senior favourite, because the naive answer is to look at averages and the average is exactly what is hiding the problem. Tail latency has a short list of causes and they are all structural.

Tests whether you know that Kubernetes waits, and for how long. The default timings surprise most candidates, and they explain why a node failure hurts longer than people expect.

Intermittent DNS is the most-reported and least-understood Kubernetes failure. There are three well-known causes and each leaves a different fingerprint.

A deceptively deep question, because there are at least six places a version can get stuck and they span the pipeline, the cluster and the edge. Work the path in order.

Both can be right, which is the whole point. Retransmissions mean a segment was not acknowledged, and the network is only one of the places that can happen.