Cloudflare Incident Response & Production Debugging interview questions

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

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.

The classic gap between what the backend measures and what the user experiences. A 504 is emitted by something in front of the backend, which is exactly the part your service dashboards do not cover.

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

Established traffic keeps working while new connections die at random, which is exactly why this one confuses people. The table is full of flows that will not be needed again for days.

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.

Gradual drift produces no errors on the host that has it, only weirdness everywhere else. Sweep first, histogram second, repair third: the distribution shape names the culprit before you log into anything.

Mixed resolution after a transfer is not propagation voodoo. Compare the parent delegation, authoritative answers and validation results. NXDOMAIN and SERVFAIL are clues; neither names a unique cause.

Purges act on exact cache keys, and the edge is full of variants the purge never named. Verify per variant at real POPs, then fix the key model instead of chasing URLs forever.

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.

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.

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.

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.

Low utilisation with terrible tail latency is not a contradiction. It is the CFS quota doing exactly what it was configured to do. Most candidates have never read nr_throttled.

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

A two-second dependency should cost you latency, not three services. The mechanics are arithmetic: Little's law plus retry amplification. The fix is a budget, not a ban.

Repeated action items are a measurable defect with a mechanical cause. Candidates who answer 'culture' without a mechanism are describing the symptom back to you.

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 disk metric explaining a whole cluster's weirdness is the point of this question. Candidates who restart etcd first turn a slow cluster into a down one.

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.