DevOps engineers touch uptime, security, and cloud spend at once, so a bad hire is expensive in three directions. These questions focus on production judgment — pipelines, Kubernetes, incidents, and cost — with notes on what a strong answer covers so you can grade without running infrastructure yourself.
What a strong answer covers
Build, automated tests, security and dependency scanning, artifact versioning, staged deployment with automated rollback criteria. Strong answers keep pipelines fast, make main always releasable, and are explicit about which gates are blocking versus advisory.
What a strong answer covers
Rolling as the cheap default, blue-green for instant rollback at the cost of double capacity, canary for risk-managed exposure with real traffic and automated analysis. The senior marker is tying the choice to blast radius, statefulness, and how fast a bad release can be detected.
What a strong answer covers
Ingress or load balancer, Service routing to endpoints, kube-proxy or eBPF-based forwarding, pod selection, readiness gates deciding membership. Precision here separates people who operate Kubernetes from people who deploy to one someone else runs.
What a strong answer covers
kubectl describe for events, logs including the previous container's, exit codes (OOMKilled versus application error), probe misconfiguration, config and secret mounts, image and dependency issues. A crisp, ordered checklist reveals real operational hours.
What a strong answer covers
Reusable modules with per-environment configuration, remote state with locking, workspaces or directory-per-environment with the trade-offs named, plan review in pull requests, and CI-driven applies. Ask how they have handled state surgery — the wince is informative.
What a strong answer covers
Declared desired state in Git, an operator like Argo CD or Flux reconciling the cluster to it, drift detection, and audit-by-pull-request. Honest answers also name the costs: secret handling complexity and the learning curve for emergency changes.
What a strong answer covers
Acknowledge and communicate, check what changed (deploys, flags, infra events), assess scope from dashboards, mitigate first — rollback, scale, failover — and investigate root cause after service is restored. Mitigation-before-diagnosis is the professional reflex you are testing for.
What a strong answer covers
Blameless framing, an accurate timeline, contributing factors over a single root cause, and action items with owners that actually reduce recurrence. Useless versions: blame theater, action items nobody tracks, or reviews only for severe incidents.
What a strong answer covers
Symptom-based alerting on user-facing SLOs rather than every CPU blip, burn-rate alerts, runbooks attached to pages, and ruthless deletion of non-actionable alerts. SLO and error-budget vocabulary used correctly is a strong positive.
What a strong answer covers
Specifics: right-sizing from utilization data, spot capacity for tolerant workloads, storage lifecycle policies, NAT and cross-AZ traffic, orphaned resources. Sustained control needs tagging, per-team visibility, and budgets in CI — cost as a continuous practice, not a one-off audit.
What a strong answer covers
A real secret store (Vault, cloud-native managers), short-lived credentials and OIDC federation for CI rather than long-lived keys, rotation, and least privilege. Plaintext secrets in CI variables without scoping, or in Git history, should make them visibly uncomfortable.
What a strong answer covers
Containerized parity, config via environment with schema validation, seeded data and service dependencies via compose or ephemeral environments, and the same artifact promoted across environments rather than rebuilt. Preview environments per pull request is a modern bonus.
What a strong answer covers
Nuanced, not absolutist: broad read access to logs and dashboards, break-glass write access with audit trails, and paved-path tooling so production changes flow through pipelines. Pure gatekeeping and pure free-for-all are both wrong answers.
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Try the interview question generator →The center of gravity moves from code design to operational judgment: incidents, pipelines, infrastructure state, and cost. A strong DevOps candidate may write less application code but should dominate the 2 a.m. scenario and the monitoring questions.
CI/CD design, the local-versus-staging question, secrets, and cost. A first hire builds paved roads for a small team; deep Kubernetes internals matter less than the judgment to keep things simple.
A review exercise: hand them a flawed pipeline definition or Kubernetes manifest with planted issues — no resource limits, a secret in plaintext, a missing readiness probe — and ask for a prioritized critique. It mirrors the review work they will actually do.
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