Top 100 DevOps Interview Questions & Answers (2026): Fresher to Senior
Quick Answer: This 100-question DevOps interview guide is split by experience level: Q1–40 for freshers cover concepts and tools (Git, Docker, Kubernetes, CI/CD); Q41–70 for 2–5 years test production scenarios (incidents, IaC, security); Q71–100 for senior roles probe architecture, cost, and team practices. Answers are reasoning-first, not memorised. This list is split by experience level – Q1–40 for freshers, Q41–70 for 2–5 years, Q71–100 for senior roles. Answer depth should match your level: at fresher stage, interviewers want clarity on concepts (what is DevOps, CI/CD, Docker basics); at mid-level, they test production scenarios (outages, rollbacks, IaC); at senior level, they probe architecture, cost, and people decisions. Source: CNCF Annual Survey 2024 for adoption context. This collection of top devops interview questions 2026 compiles devops interview questions and answers across three experience bands – devops interview questions for freshers, devops interview questions for experienced engineers, and senior scenarios – mapped directly to real devops interview preparation needs.
Key Facts at a Glance
| Parameter | Details |
| Fresher questions (0–2 yrs) | Q1–40 – concepts, tools overview, basic commands |
| Experienced questions (2–5 yrs) | Q41–70 – production scenarios, troubleshooting, IaC |
| Senior questions (5+ yrs) | Q71–100 – architecture, scale, cost, team practices |
| Most-asked tools | Git, Docker, Kubernetes, Jenkins, Terraform, Ansible, Prometheus |
| Most-asked clouds | AWS (dominant), Azure, GCP |
| What interviewers actually test | Reasoning + real-world experience, not memorised definitions |
| Red flag | Answers that sound like copy-paste from a tutorial with no ‘why’ or ‘when’ |
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How to Use This List
Go depth-first on your level band. Memorising all 100 answers is useless – interviewers rotate through 15–20 questions in 45 minutes and probe follow-ups. Better plan: pick 30 questions from your band, answer each out loud, record yourself, fix the answers that felt shaky. If you have no production experience yet, be honest. Saying ‘I have not run this in production, but here is how I would approach it in a staging lab…’ is far better than pretending. Interviewers hire for thinking, not bluffing.
Part 1 – Fresher Level (Q1–40)
Expectation at this level: concepts are clear, you can explain the CI/CD pipeline and Docker/Git basics, and you have built something small (a pipeline in Jenkins or GitHub Actions, a containerised app). No-one expects you to have run Kubernetes in production.
Q1. What is DevOps?
DevOps is a culture and set of practices that bring development and operations teams together to ship software faster and more reliably. The core levers are automation, continuous feedback, and shared ownership. For depth on the philosophy, see DevOps principles.
Q2. Why is DevOps needed?
Traditional dev vs ops silos lead to slow releases, blame cycles, and fragile deployments. DevOps reduces lead time, cuts deployment failures, and improves recovery time through automation and shared responsibility.
Q3. What is the DevOps lifecycle?
Plan → Code → Build → Test → Release → Deploy → Operate → Monitor, with feedback loops at every stage. Detailed breakdown: DevOps lifecycle.
Q4. What is CI/CD?
Continuous Integration merges code into a shared branch many times a day with automated tests. Continuous Delivery means every tested build is release-ready. Continuous Deployment pushes every passing build to production automatically. Full breakdown: what is CI/CD pipeline.
Q5. DevOps vs Agile – what’s the difference?
Agile is about how you build software iteratively. DevOps is about how you run and deliver it. Agile stops at ‘code merged’; DevOps continues through deploy and observe. Side by side: agile vs DevOps.
Q6. What is version control? Why use Git?
Version control tracks changes to code over time. Git is distributed, fast, branch-friendly, and the industry default. Every developer has a full history locally; remote platforms (GitHub, GitLab, Bitbucket) coordinate collaboration.
Q7. git merge vs git rebase?
Merge preserves history and creates a merge commit. Rebase rewrites history, producing a linear log. Rule of thumb: merge for shared branches, rebase for your local feature branch before opening a PR.
Q8. What is a Docker container?
A container is a lightweight, isolated process with its own filesystem, networking, and dependencies, running on the host OS kernel. It packages code + runtime + libs so the same image runs identically from laptop to production.
Q9. Docker image vs container?
An image is the immutable template (a recipe). A container is a running instance of that image. One image → many containers.
Q10. What is a Dockerfile?
A text file of instructions (FROM, RUN, COPY, CMD, etc.) that Docker reads to build an image step by step, cached layer by layer.
Q11. Docker vs VM?
VMs virtualise hardware – each has its own OS kernel, heavy, boots in minutes. Containers share the host kernel – lightweight, start in seconds. See virtualization in cloud computing for background.
Q12. What is Docker Compose?
A tool to define and run multi-container apps via a single docker-compose.yml file. One command (docker compose up) spins up your web app, DB, cache, and queue together.
Q13. What is Kubernetes?
Kubernetes (K8s) is an orchestrator for containerised apps – it schedules containers across a cluster of machines, keeps them running, handles rollouts, scaling, networking, and service discovery. Full primer: introduction to Kubernetes and containers.
Q14. Docker vs Kubernetes – are they rivals?
No. Docker builds and runs containers; Kubernetes orchestrates many of them. They are complementary. Comparison depth: difference between Docker and Kubernetes.
Q15. What is a Pod?
A Pod is Kubernetes’ smallest deployable unit – one or more tightly coupled containers sharing network and storage. Usually 1 container per Pod. Detail: what is a Pod in Kubernetes.
Q16. What is a Kubernetes Deployment?
A controller that manages ReplicaSets to run, scale, and roll out Pods. It handles rolling updates and rollbacks declaratively.
Q17. Kubernetes Service – what and why?
A stable network endpoint for a set of Pods. Types: ClusterIP (internal), NodePort (static port on each node), LoadBalancer (cloud LB), ExternalName (DNS alias).
Q18. Jenkins – what is it?
An open-source automation server for CI/CD. Pipelines are defined in Jenkinsfile (Groovy), triggered by SCM changes, and executed on agents. See our Jenkins interview list for depth.
Q19. Declarative vs scripted Jenkins pipelines?
Declarative pipelines use a structured pipeline { … } block – cleaner and easier to review. Scripted pipelines use full Groovy – more flexible but harder to maintain. Start declarative; drop to scripted only when necessary.
Q20. What is Infrastructure as Code?
Managing infrastructure via machine-readable config files (Terraform, Ansible, CloudFormation) stored in version control. You get repeatable, reviewable, rollback-friendly infrastructure.
Q21. Terraform vs Ansible?
Terraform provisions infrastructure (declarative, state-based). Ansible configures it (procedural, idempotent). In real teams you use both – Terraform for VMs/VPCs, Ansible for software inside them.
Q22. What is an Ansible playbook?
A YAML file describing tasks to run on target hosts in order. Full explainer: Ansible playbooks.
Q23. What is a CI/CD pipeline stage?
A logical grouping of steps – e.g., Checkout → Build → Unit Test → Security Scan → Deploy to Staging → Smoke Test → Deploy to Prod. Each stage can run in parallel or sequentially with approval gates.
Q24. Name five popular DevOps tools.
Git, Jenkins, Docker, Kubernetes, Terraform – minimum table-stakes. Add Prometheus + Grafana for monitoring. Broader list: DevOps tools.
Q25. What is a container registry?
Storage for container images – public (Docker Hub, ECR Public) or private (ECR, GCR, Harbor, Artifactory). Pipelines push built images; clusters pull them at deploy time.
Q26. What is blue-green deployment?
Two identical environments – Blue is live, Green is the new version. You switch traffic from Blue to Green once Green is healthy. Rollback = flip back. Uses more infra but offers instant rollback.
Q27. What is canary deployment?
Route a small percentage of traffic (say 5%) to the new version, observe metrics, increase gradually. Good for gating risky changes with real user signal.
Q28. Monolith vs microservices?
Monolith = one deployable unit – simple, fewer network hops, harder to scale a single feature. Microservices = many small services – independent deploys, language flexibility, more operational complexity.
Q29. What is monitoring vs observability?
Monitoring = are known metrics OK? (CPU, memory, error rate). Observability = can I debug unknown failures from outside the system using logs, metrics, and traces? Monitoring is a subset of observability.
Q30. What is the CAP theorem?
In a distributed system you can have at most two of: Consistency, Availability, Partition tolerance. Real systems choose between AP (Cassandra, DynamoDB) and CP (HBase, Zookeeper).
Q31. What is SSH and when do you use it?
Secure Shell – encrypted remote login and command execution. You use it to access Linux servers, tunnel ports, and run git over SSH. Always prefer key-based auth over passwords.
Q32. Crontab – what is it?
A Linux scheduler. Five time fields (min, hour, day-of-month, month, day-of-week) + the command. Used for backups, rotations, cleanup jobs. In containers, prefer Kubernetes CronJobs.
Q33. Linux commands a DevOps engineer uses daily?
ls, cd, grep, awk, sed, find, tail -f, ps, top, netstat/ss, df, du, journalctl, systemctl, curl, kubectl. Bonus: vim or nano for quick edits.
Q34. What is a systemd service?
A unit file describing how a daemon starts, restarts, and its dependencies. Managed with systemctl start/stop/status/enable. The modern Linux init system.
Q35. HTTP 2xx / 3xx / 4xx / 5xx – quick explanation?
2xx = success; 3xx = redirect; 4xx = client error (you); 5xx = server error (them). 404, 500, 502, 503, 504 are the ones you will see and debug most.
Q36. What is a load balancer?
A device/service that distributes incoming traffic across multiple backend instances for performance, HA, and health-based routing. Layer 4 (TCP) or Layer 7 (HTTP-aware). AWS ALB/NLB, Nginx, HAProxy are common.
Q37. What is DNS?
Domain Name System – maps human names (example.com) to IPs. Record types you should know: A, AAAA, CNAME, MX, TXT, NS. TTLs decide how long resolvers cache answers.
Q38. git pull vs git fetch?
fetch downloads remote changes without merging. pull = fetch + merge. Safer habit: fetch, inspect, then merge or rebase consciously.
Q39. How would you start learning DevOps from scratch today?
Linux basics → Git → one language (Python or Bash) → Docker → one cloud (AWS or Azure) → Terraform → CI/CD in GitHub Actions → Kubernetes last. Build one end-to-end project (web app + pipeline + IaC + monitoring) and put it on GitHub.
Q40. What questions should you ask the interviewer?
Ask about on-call expectations, typical deploy frequency, tech stack, and mentorship. Shows maturity and filters out toxic teams.
Part 2 – Experienced (2–5 Years) (Q41–70)
Expectation at this level: you can troubleshoot production, have opinions on tool choices backed by experience, and can describe incidents you have handled end-to-end. ‘In my last project…’ is the phrase interviewers wait to hear.
Q41. How do you debug a failing CI pipeline?
Reproduce locally if possible; check stage logs top-down; diff against the last green run; confirm env parity (versions, credentials, runners); check recent dependency or base-image updates. 80% of pipeline breaks are ‘something upstream changed’ rather than your code.
Q42. What is a rolling update and when can it go wrong?
Pods are replaced in batches while keeping the service available. It goes wrong when readiness probes lie (marked ready before actually ready), when DB migrations are not backward compatible, or when old and new versions cannot co-exist.
Q43. How do you handle database migrations in CI/CD?
Backward-compatible changes, deployed in two phases: expand (add new columns), deploy app to read both, contract (remove old columns in a later release). Tools: Flyway, Liquibase, Alembic. Never couple schema drop with app release.
Q44. Tell me about an incident you handled.
Pick one real incident. Describe: alert → triage → hypothesis → mitigation → root cause → action items. Interviewers want to see MTTR mindset, blameless post-mortem, and one thing you would do differently.
Q45. What is a good deployment frequency?
Depends on product risk. Elite performers (per DORA research) deploy multiple times a day. For regulated environments, weekly or biweekly with strong testing is healthy. Frequency without test coverage is reckless.
Q46. How do you secure a CI/CD pipeline?
Secrets in a vault (HashiCorp Vault, AWS SSM, GitHub OIDC to AWS – no long-lived keys). Least-privilege IAM for the runner. SAST/SCA on every PR. Signed commits and image signing (Cosign). Pipeline-as-code reviewed like app code.
Q47. Terraform state – how do you manage it?
Remote backend (S3 + DynamoDB lock, Terraform Cloud, GCS, or Azure Storage). Never commit state – it can contain secrets. State locking prevents concurrent apply collisions. One state per environment, not one giant state.
Q48. How do you structure Terraform for multi-environment?
Modules for reusable pieces. Separate tfvars or workspaces per env (dev/stage/prod). A thin ‘root’ module per env composes the shared modules. Promote via pipeline, not by hand.
Q49. Ansible – how do you handle secrets?
ansible-vault encrypt for files and strings. Store the vault password in a secret manager, never in git. For CI, pass the password via environment variable or a mounted secret. Better still, fetch secrets at runtime from Vault or AWS SSM.
Q50. Explain Docker multi-stage builds.
Multiple FROM lines – build stage has compilers/SDKs, final stage copies only the artifact into a slim base (distroless, alpine). Result: smaller image, fewer CVEs, faster pulls.
Q51. How would you reduce a 1GB Docker image to under 200MB?
Switch base to alpine/distroless. Multi-stage build. Remove build tools (apt remove, apk del). Combine RUN commands to reduce layers. .dockerignore to stop copying node_modules/.git. Use slim runtime images.
Q52. When to use Kubernetes and when not to?
Use when you have many services, need self-healing, horizontal scaling, or portability across clouds. Skip when you have 1–3 services and a small team – a managed service (ECS, Fargate, App Service) is less ops overhead.
Q53. Kubernetes liveness vs readiness probes?
Liveness: is the container alive? Failing → restart. Readiness: is it ready to serve traffic? Failing → remove from Service endpoints but don’t restart. Use startupProbe for slow-starting apps.
Q54. How do you handle secrets in Kubernetes?
Use external managers (AWS Secrets Manager + External Secrets Operator, Vault Agent Injector, Sealed Secrets). Base64 in a plain Secret object is not encryption – it’s encoding. Enable encryption-at-rest on etcd.
Q55. What is a Helm chart?
A package of Kubernetes manifests templated with values.yaml. Helm installs, upgrades, and rolls back charts. Common for third-party apps (Prometheus, Ingress-NGINX) and reusable internal deployments.
Q56. Prometheus + Grafana – how does it actually work?
Apps and exporters expose /metrics in Prometheus format. Prometheus scrapes at a fixed interval, stores time-series data. Alertmanager fires alerts based on PromQL. Grafana queries Prometheus and draws dashboards.
Q57. Explain the four golden signals of SRE.
Latency, Traffic, Errors, Saturation. Watching all four catches most outages early. See DevOps vs SRE for how SRE and DevOps overlap.
Q58. What is a feature flag?
A runtime toggle that lets you ship code to production dark, then enable it for a subset of users. Decouples deploy from release. Tools: LaunchDarkly, Flagsmith, Unleash.
Q59. GitOps – what is it?
Git as the single source of truth for declarative infrastructure and apps. A controller (Argo CD, Flux) reconciles cluster state to match the git repo. PR-based ops, strong audit trail, easy rollback via git revert.
Q60. How do you do cost optimisation on AWS?
Rightsize instances (use Compute Optimiser). Savings Plans / Reserved Instances for steady workloads. Spot for batch. Stop non-prod after hours. Tag everything and run monthly Cost Explorer reviews. S3 lifecycle rules, Intelligent-Tiering.
Q61. What is a distributed trace?
A record of a single request as it flows across services. Each hop is a span with timing and metadata. Tools: Jaeger, Tempo, Honeycomb. Essential for microservices debugging.
Q62. Immutable infrastructure – what and why?
Servers are never modified after creation; you replace, not patch. AMIs/container images baked in CI. Pros: reproducibility, fewer drift bugs. Cons: slower response to quick fixes.
Q63. Kubernetes Network Policy – what does it do?
Layer 3/4 firewall rules between Pods using labels. By default, K8s allows all Pod-to-Pod traffic – NetworkPolicies let you express ‘only frontend can talk to backend on port 8080.’ Requires a CNI that supports them (Calico, Cilium).
Q64. How do you handle logs at scale?
Structured JSON logs from apps. Node-level agent (Fluent Bit, Vector) ships to a central store – Elasticsearch, Loki, OpenSearch, or a SaaS like Datadog. Index only what you search; everything else goes to cheap object storage.
Q65. Disaster recovery – RTO and RPO?
RTO = how quickly you must restore service (recovery time). RPO = how much data loss is tolerable (recovery point). Multi-AZ covers most failures; multi-region with active-passive or active-active covers region loss.
Q66. Zero-downtime deploy for stateful services – how?
Backward-compatible schema changes. Rolling restart with readiness gates. For databases: read replicas, connection draining, blue-green with data replication, or managed failover (RDS, Aurora, Cloud SQL).
Q67. Trunk-based development vs GitFlow?
Trunk-based: short-lived branches, merge to main many times a day, feature flags for in-progress work. GitFlow: long-lived develop/release/hotfix branches. Modern DevOps favours trunk-based because it pairs with CI/CD cleanly.
Q68. What is chaos engineering?
Intentionally injecting failures (kill pods, cut network, drop a region) in controlled ways to validate resilience assumptions. Tools: Chaos Mesh, LitmusChaos, Gremlin. Start small and in non-prod.
Q69. How do you approach capacity planning?
Baseline current usage with percentile metrics (p95/p99). Forecast from product growth. Load-test to find knee-points. Reserve headroom of ~30% for traffic spikes. Revisit quarterly.
Q70. Walk me through your CI/CD pipeline end-to-end.
Describe: SCM trigger → lint/SAST → unit tests → build image → SCA/container scan → push to registry → deploy to staging → smoke and integration tests → manual approval gate (or auto) → canary in prod → full rollout → synthetic monitors. Call out where you have added real improvements.
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Part 3 – Senior / Architect (5+ Years) (Q71–100)
Expectation at this level: system design, cost vs reliability trade-offs, people and process, and a point of view on where DevOps is going. You have run production at scale and can talk about it plainly.
Q71. How would you design a CI/CD platform for 500 engineers?
Shared pipeline templates (golden paths), self-service onboarding, autoscaling runner pool, paved road for language stacks, centralised secrets and artifact stores, per-team cost visibility, and a platform team that treats it as an internal product with SLOs.
Q72. Multi-cluster vs single-cluster – how do you decide?
Multi-cluster when you need blast-radius isolation, regulatory boundaries (prod vs PCI), or geographic distribution. Single large cluster when you want simpler operations and efficient bin-packing. Most orgs land on 3–10 clusters per environment pattern.
Q73. Platform engineering vs DevOps – your take?
Platform engineering productises the DevOps paved road – self-service portals, golden templates, internal developer platforms (IDPs) like Backstage. DevOps is the culture, platform engineering is an implementation pattern that scales it without creating a ‘do everything for us’ ops bottleneck.
Q74. How do you measure DevOps success?
DORA four: deployment frequency, lead time for changes, change failure rate, time to restore. Add: availability SLOs vs error budgets, on-call pager load, developer satisfaction. Avoid vanity metrics like ‘number of deploys’ without quality.
Q75. Cost blew up 3x last quarter – how do you investigate?
Pull cost by tag/service. Find the delta service. Check traffic vs compute growth – is it usage or inefficiency? Look for data-transfer costs (cross-AZ, egress), idle reserved capacity, storage snapshots, log ingestion. Engage the top-spend service owner first.
Q76. Design a deployment strategy for a regulated bank.
Segregated duties (deployer ≠ approver), signed images, immutable audit log, change-advisory-board gates for prod, blue-green with automatic rollback, evidence capture for every release, DR drills quarterly. Tools matter less than auditability.
Q77. SRE org – embedded or centralised?
Embedded SREs per product team for deep domain knowledge. A small central platform/SRE team for shared services, incident coordination, and tooling. Hybrid beats pure centralisation at scale.
Q78. How do you handle an on-call rotation burnout?
Audit alert volume – delete noisy ones, tune thresholds. Track pages per shift; if >5 actionable per week, it is broken. Follow-the-sun rotation, compensation for after-hours, protected focus time next day. Page only on customer impact.
Q79. Kubernetes at scale – what breaks first?
etcd (write latency, snapshot size), API server rate limits, kubelet heartbeats, node-level resource pressure, secret propagation delays, and CNI IP exhaustion. Upgrade carefully – K8s control plane across large clusters is an operation in itself.
Q80. DevSecOps – what does it actually mean in practice?
Shift security left and continuous. SAST, SCA, secrets scanning on every PR. Container scanning at build. IaC scanning (Checkov, tfsec). Runtime threat detection (Falco). Policy-as-code (OPA). Security champions per team, not security as a gate at the end.
Q81. How would you architect an internal developer platform?
Backstage for the catalogue and docs. Self-service templates (scaffold a new service). Golden CI/CD pipelines. Managed infra abstractions (one YAML deploys a Cloud SQL instance with backups and monitoring). Platform team measured on adoption + developer satisfaction.
Q82. Service mesh – when is it worth it?
Worth it at 20+ services where you want mTLS by default, fine-grained traffic control, and rich observability for free. Not worth it at 3 services – complexity outweighs value. Istio, Linkerd, Cilium Service Mesh are the common choices.
Q83. How do you handle data privacy (GDPR/DPDP) in CI/CD?
No production data in non-prod – synthetic or masked instead. Secrets rotation with short TTLs. Audit every access to prod data. Data residency via region-pinned resources. Document the data flow – most audits fail on documentation, not controls.
Q84. Your microservices are chatty and slow – how do you fix it?
Trace first to confirm the hot path. Batch or coalesce calls. Add caching (edge, app-level, DB). Re-evaluate service boundaries – if A always calls B always calls C, merge them. Async via a queue where latency allows.
Q85. How do you manage a multi-cloud strategy?
Avoid accidental multi-cloud – it is 3x the operational cost. Deliberate multi-cloud only for regulatory, vendor leverage, or specific service strengths. Abstract via Terraform + Crossplane and Kubernetes. Accept that some services will remain cloud-native.
Q86. What is FinOps and where does it fit?
Operating model where engineering, finance, and product share cost accountability. Daily cost visibility per team. Unit economics (cost per request, per customer). Culture of cost-as-a-feature. Tools: AWS CUR, CloudHealth, Vantage, Finout.
Q87. How do you evaluate new tooling before adopting?
Problem first, not tool first. Define success criteria. Two-week bake-off with realistic scenarios, not the vendor’s demo. Consider total cost (licence + ops + training). Prefer open formats to avoid lock-in. Adopt, don’t integrate everything.
Q88. Your ops team resists automation – how do you lead change?
Ship a quick, obvious win together. Celebrate reclaimed time. Upskill instead of displace. Bring objectors into design from day one. Culture change is not top-down slides; it is pair-programming and patience.
Q89. How do you onboard a new engineer so they ship in week one?
Self-service env setup script. A curated ‘first PR’ task. Pair rotation for the first month. Documented golden paths. On-call shadow before primary. Measure time-to-first-commit and time-to-first-deploy as platform metrics.
Q90. What’s the hardest production issue you’ve debugged?
Pick a real one – preferably non-obvious. Structure: symptom → hypotheses tested → data that ruled things out → root cause → fix → follow-ups. Interviewers want reasoning, humility, and closure-through-post-mortem, not heroics.
Q91. How do you think about AI in DevOps workflows?
Useful today for: PR summarisation, runbook drafting, log anomaly triage, IaC generation. Still unreliable for: autonomous prod changes, security decisions. Treat AI as a senior pair, not an autopilot. Measure false-positive rates of AI-driven alerts or suggestions.
Q92. Design a zero-trust architecture on AWS.
Identity-aware proxy (AWS Verified Access, or OSS like Pomerium/Teleport). No flat VPC trust – workload identity per service (IAM Roles for Service Accounts on EKS). Signed requests, short-lived tokens. Device posture for humans. Network controls as a backstop, not the primary control.
Q93. Kubernetes version upgrade strategy across 50 clusters?
Standardise on 2 versions max in fleet. Upgrade non-prod first in waves of 5. Canary-upgrade prod by criticality. Use managed services (EKS, GKE, AKS) for control plane. Test CRDs and operators in staging for deprecated APIs before touching prod.
Q94. Your org wants to adopt serverless – how do you advise?
Great for event-driven, spiky workloads and glue code. Weak for long-running, high-throughput steady load (cost and cold starts). Factor cold starts, concurrency limits, observability gaps. Hybrid is normal – Lambda for edges, containers for the core.
Q95. How do you pick between Karpenter and Cluster Autoscaler?
Karpenter for faster, cost-aware node provisioning and workload-shape-aware choices. CAS for simpler, mature, multi-cloud coverage. Karpenter is the default on EKS today; GKE Autopilot and Azure’s node auto-provisioning are platform-specific alternatives.
Q96. What does ‘toil’ mean and how do you reduce it?
Toil = repetitive, manual work that scales linearly with service growth and has no lasting value. Measure time-on-toil (target <50%). Automate the most frequent tasks first. Every incident should produce either a fix or an automation, ideally both.
Q97. How do you handle a security vulnerability disclosed publicly?
Triage CVE severity and your real exposure (not every CVE applies). Mitigate with config if no patch available. Patch in staging, roll to prod on expedited change. Comm to leadership and customers if PII is involved. Post-mortem on how it got in (pinned base images, SCA coverage).
Q98. What is eBPF and why should a DevOps leader care?
eBPF lets you run safe programs in the kernel – enabling zero-instrumentation observability, security, and networking. Tools like Cilium, Pixie, Parca, and Tetragon give you metrics/traces without sidecars or code changes. It’s shifting how we observe and secure Linux at scale.
Q99. How do you stay current with DevOps?
CNCF landscape updates, DORA annual report, KubeCon talks, Thoughtworks Tech Radar, vendor blogs (read critically). Build a side project quarterly to keep hands dirty – reading without building produces shallow opinions.
Q100. Where do you see DevOps going in the next 3 years?
AI-assisted ops becoming normal, platform engineering as the default scale pattern, internal developer platforms getting real budget, FinOps maturing alongside DevOps, and security becoming indivisible from delivery. The name might fade; the practices embed deeper.
Red Flags Interviewers Notice
- Defining tools without explaining the problem they solve.
- Claiming production ownership without describing an actual incident.
- Naming the latest tool just because it is trending – with no trade-off awareness.
- Overusing ‘best practice’ without context for your team size and stage.
- Bluffing at the K8s deep end. If you haven’t run it, say so.
- Zero questions at the end of the interview.
How to Answer What You Don’t Know
Three good patterns: (1) ‘I haven’t used X, but the closest thing I’ve used is Y – the concept is the same, here’s how I’d approach it.’ (2) ‘I’ve read about X; I haven’t run it in production. The key trade-offs I’d want to validate are…’ (3) ‘That’s outside my experience. How does your team handle it?’ Redirection is better than invention.
Related Reading
- Azure DevOps interview questions and AWS DevOps interview questions for cloud-specific prep.
- Kubernetes interview questions for orchestration depth.
- Docker interview questions and Jenkins interview questions.
- Site Reliability Engineer interview questions for SRE crossover roles.
- DevOps engineer resume and how to become a DevOps engineer.
How Hero Vired’s PGP in DevOps Prepares You for These Questions
- Every core topic in this 100-question list is covered – Git, Docker, Kubernetes, Terraform, Jenkins, Prometheus, AWS, Azure, DevSecOps, observability, and Agentic AI in DevOps.
- Project-based learning – you build real pipelines, real clusters, real IaC, not slides.
- Mock interviews with faculty and industry practitioners.
- Capstone – a production-grade deployment you can demo on your laptop and talk about for 45 minutes.
- Alumni network and placement cell support across Hero Group’s partner companies.
The list in this blog gives you the map. The PGP in DevOps programme puts you in the territory.
Market Demand & Career Impact
DevOps is among the top 5 most-hired tech roles in India and continues to grow as enterprises migrate to cloud and adopt platform engineering. The role title mutates (DevOps Engineer → SRE → Platform Engineer → DevSecOps), but the underlying skills only deepen in value.
| Profile | Typical range (India) |
| Fresher with 1 cert + 1 project | INR 4–7 LPA |
| 2–3 yrs, strong fundamentals | INR 8–14 LPA |
| 4–6 yrs, K8s + IaC + multi-cloud | INR 16–28 LPA |
| 7+ yrs, architect / platform lead | INR 30–60+ LPA |
The differentiators that push candidates up the band are always the same four: production experience (or convincing lab equivalent), Kubernetes fluency, IaC proficiency, and comfort with at least two clouds. Certifications help with shortlisting; the projects and scenarios you can talk about determine the offer. The list above is structured the way actual devops interview preparation should be: clean devops interview questions and answers for freshers, production-grade depth for the experienced band, and scenario rounds for senior roles. Treat this as your reference for top devops interview questions 2026, bookmark the devops interview questions for experienced band if that is where you sit, and work through devops interview questions for freshers once before anything else if you are newer.
How many DevOps interview questions should I prepare?
Are dumps or leaked interview questions worth using?
Do I need certifications to crack DevOps interviews?
How long should a DevOps interview answer be?
What is the most common mistake candidates make?
How do I handle a question on a tool I have never used?
What salary can I expect after clearing a DevOps interview?
Is DevOps still a good career in 2026?
How many hours should I prepare for a DevOps interview?
Should I learn Terraform or Ansible first?
Can a fresher crack an SRE interview?
What are the most-asked DevOps tools in interviews?
Updated on April 29, 2026