DevOps Engineer Interview Questions in India (2026)

DevOps Engineer is one of the most actively hired technical roles in India right now. Knok's job radar found 811 active openings as of July 2026, with Bangalore leading at 187 roles, followed by Delhi (40), Pune (37), Hyderabad (28), Chennai (13), and Mumbai (11). Salary bands that candidates commonly report range from 6-12 LPA for entry level (0-2 years), 15-28 LPA at mid level (3-5 years), 30-50 LPA for senior roles (6-9 years), and 45-70+ LPA for lead or staff positions.

Most Indian DevOps interviews follow a familiar pattern: a recruiter screening call, one or two technical rounds covering Linux, containers, CI/CD, and cloud, a scenario or system design round, and a final HR or behavioural round. Some companies add a live debugging task on a shared screen. This guide covers questions candidates commonly report across startups, product companies, and IT services firms, so you can prepare once and interview with confidence wherever you apply.

1. Design a rate limiter for an API serving millions of requests per day.
2. Explain a production incident you debugged. What was root cause?
3. How do you approach system design for high availability?
4. Walk through a code review where you caught a serious bug.
5. Trade-offs between SQL and NoSQL for a payments ledger.
6. How do you estimate task complexity for a sprint?

Three worked examples below. The behavioural answer uses the STAR format (Situation, Task, Action, Result).

Q: Describe a production incident you were involved in.

'Situation: Our main API started returning errors for a subset of users on a Friday evening. Task: I was the on-call engineer and owned the response. Action: I checked our Grafana dashboards and saw error rates climbing on one specific service. I pulled the recent deployment history in our CI/CD tool and found a config change had gone out two hours earlier. I rolled back the config through our IaC pipeline, confirmed error rates dropped, and wrote an incident summary for the team with a clear timeline. Result: Service was restored within about twenty minutes of my first alert, and we added a config validation step to the pipeline so the same class of error would be caught before reaching production.'

Q: What is the difference between a container and a virtual machine?

A VM runs a full guest operating system on top of a hypervisor. It is heavier in resource usage but offers strong isolation because each VM has its own kernel. A container shares the host OS kernel and isolates only the process and its dependencies, making it much lighter and faster to start. For most microservices in a cloud environment, containers are the right choice because of their speed and density. VMs are the better option when you need strict kernel-level isolation, for example when running untrusted third-party workloads.

Q: The team wants to significantly cut deployment time. How do you identify the bottleneck?

First, I instrument the pipeline and look at where time is actually being spent, not where I assume it is. Common culprits candidates report are slow test suites, large Docker image builds with no layer caching, or sequential pipeline stages that could run in parallel. Once I have data, I address the biggest bottleneck first. Then I remeasure before moving to the next one, so I know each change actually helped.

STAR for behavioural questions: 20% situation, 10% task, 50% action, 20% result with numbers.

CIRCLES for product cases (PM): Comprehend, Identify customer, Report needs, Cut through prioritisation, List solutions, Evaluate trade-offs, Summarise recommendation.

For system design (engineering): clarify scale (DAU, QPS), draw high-level boxes, deep-dive one component, discuss failure modes and monitoring.

Signals that move DevOps Engineer candidates forward in India:
- Ownership of outcomes, not tasks
- Comfort with ambiguity and incomplete data
- Collaboration with cross-functional partners
- Understanding of India-specific constraints (UPI, logistics, multilingual users, price sensitivity)
- Realistic salary expectations aligned with level

A four-week plan that works for most candidates targeting DevOps Engineer roles.

Week 1: Core foundations. Revise Linux fundamentals, Docker, and basic Kubernetes. Spin up a local cluster using kind or minikube and deploy a sample application end to end. The goal is being able to run, inspect, and debug a containerised app confidently from the command line.

Week 2: CI/CD and cloud. Build a small pipeline using GitHub Actions or Jenkins that lints, tests, builds a Docker image, and deploys it. Set up a Terraform project against a free-tier cloud account to provision basic infrastructure. Hands-on experience you can talk through is far more valuable than reading documentation.

Week 3: Scenario practice. Answer scenario questions out loud or in writing, as if you are in an interview. Deliberately break things in your local cluster (misconfigure a service, set wrong resource limits, delete a deployment) and practise debugging. This is the round most candidates underprepare for.

Week 4: Mock interviews and behavioural prep. Do mock interviews with a peer or on a platform like Pramp. Prepare two or three strong STAR stories for behavioural questions. Review the common mistakes listed in the next section before your first real interview.

• Rambling without a clear result metric
• Badmouthing previous employers
• Quoting global salary data without India context
• Ignoring the 'why this company' question
• Over-indexing on frameworks without showing real shipped work

Questions are grouped by theme below. Interviewers frequently mix these themes across rounds, so treat this as a study bank rather than a strict question order.

Fundamentals

1. What does DevOps mean to you, and how would you explain it to a non-technical stakeholder?
2. Describe a CI/CD pipeline you have built or maintained. Which tools did you choose and why?
3. What is the difference between a container and a virtual machine? When would you choose each?
4. How does Kubernetes manage rolling updates and rollbacks? Walk through the process step by step.
5. What is Infrastructure as Code and why does it matter? Which IaC tools have you used?
6. Explain the difference between blue-green deployments and canary releases. When is each the right choice?

Scenario-based

1. A production deployment breaks the application right after your push. Walk me through your debugging and recovery steps.
2. Your Kubernetes pods keep entering CrashLoopBackOff. What do you check first and why?
3. The team wants to significantly cut deployment time. How do you identify the bottleneck and fix it?
4. You need to set up monitoring for a new microservice from scratch. What do you instrument and which tools do you pick?

Behavioural

1. Tell me about a time you automated a manual process. What was the impact on your team?
2. Describe a production incident you were involved in. What did you do, and what did you change afterwards?

Focus your revision on the areas below. Depth on two or three areas impresses interviewers more than surface knowledge spread across everything.

CI/CD and automation: Jenkins, GitHub Actions, GitLab CI, ArgoCD, and GitOps principles. Know how to structure a pipeline from code commit to production deployment, including lint, test, build, and release stages.

Containers and Kubernetes: Docker internals (image layers, networking, volumes), core Kubernetes objects (pods, deployments, services, ingress, ConfigMaps, Secrets), horizontal pod autoscaling, and debugging with kubectl logs and kubectl describe.

Cloud platforms: AWS is the most commonly tested in Indian interviews. Prioritise EC2, EKS, RDS, S3, IAM, VPC, and CloudWatch. Awareness of GCP and Azure is a bonus at most companies.

Infrastructure as Code: Terraform is the standard. Understand how to write reusable modules, manage remote state, and handle drift. Ansible is commonly asked at companies with legacy on-prem infrastructure.

Monitoring and observability: Prometheus and Grafana for metrics, the ELK or EFK stack for centralised logging, distributed tracing concepts, and how to define and alert on SLOs.

Linux and scripting: Bash scripting, Python for automation, process and service management, common networking commands (curl, dig, netstat), and reading log files under pressure.

Security basics: Secrets management using Vault or AWS Secrets Manager, Kubernetes RBAC, container image scanning, and the principle of least privilege applied to IAM roles.

Git and branching strategy: Trunk-based development versus GitFlow, merge versus rebase, and how your branching model connects to your CI/CD pipeline design.

Knowing tool names without knowing the 'why'. Saying 'I use Kubernetes' without explaining what problem it solves or when you would not use it signals a shallow understanding to experienced interviewers.

Skipping behavioural preparation. Many candidates lose offers in the final round because they cannot tell a clear, structured story about past experience. Prepare at least two or three STAR answers before you walk in.

Vague answers to scenario questions. When asked to debug an incident, say exactly what you check, in what order, and why. 'I would look at the logs' is too vague. Name the command, the tool, and what you are looking for.

Leaving monitoring out of your answers. Any deployment or architecture answer that does not mention observability is a signal to experienced interviewers that you have not operated a system in production. Always address how you would know if something went wrong.

Not knowing your own resume in depth. Interviewers will probe any tool or project you have listed. If Terraform appears on your resume, expect questions about state management, modules, and how you handled drift or conflicts.

Ignoring cost awareness. Senior and lead roles increasingly test for cloud cost thinking. If you have made a cost-conscious architecture decision or reduced cloud spend at a previous job, mention it with context.

While you are in preparation mode, knok checks 150+ job sites nightly, applies to jobs that match your resume, and messages HR for you, so your applications keep moving even while you are focused on studying.