DevOps Interview Questions for Indian Engineers 2026

CI/CD is the foundation of DevOps and is tested at every level. Continuous Integration: automatically building and testing code on every commit. Continuous Delivery: automatically deploying to staging environments; manual gate before production. Continuous Deployment: automatically deploying to production. Tools: Jenkins (most common at Indian enterprise), GitHub Actions (most common at product companies and startups), GitLab CI, CircleCI, Azure DevOps. Pipeline stages: Lint and code quality check (ESLint, SonarQube), Unit tests, Integration tests, Build (Docker image), Push to registry (ECR, GCR, Docker Hub), Deploy to staging, E2E tests, Manual approval gate, Deploy to production. Blue-green deployment and canary releases: zero-downtime deployment strategies: expected knowledge at senior DevOps level.

Docker is foundational: tested in almost every DevOps interview. Core concepts: Image vs container (image is blueprint, container is running instance). Dockerfile: FROM (base image), RUN (execute during build), COPY/ADD (add files), ENV (environment variables), EXPOSE (document port), CMD/ENTRYPOINT (run on container start). Multi-stage builds: separate build and runtime images to reduce final image size. Docker Compose: multi-container applications, service dependencies, volumes, networks. Docker networking: bridge (default, container-to-container on same host), host (container uses host network), overlay (multi-host Swarm). Volume types: bind mounts vs named volumes. Best practices: don't run as root, minimise layers, use .dockerignore.

Kubernetes is the dominant container orchestration platform: heavily tested at senior DevOps and SRE roles. Core objects: Pod (smallest deployable unit: one or more containers), Deployment (manages ReplicaSet, rolling updates), Service (stable network endpoint: ClusterIP, NodePort, LoadBalancer), ConfigMap (non-sensitive config), Secret (sensitive config, base64 encoded), Namespace (logical cluster separation). Ingress: routing external HTTP/HTTPS traffic to services. HPA (Horizontal Pod Autoscaler): scales pods based on CPU/memory metrics. PVC/PV: persistent storage. Rolling updates and rollbacks: kubectl rollout history, rollout undo. Common interview scenario: a deployment is not starting: how do you debug? kubectl describe pod, kubectl logs, kubectl get events.

Terraform: the dominant IaC tool in Indian cloud DevOps roles. Core concepts: providers (AWS, GCP, Azure), resources, data sources, variables, outputs, state file (terraform.tfstate), remote state (S3 backend + DynamoDB for locking), modules (reusable Terraform code). Terraform commands: init, plan, apply, destroy, import. Ansible: configuration management and agentless automation via SSH, YAML playbooks, roles. Monitoring stack: Prometheus (metrics collection, PromQL), Grafana (dashboards), Alertmanager (alert routing). ELK/EFK stack: Elasticsearch (storage), Logstash/Fluentd (ingestion), Kibana (visualisation). SLI, SLO, SLA: Service Level Indicators (what you measure), Objectives (targets), Agreements (contractual). Error budgets: 99.9% SLO leaves 8.7 hours/year of downtime budget.

DevOps and platform engineering is among the fastest-growing high-compensation tracks in Indian tech. Junior DevOps engineers at IT services firms earn 5 to 9 LPA, while those at funded startups with hands-on Kubernetes and Terraform experience earn 14 to 22 LPA at the same experience level. Senior SREs and platform engineers at Razorpay, PhonePe, or Freshworks earn 30 to 50 LPA. Principal-level roles at hyperscaler India offices such as AWS, Google Cloud, or Microsoft Azure Bengaluru reach 70 to 100 LPA with stock. Specialisations in FinOps, GitOps, or security engineering consistently attract 15 to 25 percent premiums above general DevOps roles across Indian hiring markets.

Razorpay's platform team conducts a live debugging exercise where candidates are given a broken Kubernetes YAML manifest or a failing Helm chart and must diagnose the issue on screen. Freshworks focuses on observability, asking candidates to design a Prometheus and Grafana alerting stack for a multi-tenant SaaS product. Ola and Rapido assess candidates on autoscaling strategies given traffic surge patterns common during Indian peak events like IPL or Diwali sales. Many Indian unicorns use a take-home infrastructure challenge requiring candidates to provision a complete environment using Terraform on AWS. Understanding Spot instance management and cost optimisation on AWS or GCP is considered mandatory knowledge at most Indian product-stage companies.

Indian engineering teams adopted GitOps practices rapidly through 2024 and 2025, with ArgoCD and Flux becoming standard tooling at companies like Zepto, Meesho, and BharatPe. Interviewers now routinely ask candidates to explain the difference between push-based and pull-based deployment models and to describe how they would structure a GitOps repository for a mono-repo with 20 microservices. Internal developer platforms built on Backstage are gaining traction at larger Indian engineering organisations. Candidates should also expect questions on multi-cluster Kubernetes federation, service mesh implementations using Istio or Linkerd, and how to manage secrets securely using HashiCorp Vault or AWS Secrets Manager in regulated environments such as fintech or healthtech.