DevOps Interview Questions and Answers for 2025 – Beginners to Advanced | JaganInfo

DevOps is a set of practices that combines software development and IT operations to shorten development lifecycles and deliver high-quality software continuously.

Faster delivery, improved collaboration, higher deployment frequency, quicker recovery from failures, and better product quality.

Continuous Integration is merging code changes frequently; Continuous Delivery/Deployment automates testing and release of code to production.

Git, Jenkins, Docker, Kubernetes, Ansible, Puppet, Chef, Nagios, Prometheus, Terraform.

Packaging applications and dependencies together for consistent execution across environments; Docker is widely used.

Managing infrastructure through code and automation instead of manual setup; tools include Terraform and CloudFormation.

Tracking and managing source code changes over time; Git is most popular.

An open-source automation server to build CI/CD pipelines automating builds, tests, and deployments.

Integration of security practices into the DevOps lifecycle for continuous security and compliance.

An architectural style that structures applications as small, independent services that communicate over APIs.

Continuous Delivery prepares code for release and involves manual approval; Continuous Deployment automates release to production without manual intervention.

Using Jenkinsfile, define stages like build, test, and deploy to automate CI/CD workflows.

Docker containers share the host OS and are lightweight; VMs run full OS instances and use more resources.

Open-source container orchestration platform automating deployment, scaling, and management of containerized applications.

Liveness probes check if containers are running; readiness probes check if containers can receive traffic, enabling load balancer management.

Deploy new code to idle environment, then switch traffic over, reducing downtime and deployment risk.

Gradual release of new features to a small user segment before full rollout, enabling monitoring and rollback.

Collecting, analyzing, and reacting to metrics and logs for system health and performance.

Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana), Nagios, Splunk.

Automating configuration and maintenance of systems using tools like Ansible, Puppet, Chef.

Use version control, modular templates, testing, and automated deployments for infrastructure management.

Distributing network or application traffic across multiple servers to ensure reliability and performance.

Managing lifecycle, scaling, networking, and availability of containers across clusters.

Tools such as HashiCorp Vault, AWS Secrets Manager securely store and manage sensitive data like credentials.

Using Git as the source of truth for declarative infrastructure and application delivery automation.

Kubernetes package manager for managing complex applications with charts and templates.

Stateful apps maintain client state on server; stateless do not, enabling easier scaling and resilience.

Role-Based Access Control restricts user and service permissions to resources for security.

Containers that run alongside main app containers to provide utility or helper services.

Practice of introducing failures in production to improve system resilience and reliability.

Infrastructure components are replaced rather than modified, improving reliability and rollback capabilities.

A dedicated infrastructure layer to manage service-to-service communications, security, and observability in microservices.

Provides insights into system behavior through metrics, logs, and tracing to diagnose and fix issues effectively.

Deploying new versions to a small subset of users first to validate and minimize risks before full rollout.

Using Horizontal Pod Autoscaler, Kubernetes adjusts the number of pods based on CPU/memory usage or custom metrics.

Securing pipelines prevents unauthorized code changes, protects secrets, and ensures trusted deployments.

Strategies like Git Flow, trunk-based development manage code development and release cycles effectively.

By running two identical environments and switching traffic from blue to green to minimize downtime and risk.

Custom controllers that extend Kubernetes functionality to manage complex stateful applications.

Cultural shift, tool integration, legacy system compatibility, security, and continuous learning are major challenges.

Configuration drift happens when environments diverge; prevention includes IaC, automated compliance checks, and consistent deployments.

Secrets management tools store and encrypt sensitive data such as passwords, keys, and certificates securely in pipelines.

Monitoring the performance and errors of canary deployments to decide if they are safe for full rollout.

Stateless services do not retain client state between requests; stateful services maintain state, requiring persistent storage.

Services are assigned DNS names; kube-proxy routes requests to healthy pods automatically.

Designing services to be loosely coupled, independently deployable, and stateless where possible with auto-scaling.

Vault provides secure secret storage, dynamic secrets, and encryption-as-a-service to protect sensitive information.

Audit logs help track changes, detect breaches, and meet compliance requirements.

Feature flags enable toggling features on/off without deployments, facilitating canary releases and A/B testing.

Challenges include diverse APIs, security models, cost management, and integration complexity.