Build your base first — Linux, networking (DNS, TCP/IP, load balancers, firewalls), operating systems, and basic scripting — since most rounds test fundamentals before cloud-specific knowledge. Pick one platform and get hands-on: deploy a few projects, set up a small CI/CD pipeline, and practise troubleshooting deliberately. Revise the common themes (compute, storage, networking, IAM and security, cost optimization) and rehearse explaining concepts out loud instead of only reading. Do a few mock interviews under real time pressure, and align your resume so every project maps to something in the job description.

Go beyond definitions — interviewers expect you to explain when and why you would use EC2, S3, VPC, IAM, RDS, Lambda, and CloudFormation, and how you would keep workloads secure and cost-efficient. Study the AWS Well-Architected Framework pillars, because scenario questions are usually built around them. Set up a free-tier account and actually build something: launch an instance, configure a VPC, automate a deployment. Also prepare two or three real stories from your projects or work in the STAR format, since interviewers probe for hands-on depth rather than memorized answers.

Expect four buckets: core concepts (virtualization, storage types, networking, shared responsibility model), platform-specific services, troubleshooting scenarios like "a VM is unreachable — walk me through your steps," and DevOps basics such as Git, CI/CD, and Infrastructure as Code. Behavioural rounds usually cover on-call incidents, deadlines, and teamwork. The strongest way to answer is structured: state the concept in one line, explain how it works, then give a quick real-world example. Vague one-liners are the most common reason otherwise strong candidates get rejected.

Free PDFs and question banks are widely available on cloud learning sites, GitHub repos, and community study groups, and they work well for quick revision of frequently asked questions. The catch is that PDF-only preparation rarely succeeds for cloud roles, because interviewers follow up with "why" and "what if" questions that memorized answers do not survive. Use the PDF to shortlist topics, then practise each one hands-on and out loud. If you want realistic pressure, a mock interview with a working cloud engineer will teach you more than any static document.

Fresher rounds usually stay close to fundamentals: virtualization vs cloud computing, IaaS vs PaaS vs SaaS, basic Linux commands, networking basics like IP, DNS, and ports, storage types, and simple scripting tasks. You will almost certainly be asked about your academic or personal projects in detail, so be ready to explain what you built and why. A beginner-level certification such as AZ-900 or AWS Cloud Practitioner helps your resume get shortlisted, but interviewers care more about whether you can reason through a basic troubleshooting scenario. Fresher hiring is mostly about potential, so show genuine hands-on effort.

The focus shifts from definitions to judgment: designing architectures, migration strategy, cost optimization, security and compliance, and handling real production incidents. Expect deep dives into your past work — why you chose a design, what broke, what it cost, and what you would do differently. You may also face whiteboard or system design scenarios, such as building a highly available setup across regions, plus questions about mentoring juniors if the role is senior. Quantify your achievements — cost saved, uptime improved, deployment time reduced — because numbers carry real weight at this level.

The core set is fairly predictable: Linux and shell scripting, Git and branching strategies, CI/CD pipeline design, Docker and Kubernetes, one Infrastructure-as-Code tool (Terraform is the most common), a configuration management tool like Ansible, and monitoring with Prometheus or Grafana. Cloud platform knowledge in AWS, Azure, or GCP is expected alongside, since DevOps roles are rarely cloud-agnostic in practice. Scenario troubleshooting — a failing pipeline, a crashing pod, configuration drift — shows up in almost every experienced round. Be ready to explain the "why" behind each tool, not just what it does.

For freshers, interviews concentrate on foundations: Linux commands and permissions, Git basics like branching and pull requests, what CI/CD is and why it exists, Docker fundamentals such as images vs containers, and a high-level understanding of Kubernetes and one cloud platform. You may be asked to walk through a small project — even a self-built pipeline that deploys a simple app counts strongly in your favour. Recruiters in India also look for entry-level certifications or documented hands-on labs as proof of genuine interest. Keep answers simple and honest; overstating Kubernetes depth as a fresher usually backfires.

At three years, interviewers expect ownership: designing and maintaining CI/CD pipelines end to end, writing Terraform modules, debugging Kubernetes issues like CrashLoopBackOff or OOMKilled pods, managing secrets, and handling on-call incidents. You will get "how did you do this in your current role" questions, so prepare specific stories with metrics. Architecture discussions are common too — zero-downtime deployments, rollback strategies, improving deployment frequency, and cost optimization. Interviewers at this level also probe how independently you operate, so highlight decisions you made without being told.

These questions drop you into a situation: production is down after a deployment, pods keep restarting, a Terraform apply failed halfway, or the team wants faster releases without risking stability. Interviewers evaluate your thinking order — triage the impact, roll back or fix forward, communicate with stakeholders, then root-cause and prevent recurrence. Strong answers are calm and structured rather than tool-dumping. The best preparation is revisiting real incidents you have handled and narrating them clearly, because follow-up questions always drill into specifics.

They focus on the Azure DevOps suite: Azure Pipelines (classic vs YAML, agents, triggers, service connections), Azure Repos and branching policies, Azure Boards for work tracking, and Azure Artifacts for package feeds. Expect practical tasks like writing a YAML pipeline for build and deploy, setting up approvals and gates, integrating with Git, and troubleshooting agent or permission issues. General DevOps concepts such as CI/CD principles, Docker, and Infrastructure as Code are usually mixed in, since Azure DevOps is a toolset within the broader practice. Hands-on familiarity with the portal matters more than theory here.

The standard ladder is AZ-900 (Azure Fundamentals) for cloud basics, then AZ-104 (Azure Administrator) for core platform skills, and finally AZ-400 (DevOps Engineer Expert), which earns the DevOps Engineer Expert certification when paired with a prerequisite like AZ-104. If you come from a development background, AZ-204 (Azure Developer Associate) is a useful alternative stepping stone. Alongside AZ-400, make sure your GitHub Actions, Azure DevOps pipelines, and Terraform skills are genuinely hands-on, because the exam assumes practical experience. Skipping AZ-104 is technically possible but usually makes AZ-400 much harder.

The role-based structure remains the same: Fundamentals (AZ-900), then Associate level (AZ-104 for admins, AZ-204 for developers, AI-900 and AI-102 for AI tracks), then Expert and Specialty exams (AZ-305 for architects, AZ-400 for DevOps, plus security and networking specialties). Microsoft periodically retires and adds exams, so verify the current exam list on the official certification page before booking, since paths do shift from year to year. For DevOps aspirants, AZ-900 to AZ-104 to AZ-400 is still the cleanest route. AI-flavoured certifications are the fastest-growing area, but for core infrastructure and DevOps hiring in India, AZ-104 and AZ-400 carry the most weight.

AZ-900 (Microsoft Azure Fundamentals) is the best starting point for almost everyone — it covers cloud concepts, core Azure services, security, pricing, and support in a beginner-friendly way, with no hands-on experience required. There are entry alternatives like AI-900 if you already know you want the AI track, but AZ-900 remains the safest first certification because it aligns with admin, DevOps, and architecture paths alike. It is inexpensive and can be completed with a few weekends of focused study. Treat it as a stepping stone: pair it with hands-on labs and then move on to AZ-104 if you are serious about a cloud career.

The fee depends on the exam level. In India, fundamentals exams such as AZ-900 typically work out to roughly ₹3,700 including taxes, while associate and expert exams like AZ-104 or AZ-400 are generally priced around ₹4,800 plus GST per attempt. Microsoft revises pricing periodically and runs occasional offers, so confirm the current fee on the official exam pricing page before scheduling. Also budget for the possibility of a retake if you are attempting a role-based exam for the first time.