You’ve memorized what CI/CD stands for. You can recite the difference between Docker and virtual machines. You’ve read through 100+ question listicles until your eyes glazed over.

Then you sit down for an actual DevOps interview, and the first question is: “Tell me about a time a deployment went wrong and how you handled it.”

Here’s the uncomfortable truth about DevOps interviews in 2026: the questions you’ve been studying aren’t the questions that get asked. Most interview prep content is written by people who haven’t hired anyone in years, recycling the same theoretical questions that stopped being useful when DevOps went mainstream.

What actually happens in modern DevOps interviews is different. Hiring managers want to understand how you think, not whether you’ve memorized definitions. They want to see if you can troubleshoot under pressure, explain technical concepts clearly, and admit what you don’t know.

This guide covers the questions that actually show up—organized by what they’re really testing—along with the reasoning behind strong answers. If you’re transitioning from sysadmin to DevOps or coming from a cloud engineering background, the interview format might surprise you.

What DevOps Interviews Actually Test

Before diving into specific questions, understand what’s happening on the other side of the table.

According to Workable’s research on DevOps hiring, interviews are designed to test three distinct areas:

Technical depth. Can you actually do the work? This isn’t about tool memorization—it’s about understanding why tools exist and when to use them. Interviewers ask about Docker not because they care if you know the commands, but because your answer reveals whether you understand containerization as a concept.

Problem-solving approach. How do you handle ambiguity and failure? DevOps is fundamentally about improving systems that break. If you’ve never dealt with a failed deployment or a production incident, that’s a red flag. If you have, how you talk about it matters more than whether you solved it perfectly.

Communication ability. Can you explain technical concepts to different audiences? DevOps engineers talk to developers, security teams, management, sometimes customers. The ones who explain things clearly get hired and promoted faster.

The questions below are organized by what they test, not by topic. This helps you understand what interviewers are actually looking for.

CI/CD Pipeline Questions

CI/CD questions show up in nearly every DevOps interview. But the questions have evolved past “what does CI/CD stand for?"

"Walk me through how you’d set up a CI/CD pipeline from scratch.”

This is the most common technical question, and it separates candidates immediately.

What they’re testing: Whether you understand the purpose of each pipeline stage, not just the tools. Weak candidates list tools. Strong candidates explain decisions.

How to approach it: Structure your answer around the pipeline stages, explaining what happens and why:

  1. Source control integration — “I’d connect the version control system to trigger builds on commits. This catches issues early instead of waiting for manual deployments.”

  2. Build stage — “Compile the code, resolve dependencies, and create build artifacts. The goal is a reproducible build—same inputs, same outputs, every time.”

  3. Automated testing — “Unit tests run first because they’re fast. Integration tests follow. If tests fail, the pipeline stops immediately instead of wasting time on later stages.”

  4. Artifact management — “Store versioned artifacts so you can deploy the exact same build to different environments and roll back if needed.”

  5. Deployment stages — “Deploy to staging first for additional testing, then production. Each environment should mirror production as closely as possible.”

  6. Monitoring integration — “Pipeline should verify deployment health—not just that it finished, but that the application is actually working.”

Mention specific tools you’ve used (Jenkins, GitHub Actions, GitLab CI, ArgoCD), but lead with the reasoning. “I used Jenkins because the team already had it” is a better answer than “I used Jenkins because it’s popular."

"What’s the difference between continuous delivery and continuous deployment?”

This sounds like a trivia question, but the follow-up reveals understanding.

Strong answer: “Continuous delivery means every change is deployable—it passes all tests and can go to production with a single action. Continuous deployment goes further: every change that passes automatically goes to production with no manual approval.

The difference matters because continuous deployment requires mature testing, monitoring, and rollback capabilities. Most organizations use continuous delivery because they want human oversight before production changes.”

What makes this answer work: It explains why the distinction matters, not just what the words mean. Interviewers often follow up with “which approach have you used and why?"

"How do you handle database migrations in your pipelines?”

This question tests whether you’ve dealt with real production complexity.

What they’re looking for: Awareness that database changes are different from application deployments. You can’t just roll back a database schema change the way you roll back code.

Solid approach: “Database migrations need versioning and forward-only changes. I’ve used tools like Flyway and Liquibase that track which migrations have run and ensure consistency across environments.

Key practices: migrations should be backwards-compatible with the previous code version during deployment, tested in staging with production-like data, and never contain destructive changes that can’t be undone without data loss.”

Container and Orchestration Questions

Docker and Kubernetes questions dominate modern DevOps interviews. But the questions have shifted from “what is Docker” to scenario-based problems.

”A developer says their container works locally but fails in production. How do you debug this?”

This scenario question tests troubleshooting methodology.

How to structure your answer:

  1. Compare environments — “First, I’d verify the container images are identical. Different base images or dependency versions cause silent failures. Compare image digests, not just tags.”

  2. Check configuration — “Environment variables, secrets, and config files often differ between local and production. Something might be hardcoded locally that’s missing in production.”

  3. Review resource constraints — “Production might have memory limits or CPU constraints the developer doesn’t have locally. Check if the container is being killed for exceeding limits.”

  4. Examine networking — “Different network configurations between Docker Desktop and Kubernetes clusters. Service discovery, DNS resolution, and security groups all behave differently.”

  5. Check logs — “Compare logs from both environments. If logging is inconsistent, that’s the first problem to fix.”

Why this approach works: You’re demonstrating a systematic troubleshooting methodology, not guessing. Interviewers want to see that you won’t panic when something breaks.

”Explain Kubernetes to someone who’s never used it.”

This tests whether you understand concepts well enough to simplify them.

Weak answer: “Kubernetes is a container orchestration platform that manages containerized applications across a cluster of nodes using declarative configuration and control loops.”

Strong answer: “Imagine you have a hundred copies of an application running across multiple servers. Kubernetes handles the tedious work: starting containers, restarting failed ones, balancing traffic between them, and rolling out updates without downtime.

Instead of manually managing each container, you tell Kubernetes ‘I want five copies of this application running’ and it figures out where to put them. If a server dies, Kubernetes moves those containers somewhere else automatically.”

For DevOps roles, interviewers often follow up with questions about specific components—pods, deployments, services, ingress—and how you’ve used them in practice.

”When would you choose Docker Compose over Kubernetes?”

This question tests judgment, not just knowledge.

Strong answer: “Kubernetes adds complexity that isn’t always worth it. For local development, small applications, or teams without Kubernetes expertise, Docker Compose is simpler and faster.

I’d use Compose when: I need to run multiple containers together for development, I’m deploying to a single server, or the application doesn’t need auto-scaling or high availability.

I’d use Kubernetes when: the application needs to handle variable traffic, we require zero-downtime deployments, we’re running across multiple servers, or we need sophisticated networking and service discovery.”

Choosing the right tool for the situation beats always reaching for the most powerful option.

Infrastructure as Code Questions

IaC questions reveal whether you understand modern infrastructure practices or just know how to follow tutorials.

”What happens when your Terraform state file gets corrupted or lost?”

This scenario-based question tests real-world experience.

What they’re looking for: Understanding that Terraform state is a single source of truth, and losing it creates serious problems.

Strong answer: “Losing state means Terraform no longer knows what infrastructure it’s managing. If I run terraform apply, it might try to recreate resources that already exist, potentially causing outages.

To recover: first, import existing resources back into state using terraform import. It’s tedious but necessary. Long-term prevention includes using remote state backends like S3 with versioning enabled, state locking to prevent concurrent modifications, and regular state backups.

Worst case scenario with no backups: manually recreate the state file or carefully destroy and recreate infrastructure during a maintenance window."

"How do you structure Terraform code for a growing team?”

This tests organizational thinking, not just syntax knowledge.

What interviewers want: Evidence you’ve thought about scalability, reusability, and collaboration challenges.

Solid approach: “I organize by environment and use modules for reusable components.

Directory structure might look like:

  • modules/ for reusable components (VPCs, databases, compute)
  • environments/dev/, environments/prod/ for environment-specific configurations
  • Each module has its own state file to limit blast radius

For team collaboration: mandatory code reviews for infrastructure changes, automated plan outputs in pull requests so reviewers see what will change, and separate state files per environment so a mistake in dev can’t touch production.

I’ve used Terraform workspaces for simpler setups, but dedicated directories work better for significantly different environments."

"Compare Terraform and Ansible. When would you use each?”

What this tests: Understanding that these tools solve different problems.

Clear answer: “Terraform provisions infrastructure—creates the servers, networks, and cloud resources. Ansible configures what’s on those resources—installs software, manages files, runs commands.

They overlap but excel at different things. I’d use Terraform for anything that needs to exist in a cloud provider: EC2 instances, S3 buckets, networking. I’d use Ansible for configuration management: installing packages, deploying applications, managing services.

Some teams use Terraform for everything (user-data scripts), some use Ansible for everything (dynamic cloud resources). Both work, but using each tool for its strength usually produces cleaner code. Having Python scripting skills helps with either approach.”

Monitoring and Incident Response Questions

These questions reveal whether you’ve operated production systems or only built them.

”A service is running slowly. Walk me through your debugging process.”

This is probably the most important question type. It tests systematic thinking under pressure.

How to structure your answer:

  1. Establish baseline — “What’s normal for this service? Check historical metrics to understand if this is sudden or gradual degradation.”

  2. Identify the scope — “Is it all requests or specific endpoints? All users or a segment? This narrows the investigation.”

  3. Check the obvious — “Recent deployments, configuration changes, or infrastructure modifications. What changed?”

  4. Follow the request path — “Trace a slow request from the load balancer through services, databases, and external dependencies. Where does the time go?”

  5. Look at resources — “CPU, memory, disk I/O, network. Is something saturated?”

  6. Check dependencies — “Database queries, external APIs, cache performance. Slow dependencies create slow applications.”

What makes this answer strong: You’re showing a methodology. You’re not guessing or jumping to conclusions. The interviewer sees how you’d actually handle an incident.

”What metrics would you monitor for a web application?”

Don’t just list metrics. Explain why they matter.

Strong answer organized by category:

User-facing metrics (most important):

  • Response time percentiles (p50, p95, p99)—not averages, which hide outliers
  • Error rate—what percentage of requests fail
  • Availability—is the service reachable

System metrics:

  • CPU, memory, disk utilization per service
  • Network throughput and latency
  • Container/pod health and restart counts

Application metrics:

  • Request throughput
  • Database query performance
  • Cache hit rates
  • Queue depths for async processing

Business metrics:

  • Transactions completed
  • User actions per minute
  • Revenue-affecting functionality

“I’d use something like Prometheus and Grafana for metrics, with alerting thresholds based on historical patterns, not arbitrary numbers."

"Tell me about an incident you handled. What went wrong and what did you learn?”

This behavioral question is practically guaranteed.

How to structure your answer (use the STAR method loosely):

  • Situation: Brief context on what happened
  • Investigation: How you identified the root cause
  • Resolution: What fixed it
  • Learning: What changed to prevent recurrence

Example framework: “During a deployment, our payment processing started returning errors. Initial metrics looked normal, so it wasn’t immediately obvious.

We traced the errors to a timeout issue—a new feature increased database queries per transaction, and during high traffic, queries queued up. The deployment itself was fine; it just exposed a latent scaling problem.

Short-term fix was increasing timeout limits and database connections. Long-term, we added performance testing to our CI pipeline that simulates production load. Now we catch slow queries before deployment.”

What interviewers listen for: Did you stay calm? Did you learn something? Did you fix the system so it wouldn’t happen again? Nobody expects perfect incident response. They want evidence you handle pressure without making things worse.

Behavioral and Collaboration Questions

Here’s where a lot of technically strong candidates trip up. You’ve nailed the Kubernetes architecture question, explained Terraform state like a pro, and then someone asks “tell me about a time you disagreed with a coworker” and suddenly you’re staring at the ceiling trying to remember if you’ve ever had a coworker.

DevOps interviews aren’t purely technical. Expect questions about how you work with others.

”How do you handle disagreements with developers about deployment practices?”

What this tests: Whether you can navigate organizational politics without being a pushover or a dictator.

Solid approach: “I start by understanding their perspective. Sometimes ‘we can’t follow that process’ really means ‘this process adds friction we don’t have time for,’ which is a legitimate concern.

I’d propose a conversation about why the practice exists—what risk does it mitigate?—and whether there’s an alternative that achieves the same goal with less friction. Maybe the developer’s shortcut works fine for low-risk changes, and we reserve the full process for production-critical deployments.

If we genuinely can’t agree, I’d escalate with data: ‘Here’s what happened the last three times we skipped this step.’ Usually the evidence makes the case better than my opinion."

"Describe a time you proposed and implemented a process improvement.”

What they want: Evidence you’re proactive, not just reactive.

How to approach it: Choose an example where you:

  1. Identified a problem (preferably through data or metrics)
  2. Proposed a specific solution
  3. Got buy-in from others
  4. Implemented and measured results

Avoid examples where you just complained about something. Show ownership.

”How do you approach documentation?”

This question seems minor but reveals mindset.

What they’re testing: Do you think about knowledge sharing and future maintainability, or do you only care about getting things working?

Strong answer: “I document as I build, not after. If I’m setting up something complex, I keep notes on decisions and workarounds. Those notes become documentation with light editing.

For operational runbooks, I focus on: what does this system do, how do I know if it’s healthy, and what do I do when it breaks. The documentation best practices I follow emphasize keeping docs near the code—README files in repos beat wiki pages that go stale.”

Questions You Should Ask Them

Strong candidates ask thoughtful questions. Here’s what to ask:

About the role:

  • “What does a typical week look like for this position?”
  • “What’s the most challenging problem the team is facing right now?”
  • “How does the on-call rotation work?”

About the team:

  • “How are decisions made about tooling and architecture?”
  • “What does the deployment process look like today? What’s changing?”
  • “How does the team handle incidents?”

About growth:

  • “What does career progression look like for DevOps engineers here?”
  • “What resources are available for learning and experimentation?”

Red flags to probe:

  • If they mention lots of manual processes, ask what’s being automated
  • If they seem to have frequent incidents, ask how they’re addressing root causes
  • If the team is small, ask about on-call expectations honestly

How to Prepare for DevOps Interviews

Knowing the questions isn’t enough. Here’s how to actually prepare.

Build Something Real

The best interview prep is operating real systems. Set up a personal project with:

  • A CI/CD pipeline that builds and tests code
  • Containers deployed to a cluster (even a small one)
  • Monitoring and logging
  • Infrastructure defined in code

When you’ve done it yourself, the questions become conversations about shared experience rather than pop quizzes.

Consider building a home lab where you can experiment without fear of breaking production. Platforms like TryHackMe and Shell Samurai provide structured environments for practicing Linux and infrastructure skills.

Practice Explaining

Technical knowledge means nothing if you can’t communicate it. Practice explaining:

  • Why you’d choose one tool over another
  • How you’d debug a problem step by step
  • Complex systems in simple terms

Record yourself answering questions. It’s uncomfortable but effective.

Know Your Resume

Every project and tool on your resume is fair game. If you listed Kubernetes, be ready to discuss:

  • Specific problems you solved with it
  • Challenges you encountered
  • What you’d do differently

If you can’t speak confidently about something, remove it or study it before interviewing.

Prepare Incident Stories

Have two or three incident stories ready:

  • What happened
  • How you debugged it
  • What you learned
  • What changed afterward

These stories prove you’ve done the work. Theoretical knowledge can’t compete.

Common Mistakes That Kill DevOps Interviews

After talking with hiring managers, these patterns consistently hurt candidates:

Over-focusing on tools. “I know Jenkins, Kubernetes, Terraform, Ansible, Docker…” means nothing without context. How did you use them? Why? What problems did they solve?

Memorizing definitions instead of understanding concepts. Definitions are the start, not the goal. Understanding why practices exist matters more than reciting what they are.

Pretending to know everything. Nobody expects you to know everything. Saying “I haven’t worked with that, but here’s how I’d approach learning it” beats making up an answer and getting caught.

Not asking questions. Interviews are two-way. Asking nothing suggests you’re not evaluating the role critically—or worse, that you’re not curious. Avoid the other common IT interview mistakes too.

Avoiding failure discussions. Everyone has failed. Refusing to discuss failures suggests you haven’t learned from them or you’re being evasive. Either looks bad.

Frequently Asked Questions

What tools should I learn before a DevOps interview?

Focus on one tool per category: one CI/CD platform (GitHub Actions or GitLab CI for starters), one container runtime (Docker), one orchestrator (Kubernetes basics), one IaC tool (Terraform), and one configuration management tool (Ansible). Depth in a few tools beats surface knowledge of many.

How technical are DevOps interviews compared to software engineering interviews?

DevOps interviews are technical but different. You might not write algorithms on a whiteboard, but you’ll whiteboard architectures, debug scenarios, and explain system designs. Expect hands-on assessments where you write pipeline configurations, Dockerfiles, or Terraform code.

Should I mention certifications like AWS or Kubernetes certifications?

Certifications demonstrate structured learning and can help get past resume screening. In interviews, they’re a starting point—not proof of competency. Be ready to discuss anything a certification supposedly validates. Cloud certifications help, but practical experience matters more.

How do I answer questions about tools I haven’t used?

Be honest: “I haven’t worked with [tool] directly, but I’ve used [similar tool] which solves similar problems. My understanding is that [tool] differs in [specific ways].” Then pivot to what you do know. Interviewers respect honesty and transferable knowledge.

What if I don’t have production DevOps experience?

Personal projects and home labs count. “I built a CI/CD pipeline for my personal project using GitHub Actions” is legitimate experience. What matters is that you’ve done the work, not whether someone paid you to do it.

The Real Test

DevOps interviews have changed. Hiring managers got tired of candidates who could define terms but froze when asked to troubleshoot. The bar now is whether you can think through problems, explain your reasoning, and learn from mistakes.

Stop memorizing definitions. Start practicing how you’d talk through problems out loud. Build something so you have real stories to tell.

The best DevOps candidates treat interviews as technical conversations, not exams. If you can discuss infrastructure the way you’d discuss it with a coworker over coffee, you’re ready.