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DevOps Engineer Interview Questions That Matter(with answers)

Updated: Jul 13, 2023

10 Important DevOps Engineer Interview Questions:

DevOps Engineer Interview Questions And Answers

How would you approach setting up a continuous delivery pipeline? Could you elaborate on how the different tools interact in the process?

Why is this question asked?

As a DevOps engineer candidate, understanding Continuous Delivery (CD) pipeline architecture and its tooling is vital.


This question helps interviewers assess your knowledge of these areas, your practical experience in setting up pipelines, and your ability to strategize and coordinate different tools efficiently.

Example answer:

I'd start with a version control system like Git to manage and track code changes. When code is pushed to the repository, I would then use a Continuous Integration (CI) server, like Jenkins or Travis CI, to automatically trigger a pipeline run.


This CI process would build the application and run a series of tests, such as unit tests, integration tests, and static code analysis, to ensure code integrity and quality. Tools like JUnit or SonarQube could be used for these tests.


Once the application passes these tests, I would use a tool like Docker to package the application into a container, ensuring it runs consistently across different environments.


To manage these containers, especially in a distributed environment, I would use a container orchestration platform like Kubernetes. Kubernetes enables automatic deployment, scaling, and management of containerized applications across clusters of hosts.


For configuration management and provisioning infrastructure, I prefer using tools like Ansible or Terraform. They help in maintaining the desired state of the infrastructure and also speed up the process of setting up new servers or environments.


Once the application is deployed to a staging environment, acceptance tests should be run to ensure that the software behaves as expected from the end user's perspective. Tools like Selenium can be used for this.


Post-deployment, monitoring and logging are vital to ensure the application's performance and quickly address any issues. Here, I’d use tools like Prometheus for monitoring, and the ELK Stack (Elasticsearch, Logstash, Kibana) for log management and analysis.


Why is this answer good?

  • Comprehensive Understanding: This answer demonstrates a clear understanding of the complete CD pipeline, from code development to deployment and post-deployment monitoring.

  • Specific Tools: The candidate is able to name and describe the function of specific tools at each stage of the pipeline, indicating strong knowledge and hands-on experience.

  • Balance of Automation and Communication: The response highlights not only the importance of automation in testing, deployment, and monitoring, but also the role of effective communication throughout the process.

  • User-Centric: By including acceptance testing in the pipeline, the candidate shows a commitment to user satisfaction and product quality, which are key aspects of the DevOps philosophy.

Could you explain the advantages and disadvantages of mutable versus immutable deployments, and in which scenarios each would be most suitable?

Why is this question asked?

As a DevOps engineer candidate, understanding mutable and immutable deployments is vital.


This question helps interviewers gauge your knowledge of these deployment methodologies, your ability to weigh their pros and cons, and your practical experience in deciding the suitable strategy based on different use cases.



Example answer:

In a mutable deployment, we update the existing servers with the new version of the software.


This might involve tasks such as updating packages, modifying configurations, or deploying new code. One of the significant advantages of mutable deployments is that they typically require less infrastructure since we're reusing existing servers.


However, a major disadvantage is that they can lead to configuration drift, where the servers' state diverges over time, making it difficult to manage and troubleshoot.


Mutable deployments might be suitable for smaller environments with fewer servers, where configuration management is more straightforward, or when infrastructure resources are limited.


On the other hand, in an immutable deployment, instead of updating the existing servers, we replace them entirely with new servers for every deployment.


The benefits of this approach are consistency and reliability since every deployment happens on a fresh, identical environment. This eliminates the risk of configuration drift and makes rollbacks straightforward as we can simply revert to the previous server setup.


But, a disadvantage of immutable deployments is the infrastructure cost, as we need to spin up new servers for each deployment. Also, the process of setting up new servers can take longer than updating existing ones.


Immutable deployments are highly suitable for large-scale, complex systems where maintaining consistency is crucial. They are also great for when the software is deployed frequently or when the potential risks and downtime associated with mutable deployments are unacceptable.


So, I’d say the choice between mutable and immutable deployments is not absolute; it depends on factors such as the scale of the system, available resources, the frequency of deployments, and the acceptable level of risk.

Why is this answer good?

  • Conceptual Clarity: The answer demonstrates a clear understanding of mutable and immutable deployments, their benefits, and their drawbacks.

  • Practical Application: The candidate accurately highlights the scenarios in which each type of deployment is most suitable, indicating practical experience with deploying and managing real-world systems.

  • Balanced Viewpoint: The candidate does not categorically favor one approach over the other, instead emphasizing that the choice depends on various factors. This shows a balanced, pragmatic approach to problem-solving.

  • Risk Awareness: The candidate's mention of configuration drift and risks associated with deployments shows a deep understanding of the challenges in DevOps work and the importance of managing these risks.


Can you describe an efficient way to monitor and log hundreds of servers? What tools and strategies would you recommend?

Why is this question asked?

The idea here is to evaluate your knowledge and experience with large-scale system monitoring and log management.


Effective monitoring and logging are crucial for maintaining system health, troubleshooting issues, and enhancing system performance.


Your answer will reveal your practical skills, understanding of relevant tools, and your strategies for handling complex, large-scale environments.


Example answer:

When it comes to monitoring and logging hundreds of servers, I think it’s useful to use a combination of strategies and tools to ensure comprehensive coverage.


For infrastructure monitoring, I prefer using tools like Prometheus, Nagios, or Datadog. These tools can collect metrics from servers, like CPU usage, memory consumption, disk I/O, and network bandwidth, and provide real-time data.


I would use Grafana for visualizing these metrics, which can help identify trends and spot potential issues quickly.


On the application side, the Application Performance Monitoring (APM) tool New Relic is excellent. It can track errors, slow transactions, and performance bottlenecks within your application, providing in-depth insights that go beyond what infrastructure monitoring can offer.


Now, when it comes to log management, given the scale we're talking about, centralized logging is essential.


I'd use the ELK Stack (Elasticsearch, Logstash, and Kibana) or similar tools like Graylog. Logstash collects and transforms the logs, Elasticsearch stores and indexes them, and Kibana visualizes the data, allowing you to explore them in a user-friendly way.


I'd also recommend integrating your logging solution with a tool like Splunk, which excels at log analysis and can provide valuable insights from your log data.


It's great for identifying patterns, troubleshooting issues, and even setting up alerts based on specific events in your logs.


Another key strategy would be to implement alerts and notifications. Most of the tools I mentioned have capabilities or integrations for this. Setting up alerts for significant events or anomalies can help us respond quickly when something goes wrong.


Why is this answer good?

  • Detailed and Comprehensive: The answer provides a comprehensive overview of the tools and strategies necessary for monitoring and logging at scale, demonstrating in-depth knowledge and experience.

  • Appropriate Tooling: The candidate suggests a suite of tools that are widely used and recognized in the industry for their effectiveness, showing practical proficiency with relevant technologies.

  • Proactive Approach: By emphasizing alerts and notifications, the candidate demonstrates a proactive approach to problem detection and resolution, a crucial aspect of successful DevOps practice.

  • Balanced Strategy: The candidate's response covers both infrastructure and application-level monitoring, highlighting an understanding of the need for a balanced, holistic monitoring strategy.


How do you manage shared secrets or sensitive configuration details in a DevOps environment? Can you elaborate on the best practices and potential pitfalls?

Why is this question asked?

The interviewer is trying to understand your knowledge of securing sensitive information in a DevOps environment.


As a DevOps engineer, you need to ensure that shared secrets like passwords, API keys, and other sensitive data are properly managed to prevent security breaches, comply with regulations, and maintain system integrity.


Example answer:

My primary approach would be to use a dedicated secrets management system like HashiCorp's Vault, AWS Secrets Manager, or Azure Key Vault.


These tools allow for secure secret storage, access control, auditing, and automated secret rotation.


In terms of best practices, I adhere to the principle of least privilege, which means that access to secrets is only given to the individuals or services that absolutely need them.


Also, secrets should never be hardcoded into the application code or configuration files. Instead, they should be injected at runtime using environment variables or through the secret management tool's API.


As for potential pitfalls, one common mistake is not regularly rotating secrets. Regular rotation can minimize the risk if a secret is compromised.


Another major mistake, I think, is inadequate auditing. It's very important to monitor and log access to secrets to detect any unusual or unauthorized access quickly.


Finally, while secret management tools provide an important layer of security, it's equally important to ensure that these tools themselves need to be secured, updated, and properly configured to prevent breaches.


Regular security audits, patch management, and following the vendor's security best practices are crucial in this regard.


Why is this answer good?

  • Knowledge of Tools: The answer shows the candidate's familiarity with multiple secrets management tools, indicating their practical experience in secure DevOps environments.

  • Security Best Practices: The candidate highlights important security best practices, such as the principle of least privilege, secret rotation, and not hardcoding secrets in the code, reflecting their understanding of secure DevOps operations.

  • Understanding of Pitfalls: By discussing potential pitfalls, the candidate demonstrates their awareness of common mistakes and how to avoid them, indicating a proactive approach to security.

  • Importance of Auditing: Mentioning the need for auditing reflects the candidate's understanding of the importance of monitoring and accountability in maintaining a secure environment.


What's your approach to managing the Docker lifecycle, and how do you handle container orchestration?

Why is this question asked?

Your interviewer is trying to assess your understanding of Docker lifecycle management and container orchestration, two fundamental aspects of modern DevOps.


Your response should showcase your familiarity with containerized environments, practical experience with Docker and orchestration tools, and your strategy for efficiently managing container-based systems.


Example answer:

For building images, I generally use a Dockerfile to define the application environment. It’s best practice to keep the images as lean as possible, removing any unnecessary dependencies to reduce build time, increase startup speed, and minimize the potential attack surface.


Once the Docker image is built, it can be pushed to a registry like Docker Hub or a private registry for future use.


When it comes to running the Docker containers, it's crucial to ensure that they're stateless and immutable, meaning any data that needs to persist is stored outside the container. This makes it easier to stop, start, or move containers without losing data.


In terms of cleanup, Docker provides commands like 'docker system prune' to remove unused data. It's important to regularly clean up unused images, containers, and volumes to free up system resources.


When it comes to container orchestration, I prefer Kubernetes due to its widespread adoption and robust community support.


Kubernetes provides a declarative way to manage services, deployments, and scaling. It also handles networking between pods, service discovery, and ensures that the system is running as desired.


Helm, as a package manager for Kubernetes, also simplifies deploying and managing Kubernetes applications.


However, managing Kubernetes can be complex. So, using managed Kubernetes services like Google Kubernetes Engine (GKE), Amazon EKS, or Azure AKS could be a more effective way to handle orchestration, as they reduce the operational overhead.


Why is this answer good?

  • End-to-End Understanding: The candidate exhibits a comprehensive understanding of the Docker lifecycle, from building images to running containers and cleanup, demonstrating in-depth practical knowledge.

  • Orchestration Skills: The candidate's preference for Kubernetes and understanding of its benefits and challenges shows their familiarity with industry-standard tools and best practices.

  • Security and Efficiency: By emphasizing lean Docker images and managed services, the candidate demonstrates a focus on efficiency and security, two critical factors in successful DevOps practice.

  • Data Management: The mention of making containers stateless and immutable shows an understanding of how to manage data in a containerized environment, which is a common challenge in such setups.


Can you discuss a time when you had to scale a system to handle an increased load? What tools and strategies did you use?

Why is this question asked?

This question is asked to understand your real-world experience with system scaling, a critical aspect of DevOps.


Your answer will provide insight into your ability to deal with increased system loads, your problem-solving skills, and your familiarity with tools and strategies used for effective scaling.


Example answer:

In my previous role, our application experienced an unexpected surge in traffic due to a successful marketing campaign. The load increased beyond our current capacity, resulting in slow response times and even occasional downtimes.


Firstly, we addressed the immediate issue by adding more servers to our fleet, effectively scaling up. We used AWS EC2 instances and were able to quickly provision additional servers through AWS Management Console.


However, for a more sustainable solution, we decided to implement auto-scaling, allowing our system to dynamically scale in or out based on the load.


We used AWS Auto Scaling in conjunction with Elastic Load Balancer (ELB) to distribute incoming traffic evenly across the servers.


We also identified that our database was a bottleneck during peak load. Therefore, we adopted a Read Replica feature of Amazon RDS for our relational database to handle increased read traffic, thus balancing the load between the master and replica databases.


Another crucial part of our strategy was to implement caching using Redis. By storing the frequently accessed data in the cache, we significantly reduced the load on our databases and improved the application's response time.


Throughout this process, we heavily relied on monitoring tools like Amazon CloudWatch and New Relic to track the system's performance and adjust our scaling strategies accordingly.


So, this experience taught me the importance of proactively planning for scale, monitoring system performance, and leveraging cloud services for effective load balancing and auto-scaling.


Why is this answer good?

  • Real-World Experience: The candidate provides a detailed account of a real-world scenario, demonstrating their ability to handle practical challenges in system scaling.

  • Tool Proficiency: The candidate shows their familiarity with several AWS services, database management strategies, and monitoring tools, reflecting their technical competency.

  • Strategic Approach: The candidate’s approach to managing the immediate crisis, then implementing a more sustainable solution, demonstrates strategic thinking and effective problem-solving skills.

  • Lessons Learned: The candidate concludes with what they learned from the experience, showing a commitment to continual learning and improvement, key traits for a DevOps engineer.


How do you ensure that the infrastructure you create is as code (IaC)? How does this contribute to the overall DevOps workflow?

Why is this question asked?

Your interviewer wants to understand your knowledge of and experience with Infrastructure as Code (IaC), a crucial practice in modern DevOps. Your ability to implement and understand the benefits of IaC is a key component of effective, scalable, and resilient DevOps strategies.


Example answer:

To ensure that infrastructure is created as code, I utilize tools like Terraform, Ansible, and CloudFormation. These tools allow us to define and provision our infrastructure in a repeatable and predictable manner.


For example, with Terraform, I write configuration files in HashiCorp Configuration Language (HCL) to describe the resources required.


These configurations can be version-controlled in a repository, such as Git, just like application code, allowing us to track changes, revert to previous versions, and involve multiple team members in the review process.


The main advantage of IaC in the overall DevOps workflow is consistency and speed. With IaC, we can quickly set up or replicate environments without manual error-prone steps, thus speeding up the process of software delivery.


Also, it helps maintain consistency between development, staging, and production environments, reducing the risk of issues arising from configuration drift.


IaC also facilitates automation, another key aspect of DevOps. With IaC, we can use Continuous Integration/Continuous Deployment (CI/CD) pipelines to automatically build, test, and deploy both our application and the infrastructure it runs on.


This results in more frequent and reliable deliveries.


Lastly, IaC also helps with disaster recovery. Since our infrastructure is codified, we can rebuild it quickly and accurately in case of a disaster, increasing the resiliency of our systems.


Why is this answer good?

  • Tool Familiarity: The candidate mentions specific tools for IaC, indicating they have hands-on experience with these technologies.

  • Version Control & Collaboration: The mention of version control shows the candidate's understanding of best practices in IaC and teamwork.

  • Understanding of Benefits: The candidate explains the benefits of IaC in terms of consistency, speed, automation, and disaster recovery, showing a deep understanding of how IaC contributes to effective DevOps workflows.

  • Integration with DevOps: Discussing how IaC fits into the larger DevOps strategy, especially in the context of CI/CD pipelines, shows a holistic view of DevOps practices.


Can you discuss the importance of shift-left testing in a DevOps context? What are the main considerations and how do you ensure it is properly implemented?

Why is this question asked?

The idea is to test your knowledge of the shift-left testing approach in DevOps and its implementation.


Your ability to understand its significance, the main considerations, and how to ensure it is appropriately applied shows your capability in enhancing DevOps efficiency and software quality.


Example answer:

Shift-left testing is an approach where testing is performed earlier in the lifecycle (i.e., 'shifted left' on the project timeline). In the context of DevOps, it plays a crucial role in enabling faster, more reliable software releases.


There are several considerations for implementing shift-left testing. Firstly, testing should be embedded in all stages of development, from unit testing in the coding phase to integration testing when merging code to the main branch.


This requires a change in mindset, where quality becomes everyone's responsibility, not just the QA team's.


To implement shift-left testing, I encourage developers to write tests for their code, use test-driven development (TDD) where appropriate, and automate as many tests as possible.


This could be achieved through tools such as Junit, Selenium, or Cucumber for unit, functional, and behavior-driven testing respectively.


Integration with a CI/CD pipeline is also critical. Each code commit triggers an automated build and test process, ensuring that issues are detected and fixed early.


Another key aspect is maintaining a test environment that closely mirrors the production environment. This can be achieved using Infrastructure as Code (IaC) tools, such as Terraform or Ansible, and containerization with Docker.


Properly implementing shift-left testing involves not just the right tools and processes, but also fostering a culture of shared responsibility for quality. This can be encouraged through practices such as pair programming, code reviews, and knowledge-sharing sessions.


Why is this answer good?

  • Concept Understanding: The candidate clearly articulates the shift-left testing concept and its importance in a DevOps context, showcasing their grasp of efficient testing strategies.

  • Practical Approach: The candidate details their approach to implementing shift-left testing, from embedding testing into development to automating tests and integrating with CI/CD, indicating practical knowledge and experience.

  • Tool Knowledge: Mention of specific tools for testing and IaC indicates the candidate's hands-on experience with these technologies.

  • Cultural Aspect: The emphasis on fostering a culture of shared responsibility for quality shows the candidate's understanding that successful DevOps involves both technological and cultural shifts.


Can you discuss a time when a deployment failed and how you handled it? What was the cause, and what did you learn from that experience?

Why is this question asked?

This question is asked to understand your ability to handle challenging situations and learn from failures.


Your approach to troubleshooting, your ability to analyze the root cause of issues, and the lessons you derive from such incidents are important for effective problem-solving and continual improvement in a DevOps role.


Example answer:

A few months ago, we faced a deployment failure. We were pushing a major update, but as soon as the new version went live, the application started experiencing serious performance issues, rendering it unusable for many users.


We had incorporated a rollback strategy as part of our deployment process, so my immediate response was to roll back to the previous stable version. This immediately mitigated the impact on our users, buying us time to investigate the root cause.


The cause turned out to be a database query in the new feature, which was not optimized for our production data volume and was causing a CPU bottleneck. The issue hadn't shown up during testing because our test data volume was much smaller.


The main lesson from this incident was the importance of testing with a production-like environment, including data volume.


To address this, we improved our testing strategy to include performance testing with large datasets, ensuring the test environment closely mirrored the production environment.


We also incorporated a more comprehensive monitoring system, which helped us identify issues before they became critical.


Why is this answer good?

  • Real-World Experience: The candidate provides a detailed account of an actual deployment failure, demonstrating their ability to handle real-life issues.

  • Immediate Mitigation: The candidate’s first step was to minimize the impact on users, showing their understanding of the importance of user experience.

  • Root Cause Analysis: The candidate was able to identify the root cause of the issue, showing good troubleshooting skills.

  • Lessons Learned and Improvement: The candidate talks about how the incident led to concrete improvements in their testing and monitoring processes, indicating a commitment to continual learning and improvement.


Have you had an experience where communication or collaboration issues impeded the smooth running of DevOps practices? How did you handle the situation, and what changes were implemented as a result?

Why is this question asked?

Your interviewer wants to assess your communication and collaboration skills. In DevOps, team collaboration and communication are critical, and your ability to resolve any such issues and enhance collaboration demonstrates your effectiveness as a DevOps Engineer.


Example answer:

In one project, there were frequent misunderstandings between the development and operations teams due to communication gaps. These issues were affecting the speed and efficiency of our deployments.


To address this, I suggested we implement a ChatOps strategy, incorporating a tool like Slack where both teams could communicate effectively.


By moving discussions about deployment and infrastructure to a shared platform, everyone had visibility of the conversation and could understand the challenges and blockers faced by the other team.


Additionally, I advocated for more joint planning and review sessions, ensuring both teams were involved in the decision-making process from the start.


These changes greatly improved our team dynamics. The shared visibility increased empathy and understanding between the teams, and we were able to collaborate more effectively, which had a positive impact on our DevOps practices.


Our deployment frequency increased, and the number of failed deployments decreased significantly.


Why is this answer good?

  • Identification of the Issue: The candidate accurately recognized communication as a problem impacting their DevOps practices, indicating their understanding of the importance of good communication in DevOps.

  • Proactive Problem-Solving: The candidate didn't just identify the problem, but took active steps to solve it, demonstrating their initiative and problem-solving skills.

  • Effective Solutions: The solutions implemented by the candidate were well-thought-out and effective, showing their understanding of how to improve team communication and collaboration.

  • Positive Outcome: The candidate was able to demonstrate the positive impact of the changes, providing evidence of their effectiveness as a DevOps Engineer.


Conclusion:

There you have it — 10 important DevOps Engineer interview questions and answers. Within these larger answers, we’ve also answered a few smaller, simpler questions.


This way, you don’t have to go over the same questions again and again.


Use this as a guide and great opportunities should not be too far behind.


On that front, if you’re looking for DevOps Engineer roles, check out Simple Job Listings. We only list remote jobs and most of them pay really well. What’s more, a huge chunk of jobs that we list aren’t posted anywhere else.


Visit Simple Job Listings and find amazing remote DevOps Engineer roles. Good luck!


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