Almost a decade ago, software developers and the operations team used to work separately. Thanks to DevOps Engineers, they have revolutionized the way development and operations teams collaborate with each other.

According to a recent report by Burning Glass Institute, job postings for DevOps engineers have grown by 18% annually since 2020. This reflects an increasing adoption of cloud technologies and containerization.

In this blog, we will discuss the answers to the most commonly asked DevOps interview questions and answers. First of all, we will discuss beginner-friendly DevOps interview questions followed by advanced DevOps interview questions.

DevOps Interview Questions for Beginners

1. What is meant by DevOps?

DevOps is a software development philosophy that bridges the gap between software development and IT operations. This concept came into existence between 2007 and 2008 in order to automate and streamline the software development, testing, deployment, and maintenance process. 

The main objectives of DevOps are as follows:

• To speed up and reduce errors in the software development life cycle (SDLC).

• To monitor and collect feedback that allows the development and operations teams to identify the problem early. Engineers can proactively handle technical issues.

• To reduce failure rates of new releases.

2. What does a DevOps Engineer do?

A DevOps Engineer is a technical professional who develops, deploys and maintains software systems with the help of DevOps methodologies and practices.

His goal is to help both software development, IT operations team and stakeholders in efficient delivery of products and services. A DevOps Engineer must have the following skills:

• Cross-boundary communication: Translating technical concepts across dev, ops, and business teams.

• Incident psychology: Stress management during outages and building psychological safety for innocent analysis.

• System visualization: Developing intuitive diagrams that explain intricate infrastructure relationships.

• Technical debt assessment: Balancing immediate needs against long-term sustainability costs.

• Documentation empathy: Creating guidelines that foresee users' frustrations and areas of knowledge deficit.

3. What is the difference between DevOps and Agile methodologies?

DevOps Methodology:

Agile Methodology:

4. Mention some of the most popular DevOps tools. What are their functions?

The following are some of the most popular DevOps tools that you must be familiar with if you want to become a DevOps engineer:

• Jenkins - Automated open-source server for continuous delivery and integration

• Docker - Platform for packing applications along with dependencies inside a container

• Kubernetes - Orchestration platform for managing application containers

• Git - System for versioning control, widely deployed with GitHub, GitLab, or Bitbucket

• Terraform - Coding infrastructure platform to provision as well as handle cloud resources

• Ansible - App deployment along with configuration management platform

• Prometheus - Tool kit for alerting and monitoring

• Grafana - Platform for analytics along with monitoring and metric visualization

• ELK Stack (Elasticsearch, Logstash, Kibana) - Log analysis and management suite

• Jira - Agile-aware project management solution

• SonarQube - Code security analysis and quality platform

• Puppet - Infrastructure configuration management tool

• AWS CloudFormation - AWS resource infrastructure as code service

Note: Do you want to learn all these tools in 6 months? Enroll in the DevOps Master’s Program now!

5. What is meant by CI/CD?

CI/CD means Continuous Integration and Continuous Delivery/Deployment, and it's an underlying DevOps practice that mechanizes the delivery process of the software.

Continuous Integration (CI):

• Code changes are merged periodically by developers to a central location

• Automated testing and builds execute with each merge

• Issues in integration and bugs are spotted immediately

• Central purpose: Confirm new code interacts suitably with the current codebase

Continuous Delivery (CD):

• Prepares code changes automatically for delivery to production

• Keeps the software in an always-deployable state

• Usually encompasses staged environments and testing that is automatic

• Actual release to production could still need some manual approval

The following are the advantages of CI/CD pipelines:

• Faster time to market

• Less error due to reduced manual intervention

• More frequent delivery

• Lower risk deployments

• More productive developers

• Better quality code

• Faster feedback cycles

CI/CD pipelines are generally executed through tools such as Jenkins, GitLab CI, GitHub Actions, CircleCI, or Travis CI, which automate the build, test, and deployment process whenever code changes are pushed to the repository.

6. What do you understand by container? How is it different from a virtual machine?

A container is a light, independent, run-time executable package of software containing everything required to execute an application: code, runtime, system tools, libraries, and configurations. Containers make software independent of its environment and cause it to operate consistently despite infrastructure variations.

The following are the key differences between Containers and Virtual Machine:

7. What is the need for AWS in DevOps? Why is it Important?

DevOps teams require vast infrastructure and services in order to implement their practices effectively. However, relying on physical infrastructure can be expensive, resource-intensive and time-consuming. This is when cloud infrastructure comes into play.

With 33% market share in cloud computing, AWS is quite compatible with DevOps environments. 

The following are the reasons for why AWS is important in DevOps:

• Infrastructure on Demand

1. Offers resizable compute, storage, and network resources without tangible hardware

2. Makes it possible to provision infrastructure in code (Infrastructure as Code)

3. Does away with slow hardware procurement cycles

• Automation Capabilities

1. Provides a myriad of services automatable through APIs

2. Supports automation of infrastructure via CloudFormation, AWS CDK, or Terraform

3. Facilitates automated deployment with CodePipeline, CodeBuild, and CodeDeploy

• Managed Services

1. Does away with operational overhead with managed databases, caching, messaging systems

2. Makes available monitoring, logging, and alerting through CloudWatch

3. Provides security features that can be integrated with DevOps processes

• Scalability

1. Auto-scaling functionality scales resources in response to demand

2. Elastic load balancing disperses traffic for high availability

3. Enables teams to architect systems that scale automatically without human intervention

• Cost Optimization

1. Pay-as-you-go pricing model aligns costs with actual usage

2. Cost visibility tools optimize spending

3. Ability to scale down unused resources to reduce costs

• Global Infrastructure

1. Multiple regions support global deployment strategies

2. Edge locations enhance content delivery and application performance

3. Enables disaster recovery and high availability architectures

8. Discuss Anti-Patterns of DevOps.

Anti-patterns refer to the practices in DevOps that contradict the core principles of DevOps. This can lead to inefficiencies, cultural problems and even failures. 

Some of the most prominent examples of Anti-Patterns in DevOps are as follows:

1. Siloed ‘DevOps Team’

Anti-pattern: Establishing a distinct "DevOps team" that takes a middle-man position between operations and development.

Example: One company establishes a dedicated DevOps team that's responsible for deployments and infrastructure. Developers toss code "over the wall" to this team, who then struggle to deploy it. This makes a new silo instead of removing barriers.

2. Manual Deployments

Anti-pattern: Using manual process for production deployment.

Example: An engineer uses a 20-step checklist for every deployment, such as manual database migrations and configuration updates. This is repeatable and error-prone, resulting in inconsistent environments and failed deployments.

3. Separate Development and Production Environments

Anti-pattern: Utilizing very different configurations between development and production.

Example: Windows laptops with local databases are used by developers and production uses Linux with clustered databases. Apps function in development but not in production because of environmental discrepancies.

4. Rare, Big Releases

Anti-pattern: Piling up lots of changes in large, rare releases.

Example: A group of developers packages three months' development into one weekend release. Trouble-shooting becomes almost impossible with such complexity when trouble occurs, and it frequently leads to long outages.

5. Monitoring and Observability Less

Anti-pattern: Flying blind without monitoring.

Example: A service goes down, but the team doesn't learn about it until customers call and complain. They don't have metrics, logs, or tracing to figure out what occurred and how to remedy it rapidly.

6. "Works on My Machine"

Anti-pattern: Brushing off bugs that won't reproduce locally.

Example: A coder refuses to debug a production problem since they can't replicate it on their laptop. The issue continues because differences in the environment are not controlled.

7. No Automated Testing

Anti-pattern: Manual testing alone.

Example: Each release takes a two-week test cycle during which QA manually checks hundreds of user scenarios. This slows down delivery and still overlooks numerous edge cases that could be identified by automated tests.

8. Treating Infrastructure as a Pet, Not Cattle

Anti-pattern: Maintaining servers one by one instead of as interchangeable assets.

Example: There is a team that has a single production server called "Zeus" which has been manually tweaked for years. Recovery is done in days when it crashes since no one recalls all the manual tweaks to it.

9. Runbooks Rather than Automation

Anti-pattern: Writing runbooks of manual procedures instead of automating them.

Example: One group keeps a 50-page guide explaining how to recover from typical failures, instead of building self-healing systems or automation scripts.

10. Blaming Culture

Anti-pattern: Instead of finding out how to avoid it, looking for who created a problem.

9. What is Infrastructure as Code (IaC)? Mention most popular IaC tools.

Infrastructure as Code (IaC) is a DevOps technique that provisions and manages computing infrastructure by using machine-readable definition files instead of manual methods. It addresses infrastructure configuration in the same manner as software code - written, versioned, tested, and deployed by automated means.

 The following are the main advantages of IaC:

• Consistency: Prevents configuration drift across environments

• Repeatability: Provisions same infrastructure every time

• Scalability: Scale infrastructure easily for many environments

• Version Control: Follow changes and roll back if necessary

• Documentation: Code is self-documenting infrastructure

• Automation: Eliminates manual steps and human mistakes

• Collaboration: Allows team review and contribution to infrastructure

The list of most popular IaC tools are as follows:

• Terraform - Cloud-agnostic tool that supports multiple providers with HCL syntax

• AWS CloudFormation - Native AWS service utilizing JSON/YAML templates

• Azure Resource Manager (ARM) - Native Azure service with JSON templates

• Google Cloud Deployment Manager - Native GCP service utilizing YAML and Python/Jinja2

• Ansible - Agentless automation tool that can handle configuration and deployment

• Chef - Configuration management solution with Ruby-based DSL

• Puppet - Configuration management with homegrown declarative language

• Kubernetes YAML - Declarative configuration for orchestration of containers

• Pulumi - Infrastructure as real code in programming languages (Python, TypeScript, etc.)

• Crossplane - Kubernetes-native provisioning of infrastructure

These solutions enable teams to code infrastructure, permitting version control, automated testing, and repeatable deployment practices between environments.

10. What is automation testing? Mention the benefits of automation testing.

Automation testing is the process of employing automation tools and scripts to run tests automatically, comparing actual outputs with expected outcomes. This method substitutes or complements manual testing activities by employing automation tools to perform repetitive test cases.

It is beneficial in performing regression testing, load/performance testing, and testing across multiple platforms or configurations.

The following are the main advantages of automation testing:

• Time Efficiency - Significantly lowers test run time than manual testing, particularly for regression tests

• Cost Savings - More initial cost but great long-term cost savings via less manual testing hours

• More Accuracy - No human errors during test execution and result validation

• Test Reusability - Scripts can be used for several test cycles and projects with minimal adaptation

• Consistency - Tests are run the same way each time, so results are always consistent

• Earlier Defect Detection - Can be incorporated into CI/CD pipelines to detect problems earlier in the development process

• Parallel Execution - Tests can be run in parallel across various environments and configurations

• Continuous Feedback - Gives instant feedback to developers, allowing them to work more quickly and iterate with fixes

11. What is meant by Version Control? Why is it important in DevOps?

Version control is a mechanism that keeps a record of file changes across time, enabling you to monitor changes, contrast versions, and return to earlier states if required. It keeps a total record of alterations made to a codebase.

Version control is central to DevOps practices for a number of crucial reasons:

1. Collaboration

Version control enables multiple workers to work on the same project at a time without conflicts.

Example: Three programmers developing separate features of an online shopping application can each develop their own branches of the master codebase. One develops the shopping cart, another develops user authentication, and the third develops payment processing—all without affecting one another's work.

2. Traceability

Each change is tracked with author data, timestamp, and comments.

Example: When a production bug surfaces, the team can look at the commit history to determine precisely which change caused the problem, who created it, and why, cutting debugging time considerably.

3. CI/CD Integration

Version control relies on automated pipelines to trigger builds and deployments.

Example: When a developer commits code to the main branch in Git, a Jenkins pipeline automatically identifies the change, executes tests, builds the app, and deploys it to staging environments.

4. Rollback Capability

Version control allows for rapid recovery from faulty changes.

Example: Following the release of a new feature that inadvertently crashes the system, operations can roll back to the most recent stable version immediately by switching back to the earlier commit, rebuilding services within minutes rather than hours.

5. Environment Consistency

Environment consistency is maintained by Infrastructure as Code files held in version control.

Example: Terraform scripts that define cloud infrastructure are versioned together with application code so that infrastructure changes are tracked and can be rolled back just like code changes.

6. Knowledge Sharing

Code history gives context and documentation to team members.

12. What is meant by the blue/green deployment pattern?

Blue/Green deployment is a release method that keeps two equal production environments: an active one (blue) and an idle one (green). This greatly decreases deployment risk and downtime.

This is how Blue/Green Deployment works:

1. Initial State: The "blue" environment hosts all production traffic while the "green" environment is present but does not get any traffic.

2. New Version Deployment: A new version of the application is rolled out to the idle "green" environment while the "blue" environment continues to serve users.

3. Testing: The "green" environment is tested with final production-like conditions, but without impacting actual users.

4. Traffic Switch: After validation, traffic is routed from "blue" to "green" environment—usually by modifying a load balancer setting or DNS.

5. Monitoring: The new environment is monitored for any problems.

6. Rollback Option: In case of problems, traffic can be routed back to the "blue" environment instantly with zero downtime.

7. Completion: Once deployed successfully, the "blue" environment goes into idle mode and will be the target of the next deployment.

Example Scenario

Suppose an e-commerce website on AWS:

1. The live application (v1.0) is hosted on EC2 instances behind an Elastic Load Balancer—this is the "blue" environment.

2. A new batch of EC2 instances is created and loaded with the updated application version (v1.1)—this is the "green" environment.

3. The QA team does final testing on the "green" environment with production data.

4. When prepared, DevOps engineers renew the ELB to route traffic to the "green" instances.

5. The switch occurs in seconds, and users see no downtime.

6. The team observes application stats and error rates following the switch.

7. If any major problems occur, they can quickly switch back to v1.0 by reversing the ELB to the "blue" environment.

13. What is SSH? What is its use?

SSH is a secure communications protocol that enables you to connect to and administer remote computers securely over an insecure network. SSH offers encrypted communications between two networked devices, establishing a secure channel even on public internet connections.

Most Common Uses of SSH in DevOps:

1. Secure Remote Administration

• Enables DevOps engineers to securely log into remote servers for management

• Offers command-line access to configure, troubleshoot, and maintain systems

2. Secure File Transfers

• Allows secure copying of files between systems via SCP (Secure Copy Protocol) or SFTP (SSH File Transfer Protocol)

• Utilized for code and configuration file deployment to production servers

3. Automated Scripts and Processes

• Facilitates automation of repetitive tasks through scripted SSH sessions

• Utilized in CI/CD pipelines for deployment automation

4. Tunneling and Port Forwarding

• Establishes secure tunnels for accessing services behind firewalls

• Allows access to restricted services through SSH port forwarding

5. Key-Based Authentication

• Offers safer authentication than passwords through public/private key pairs

• Supports automated, password-free logins required by CI/CD workflows

6. Integration with DevOps Tools

• The majority of DevOps tools (Jenkins, Ansible, etc.) employ SSH for safe communication with servers

• Supports safe execution of commands on remote hosts

14. Explain the process of branching in Git.

Git branching allows developers to diverge from the main line of development and work independently without affecting the main codebase. Here's an explanation of the branching process in Git:

Core Concepts of Git Branching

1. What is a Branch?

• A branch in Git is a lightweight movable pointer to a commit

• Each branch represents an independent line of development

• The default branch in Git is called "main" (formerly "master")

2. Basic Branching Workflow

• Create a new branch from an existing one (typically main)

• Make changes in your new branch

• Commit your changes to the new branch

• Merge your branch back into the main branch when complete

• Delete the feature branch after merging (optional)

3. Common Branch Types

• Feature branches: for developing new features

• Bugfix branches: for fixing bugs

• Release branches: for preparing releases

• Hotfix branches: for emergency fixes to production

4. Key Git Branch Commands

• git branch: List all branches

• git branch <branch-name>: Create a new branch

• git checkout <branch-name>: Switch to a branch

• git checkout -b <branch-name>: Create and switch to a new branch

• git merge <branch-name>: Merge a branch into your current branch

• git branch -d <branch-name>: Delete a branch

5. Advanced Branching Operations

• Rebasing: Reapplying commits on top of another branch

• Cherry-picking: Selecting specific commits to apply

• Branch protection: Preventing direct commits to important branches

15. What is the difference between horizontal and vertical scaling?

DevOps Interview Questions for Advanced Professionals

16. How do you handle configuration drift in a DevOps environment, and what tools can you use to prevent it?

Configuration drift occurs when the actual configuration of a system deviates from the desired configuration. This can lead to inconsistencies, errors, and security vulnerabilities. To handle configuration drift in a DevOps environment, you can use tools like Ansible, Chef, Puppet, or SaltStack. These tools allow you to define the desired configuration of your systems in code and automatically apply the configuration to all systems in the environment. By using version control and automation, you can ensure that all systems are consistent and up-to-date.

To prevent configuration drift, you can also use infrastructure as code (IaC) practices. IaC involves defining the infrastructure of your systems, such as virtual machines, networks, and storage, in code. This allows you to version control and automate the creation, configuration, and destruction of your infrastructure. By using IaC, you can ensure that your infrastructure is consistent, reproducible, and auditable.

17. How do you ensure compliance and security in a DevOps environment, and what best practices can you follow?

Ensuring compliance and security in a DevOps environment involves following best practices such as:

• Implementing security policies and procedures: Define and enforce security policies and procedures throughout the software development lifecycle.

• Using secure coding practices: Follow secure coding practices such as input validation, output encoding, and error handling to prevent security vulnerabilities.

• Implementing continuous monitoring: Use monitoring tools to detect and respond to security threats in real-time.

• Performing regular security audits: Conduct regular security audits to identify and remediate security vulnerabilities.

• Using encryption: Use encryption to protect data in transit and at rest.

• Implementing access controls: Implement access controls to limit who has access to your systems and data.

• Using automation: Use automation to enforce security policies and procedures consistently and accurately.

By following these best practices, you can ensure compliance and security in a DevOps environment.

18. How do you handle database changes in a DevOps environment, and what tools can you use?

Handling database changes in a DevOps environment involves using tools and practices such as:

• Version control: Use version control to track changes to your database schema and data.

• Database schema migrations: Use database schema migrations to manage changes to your database schema in a controlled and automated manner.

• Database continuous integration: Use database continuous integration to test your database changes in a staging environment before deploying them to production.

• Database continuous delivery: Use database continuous delivery to deploy your database changes to production automatically and consistently.

• Database backup and recovery: Use database backup and recovery tools and practices to protect your data and recover from disasters.

Tools you can use to handle database changes in a DevOps environment include Liquibase, Flyway, and DBDeploy. These tools allow you to manage database schema migrations, version control your database schema and data, and automate your database deployments.

19. How do you handle container orchestration in a DevOps environment, and what tools can you use?

Container orchestration involves managing and scaling containers in a distributed environment. To handle container orchestration in a DevOps environment, you can use tools such as Kubernetes, Docker Swarm, or Apache Mesos. These tools allow you to automate the deployment, scaling, and management of containers.

Best practices for container orchestration include:

• Using declarative configuration: Define the desired state of your containers and let the orchestration tool handle the details of deploying and managing them.

• Implementing health checks: Use health checks to monitor the health of your containers and automatically replace failed containers.

• Implementing rolling updates: Use rolling updates to update your containers without downtime.

• Implementing service discovery: Use service discovery to enable containers to find and communicate with each other.

• Implementing load balancing: Use load balancing to distribute traffic across multiple containers and improve performance and availability.

20. How do you handle incident response in a DevOps environment, and what best practices can you follow?

Handling incident response in a DevOps environment involves following best practices such as:

• Defining incident response procedures: Define and communicate incident response procedures throughout the organization.

• Implementing monitoring and alerting: Use monitoring and alerting tools to detect and respond to incidents in real-time.

• Implementing incident response playbooks: Use incident response playbooks to define the steps to take in response to specific incidents.

• Practicing incident response: Conduct regular incident response drills to test and improve your incident response procedures.

Bottom Line

In this blog, we discussed 20 advanced DevOps interview questions with answers. These questions cover topics such as deployment strategies, configuration drift, compliance and security, database changes, container orchestration, and incident response. 

By understanding these topics and best practices, you can demonstrate your advanced DevOps knowledge and skills in an interview. Remember to provide clear and concise answers, and use real-world examples to illustrate your points. Good luck with your DevOps interviews!