DevOps Interview Questions You Need to Know in 2023 - IQCode

Introduction to DevOps

DevOps is a software engineering practice that involves the collaboration of the development and operations teams to automate the project lifecycle. This method is related to the agile methodology and focuses on team communication, resource management, and teamwork to improve the production environment.

In this regard, this approach provides several benefits, including faster deployment, issue resolution, application stability and innovation behind it.

DevOps Tools

DevOps methodology aims to increase productivity and quality of product development through the use of several tools:

- Version Control System tools - e.g. GIT - Continuous Integration tools - e.g. Jenkins - Continuous Testing tools - e.g. Selenium - Configuration Management and Deployment tools - e.g. Puppet, Chef, Ansible - Continuous Monitoring tool - e.g. Nagios - Containerization tools - e.g. Docker

Organizations using DevOps have reported up to thousands of deployments in a single day, resulting in increased reliability, stability, security, and customer satisfaction.

DevOps Interview Questions for Freshers

1. What is a DevOps Engineer?

Reasons for the Popularity of DevOps

DevOps has become increasingly popular due to several reasons, including:

- Increased collaboration and communication between development and operations teams - Faster development cycles and continuous delivery of software - Improved deployment frequency and stability - Automation of routine tasks and processes - Greater emphasis on testing and quality assurance - Adoption of cloud technologies and infrastructure as code - Alignment with agile and lean methodologies - Business agility and the ability to respond quickly to changing market needs.

Overall, DevOps helps organizations to deliver software faster, with better quality and reliability, while maximizing efficiency and minimizing costs.

Understanding the Purpose of SSH

SSH or Secure Shell is a protocol used for secure remote access and communication between two devices. It enables users to securely access a remote computer or network over an unsecured network, such as the internet. SSH provides encryption for data transmission, making it more secure than other remote access methods like Telnet or FTP. With SSH, users can remotely access servers, transfer files, and create secure network tunnels. It is widely used for system administration tasks, managing servers, backing up data, and accessing remote resources securely.

What is Configuration Management?

Configuration Management is the practice of maintaining and controlling the state of a system or product throughout its entire lifecycle. It involves identifying and documenting the components of the system, tracking changes and updates, and ensuring that all configurations are consistent and up-to-date. Configuration Management is essential for ensuring that systems and products are reliable, maintainable, and meet the requirements of stakeholders.

Importance of Configuration Management in DevOps

Configuration management is crucial in DevOps because it helps in maintaining consistency and stability across the development, testing, and deployment phases. By using configuration management tools, teams can manage and automate the configuration of infrastructure, software, and applications, ensuring a smooth and efficient process.

Benefits of utilizing configuration management in DevOps include:

- Ensuring consistency and repeatability across environments - Tracking changes and versions of infrastructure, software, and applications - Enabling quick and easy recovery from failures and errors - Reducing errors and minimizing downtime - Facilitating collaboration and communication between team members

Overall, configuration management is a necessary component of DevOps that helps teams deliver high-quality products to customers faster and more consistently.

What is the meaning of CAMS in DevOps?

In DevOps, CAMS stands for Culture, Automation, Measurement, and Sharing. These four principles lay the foundation for effective implementation of DevOps practices and help organizations to achieve their goals faster and more efficiently.

What is Continuous Integration (CI)?

Continuous Integration (CI) is a software development practice where developers frequently integrate their code changes into a central repository. With each integration, automated builds and tests are run to detect errors and conflicts early on. The ultimate goal of CI is to provide rapid and consistent feedback on the quality of code changes, enabling teams to catch issues earlier and resolve them more efficiently.

Reasons for the Need of Continuous Integration

Continuous Integration (CI) is necessary for the following reasons:

  1. It helps to identify errors early in the development cycle, enabling quick and easy rectification before they become more complex and costly.
  2. It promotes collaboration and communication among team members and provides a unified codebase for software development.
  3. It enables developers to integrate code changes more frequently, minimizing the likelihood of code conflicts and making the project more adaptable to changes
  4. It leads to early software delivery. By continuously integrating code that has been tested and verified, the application becomes more reliable and can be released sooner

What is Continuous Testing (CT)?

Continuous Testing is a software testing approach that involves automated testing at every stage of the software development lifecycle. The goal of CT is to ensure that code changes are thoroughly tested and verified before being released into production. This iterative testing process helps to identify and address bugs and issues early on, thereby improving software quality and reducing the risk of defects in production. CT also helps to speed up the release cycle by providing instant feedback to developers about the quality of their code.

What are the three essential DevOps KPIs?

In DevOps, measuring the right Key Performance Indicators (KPIs) is crucial to ensure continuous improvement. Three important DevOps KPIs are:

1. Lead time: This KPI measures the time it takes to move a new feature or update from development to production. It is important to keep this time as short as possible to reduce the risk of defects and keep up with market requirements.

2. Deployment frequency: This KPI measures how often changes are deployed to production. Higher deployment frequency leads to faster innovation, reduced lead time and increased customer satisfaction.

3. Mean time to recover (MTTR): This KPI measures the time taken to restore production service after an incident or outage. Lower MTTR indicates better incident response and proactive monitoring of production systems.

Explanation of Phases in DevOps Methodology

DevOps is a combination of software development and operations and involves collaboration among different IT teams. The different phases in the DevOps methodology are:

1. Plan:

In this phase, all requirements are collected from the stakeholders and a plan is created for the development and deployment of the software.

2. Code:

In this phase, the actual software development takes place. Various coding practices and tools such as version control systems are used for efficient development.

3. Build:

In this phase, the code is transformed into an executable form with the help of build tools like Maven.

4. Test:

In this phase, all types of testing such as unit testing, integration testing, and regression testing are performed to ensure the quality of the software.

5. Deploy:

In this phase, the software is deployed to the production environment for release.

6. Operate:

In this phase, the software is monitored and any issues or bugs are resolved to ensure its smooth operation.

7. Monitor:

In this phase, the performance of the software is analyzed and monitored to identify any potential issues and make necessary improvements to the software.

Differences between DevOps and Agile Methodology

The Agile methodology and DevOps are two different terms often used interchangeably, but they have distinct differences.

Agile methodology is a software development practice that aims to improve software product quality, deliver it faster, and increase customer satisfaction. It utilizes an iterative approach and focuses on collaboration between cross-functional teams to deliver working software quickly.

On the other hand, DevOps is a set of practices and strategies used to automate and streamline the software development process. It emphasizes communication, collaboration, and integration between development and operations teams. The goal of DevOps is to enable continuous delivery of software changes while maintaining its quality and reliability.

In summary, Agile methodology focuses on developing software, while DevOps focuses on deploying and maintaining it. While there are overlaps between the two, they have different approaches and goals.

Difference between Continuous Deployment and Continuous Delivery

Continuous deployment and continuous delivery are two essential terms in the DevOps world, and though they sound similar, they have different meanings.

Continuous Deployment refers to the practice of deploying every code change that passes automated tests automatically to production. It means every time a developer pushes a change, it is automatically released to the users without human intervention.

Continuous Delivery, on the other hand, means that every change made to the codebase goes through automated testing, build, and deployment processes but it is not necessarily released to the end-users automatically.

In summary, continuous delivery ensures that the software is at a production-ready state, and continuous deployment automatically releases it to the end-users.

Antipatterns in DevOps

In DevOps, antipatterns refer to common practices or solutions that are ineffective, counterproductive, or even harmful to the overall objective of DevOps – to achieve fast and efficient delivery of high-quality software. Some common antipatterns in DevOps are:

1. Overreliance on automation tools - When teams rely too much on automation tools without considering the limitations and potential errors, it can lead to bigger problems.

2. Silos in the teams - Lack of communication and collaboration between various teams in the software development lifecycle can cause delays and inconsistencies.

3. Neglecting testing and quality assurance - Poor quality and insufficient testing can lead to production issues and customer dissatisfaction.

4. Ignoring security concerns - Inadequate security measures can result in breaches and data loss.

5. Inconsistent deployment practices - Inconsistent deployment processes can cause confusion and lead to errors in the production environment.

To avoid these antipatterns, teams should prioritize communication, collaboration, continuous testing, and security measures. They should also implement standardized deployment practices and regularly review their processes to identify areas for improvement.

Something About Memcached

Memcached is an in-memory caching system that is used to speed up dynamic database-driven websites. It stores data and objects in cache instead of directly querying the database, which helps reduce the load on the servers and improves the website's performance. Memcached is particularly useful for sites that have a large user base and frequently accessed data.


Here's an example of how to use Memcached in PHP:

// Connect to Memcached server
$memcached = new Memcached();
$memcached->addServer('localhost', 11211);

// Set data in cache
$memcached->set('key', 'data');

// Retrieve data from cache
$data = $memcached->get('key');

// Delete data from cache

Various Branching Strategies Used in Version Control System

In version control system, there are several branching strategies that can be used. The most commonly used branching strategies are:

1. Feature Branching:

This strategy involves creating a new branch for each new feature being developed. This allows developers to work on separate features without interfering with each other's code.

2. Release Branching:

In this strategy, a new branch is created specifically for final code releases. This allows developers to make sure that their code is complete and fully tested before being released to the public.

3. Hotfix Branching:

This strategy involves creating a new branch to fix critical bugs and issues in the production code. This allows developers to quickly fix any issues without interrupting the main development branch.

4. Mainline Branching:

This strategy involves using a single branch for all development, testing, and production code. This approach is simple and straightforward but can lead to issues with version control and bug tracking.

Choosing the right branching strategy depends on the specific needs of the development team and the project requirements.

List of Key Performance Indicators (KPIs) for Measuring the Success of DevOps:

Here are some KPIs that can be used to measure the success of DevOps:

1. Deployment Frequency<br>
2. Lead Time for Changes<br>
3. Mean Time to Recover (MTTR)<br>
4. Change Failure Rate<br>
5. Customer Satisfaction<br>
6. Employee Satisfaction<br>
7. Number of Releases<br>
8. Time to Release

These KPIs can provide insights into the efficiency, quality, and impact of the DevOps process on the overall business performance. Regular monitoring and analysis of these KPIs can help organizations make data-driven decisions for continuous improvement.

Understanding CBD in DevOps

In the context of DevOps, CBD stands for "Continuous Build and Deployment." This refers to a set of practices that enable teams to continuously develop, build, and deploy software. CBD is an important aspect of the DevOps workflow, as it helps to ensure that changes are integrated and deployed smoothly and efficiently. By automating the build and deployment process, teams can save time and reduce the risk of errors. This can ultimately lead to faster delivery of new features and improvements to end-users.

What is Resilience Testing?

Resilience testing is the process of testing a system's ability to withstand and recover from various failure scenarios. It involves intentionally triggering failures in the system, such as server crashes or network outages, to see how the system reacts and recovers. The goal of resilience testing is to identify weaknesses in the system's design or architecture and to improve its overall reliability and availability. This type of testing is particularly important for critical systems or applications that need to be available 24/7.

Difference between Continuous Testing and Automation Testing

Continuous Testing and Automation Testing are two distinct concepts in software testing.

Continuous Testing is an approach where tests are executed continuously throughout the development cycle. It involves automated and manual testing and provides feedback on the business risks associated with a software release candidate.

On the other hand, Automation Testing is a technique where software tests are performed with the help of tools and scripts, essentially replacing the manual testing process. It requires the use of specialized software to automate the execution of pre-defined test cases.

In summary, Continuous Testing involves both manual and automated testing performed continuously throughout the development cycle, while Automation Testing is specifically focused on the use of tools and scripts to automate test cases.

//Example of automation testing using Selenium WebDriver in Java

import org.openqa.selenium.By;
import org.openqa.selenium.WebDriver;
import org.openqa.selenium.WebElement;

public class Automation_Testing_Example {
  public static void main(String[] args) {
    //defining the chrome driver path
    //creating driver object
    WebDriver driver = new ChromeDriver();
    //loading the url

    //finding the search bar element and typing the search query
    WebElement searchbar = driver.findElement("q"));
    searchbar.sendKeys("Automation Testing");

    //finding the search button and clicking it
    WebElement searchBtn = driver.findElement("btnK"));;

    //closing the driver

Overview of DevOps Pipeline

The DevOps pipeline is a framework for development and deployment of software products that emphasizes close collaboration between development and operations teams to streamline the process of delivering code from development to production. The overall goal of the pipeline is to automate as much of the development and deployment process as possible, in order to reduce the time and effort required to deliver new features and fixes to end-users.

The pipeline can be broken down into several stages, including continuous integration, testing, delivery, and deployment. Continuous integration involves the process of merging all code changes into a central repository on a regular basis, typically several times a day. This helps ensure that all code is always up-to-date and that any changes made by different developers are compatible with each other.

Testing involves running automated tests to check the functionality of the software. These tests can include unit tests, integration tests, and other forms of automated testing.

Delivery involves packaging the code into a deployable format, such as a Docker image or a virtual machine image. This process also includes creating any necessary documentation or release notes.

Deployment involves pushing the code to a production environment, such as a server or a cloud-based platform. This process can involve rolling updates or blue-green deployments to minimize downtime and ensure a smooth transition from the old version of the software to the new one.

Overall, the DevOps pipeline is an essential tool for any organization that wants to deliver high-quality software products quickly and efficiently. By streamlining the development and deployment process, it helps teams work more collaboratively and reduces the risk of errors and downtime.

Overview of Ansible's Role in DevOps

Ansible is a popular configuration management tool used in the DevOps process to automate IT infrastructure and application deployment. It allows for rapid deployment, configuration management and orchestration of servers, virtual machines, network equipment, and applications.

With Ansible, DevOps teams can automate repetitive tasks, manage large environments more efficiently, and eliminate manual errors, thereby improving the reliability and stability of their systems. Ansible uses declarative language to describe system configurations and automates complex tasks using simple scripts. This makes it easier for developers to manage and deploy code across various environments, from development to production.

Furthermore, Ansible has a low learning curve, supports automation across multiple operating systems, and integrates well with other DevOps tools such as Jenkins and Docker. Its versatility and simplicity make it a popular choice for organizations looking to streamline their DevOps processes.

How Does Ansible Work?

Ansible is a configuration management and automation tool that allows users to manage and deploy software applications across multiple servers. It works by communicating with nodes (machines that are managed by Ansible) over SSH and executing tasks using modules.

Ansible requires Python to be installed on the control machine and the nodes. The control machine sends commands to the managed nodes via SSH and does not require any additional software to be installed on the nodes.

Ansible playbooks contain a series of tasks that are executed in sequence on the managed nodes. Playbooks can be used for various purposes such as deploying applications, configuring servers, and managing user accounts.

Overall, the simplicity and flexibility of Ansible make it a popular choice for system administrators and DevOps engineers.

How AWS Contributes to DevOps

AWS provides a variety of tools and services that enable organizations to adopt DevOps practices, such as continuous integration and delivery, infrastructure as code, and monitoring. Some of the AWS services that contribute to DevOps are:

1. AWS CodePipeline: A continuous integration and delivery service that helps users build, test, and deploy their applications.

2. AWS CloudFormation: A service that enables users to model and provision AWS resources using code. This helps to avoid manual provisioning and ensure consistency in infrastructure deployments.

3. AWS Elastic Beanstalk: A platform as a service that simplifies application deployment and management by automatically handling the capacity provisioning, load balancing, scaling, and monitoring of applications.

4. AWS Lambda: A serverless compute service that enables users to run code without provisioning or managing servers. This helps to speed up development and reduce operational overhead.

5. AWS CloudWatch: A monitoring service that provides users with visibility into their AWS resources and applications. It helps users to detect and respond to issues in real-time.

By leveraging these and other AWS services, organizations can automate their infrastructure deployments, improve their development processes, and accelerate their software delivery. This can help them to deliver high-quality applications faster and with greater agility.

Preparatory Approach for Developing a Project Using DevOps Methodology

Before initiating a project using DevOps methodology, the following preparatory approaches can be taken:

  1. Identify the objectives and goals of the project

  2. Identify the team members who will be involved in the project

  3. Establish communication channels between team members

  4. Identify the tools and technologies required for the project

  5. Develop a plan for continuous integration and continuous delivery

  6. Set up an automated testing framework

  7. Establish a version control system and repository for code management

  8. Implement security measures to protect the project

  9. Ensure that the project meets the required standards and compliances

  10. Define the process for monitoring and logging

  11. Implement a system for feedback and continuous improvement

By following these preparatory approaches, a project using DevOps methodology can be initiated and managed effectively to achieve the desired results.

DevOps Interview Question for Experienced: Explain the "Shift Left to Reduce Failure" concept in DevOps

In DevOps, the concept of "Shift Left to Reduce Failure" means moving testing and quality control processes to an earlier stage in the software development life cycle. This involves implementing automated testing during the coding process, which allows developers to identify and correct issues early on. This approach can help reduce failure rates, decrease the time required for testing, and minimize the need for post-release bug fixes. Essentially, the goal is to catch and fix problems as early as possible, before they have a chance to become larger issues down the line.

Have You Heard of Post-Mortem Meetings in DevOps?

In DevOps, post-mortem meetings are a common practice to analyze the causes of a system failure or incident. During these meetings, the team discusses what went wrong, what steps were taken to resolve the issue, and how to prevent similar incidents from happening in the future. These meetings are essential for continuous improvement and learning in DevOps.

The Concept of Sudo in Linux Operating System

In the Linux operating system, the sudo command allows users to execute commands with administrative or root-level privileges. The word "sudo" stands for "superuser do".

The concept behind using sudo is to provide a way for authorized users to perform specific tasks as an administrator, without giving them full root-level access. This helps to prevent accidental damage to system files and configurations, as well as unauthorized changes.

By default, the root user has full access to all system resources, which can be dangerous if used improperly. The sudo command allows users to perform specific administrative tasks without logging in as the root user, providing a layer of security and control.

Sudo can also be used to define and manage user privileges and access control on a Linux system. This allows administrators to fine-tune user permissions and access to specific system resources.

Overall, the sudo command is a critical tool for managing and securing Linux systems, and is a fundamental concept in the world of Linux administration and security.

Explanation of the architecture of Jenkins

Jenkins is a continuous integration and continuous delivery tool that helps automate the software delivery process. Its architecture follows a master-slave model, where the master node is responsible for managing the build queue, scheduling and distributing build jobs to slave nodes for execution.

The master node communicates with the slave nodes using Java Network Launch Protocol (JNLP) over TCP/IP connection. The communication is one way, from the master to the slave, which ensures that the slave nodes are secure and can't initiate any connections back to the master.

Jenkins provides various plugins for integrating with different tools and technologies such as version control systems, build tools, and testing frameworks. These plugins enable teams to customize their build environment according to their specific needs.

Jenkins also provides a web interface that allows users to configure, manage, and monitor their build jobs and other administrative tasks. The web interface is hosted on the master node and is accessible through a web browser.

Overall, the architecture of Jenkins is designed to provide flexibility, scalability, and ease of use for software development teams. It enables teams to set up a robust and efficient continuous delivery pipeline for their software delivery process.

Explanation of "Infrastructure as Code" (IAC) concept

Infrastructure as Code (IAC) refers to the process of managing and provisioning computing infrastructure using machine-readable definition files, rather than using manual processes. This creates a more reliable, consistent, and repeatable infrastructure deployment. With IAC, infrastructure configuration is treated as code, making it easier to track changes and maintain consistency across multiple environments. This approach helps in automating the infrastructure provisioning process and provides the ability to test and verify infrastructure changes before they are deployed. In general, IAC helps in streamlining infrastructure management and reduces the potential for human error.

What is Pair Programming?

Pair Programming is a software development technique where two programmers work together on the same task using a single workstation. One programmer is the driver, who writes the code, and the other is the navigator, who reviews each line of code and provides feedback. This approach promotes collaboration, shared learning, and can improve code quality by catching errors early.

Understanding Blue/Green Deployment Pattern

Blue/Green deployment pattern is a technique used in software development for deploying updates without downtime. This strategy involves creating two identical environments, one production-ready (green) and the other inactive (blue). The new update is deployed to the inactive environment, and upon completion, traffic is redirected from the current environment to the updated one. By doing so, you ensure that the updated environment works correctly before it receives real-time traffic. If there are any issues, you can easily switch back to the previous version with minimal downtime. This pattern is widely used in continuous deployment and Agile software development as it reduces the risk of failed deployments and minimizes downtime.

Understanding the Dogpile Effect and Preventing It

The dogpile effect is a situation that occurs when a high number of requests are made to a resource that is under heavy load, causing it to slow down or even crash. This is a common occurrence in web applications where multiple users are simultaneously trying to access a particular resource.

To prevent the dogpile effect, caching can be implemented. Caching involves storing the response of a request in a cache and then serving subsequent requests from the cache instead of querying the server every time. This helps to reduce the number of requests to the server and relieve the load on the resource.

Another way of preventing the dogpile effect is through the use of rate limiting. Rate limiting involves restricting the number of requests that can be made to a resource within a particular time frame. By limiting the number of requests per user, the resource is able to manage the load and avoid getting overwhelmed.

Proper load testing can also help to identify potential bottlenecks and optimize the resource to handle high levels of traffic. By identifying potential issues before they occur, measures can be taken to prevent the dogpile effect and ensure optimal performance of the resource.

Configuring Git Repository for Code Sanity Checking Before Commits

To configure Git repository to run code sanity checking tools before any commits, follow these steps:

1. Create a pre-commit hook script that will run the code sanity checking tool(s).

2. Save the script with the name "pre-commit" in the ".git/hooks" directory of your repository.

3. Set the executable permission of the script by running the command:

chmod +x .git/hooks/pre-commit

This will ensure that the script is executable.

4. Commit your changes. Now, every time you attempt to commit changes to the repository, the pre-commit hook will run the code sanity checking tool(s) before allowing the commit.

If the sanity testing fails, the commit will be rejected, and you will receive an error message. To prevent this from happening again, you will need to edit your code to fix any errors before attempting another commit.

Once you have made the necessary changes, you can attempt the commit again, and the pre-commit hook will run the code sanity checking tool(s) once more to ensure that the changes are now error-free before allowing the commit.

Ensuring a Script Runs Every Time a Repository Gets New Commits through Git Push

To ensure a script runs every time a repository gets new commits through Git push, you can use Git hooks. More specifically, you can use the post-receive hook, which is triggered after new commits have been received by the repository.

Here's how to set it up:

1. Connect to the server hosting your Git repository. 2. Navigate to the repository's Git directory. 3. In the hooks subdirectory, create a new file named post-receive (if it doesn't exist already). 4. Make sure the file is executable by running the command: chmod +x post-receive 5. Open the file in your preferred text editor. 6. Add the necessary commands or script to run whenever new commits are received. 7. Save and close the file. 8. Test the hook by pushing new commits to the repository and checking that the script runs as expected.

Note that the post-receive hook runs on the server side, so the script will run on the server where the Git repository is hosted.

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