Beginners

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Q1. What is the difference between Continuous Deployment vs Continuous Delivery?

Continuous Delivery and Continuous Deployment are two terms that are often used interchangeably, but they have different meanings in software development.

Continuous Delivery (CD) is a software development practice where code changes are automatically built, tested, and prepared for release to production in a repeatable and reliable way as needed.

Continuous Deployment (CD) can be defined as an extension of Continuous Delivery, in which all passed codes from automated testing are deployed to production without manual interruption.

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Q2. Describe the version control system and its benefits.

A version control system (VCS) is a tool that enables developers to manage changes to source code, documentation, and other types of files. VCS is also referred to as SCM (Source Code Management) or RCS (Revision 
Control System), interchangeably. A VCS provides a shared central repository where developers can store and track changes to files, track issues and bugs, collaborate on projects, and maintain a history of changes.

The most common type of VCS is a distributed version control system (DVCS), which allows multiple developers to work on a project simultaneously and independently. Some popular examples of VCS software include Git, SVN (Subversion), Mercurial, and CVS (Concurrent Versions System).
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Benefits:

• Collaboration: VCS allows multiple developers to work on the same codebase simultaneously without the risk of conflicts or data loss. In this way, developers are free from merge conflict issues.
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• Versioning: VCS has a track of all changes made to a codebase, including who, when, and what changes are made. This enables developers to easily revert to a previous version of the code if necessary or to compare different versions of the code to identify bugs or issues.
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• Backup and disaster recovery: VCS acts as a backup of the codebase, allowing developers to recover lost or deleted code. It also provides a way to roll back to a previous version of the code in the event of a catastrophic failure.
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• Branching and merging: It allows developers to create and manage multiple branches of a codebase, enabling them to work independently. The ability to merge changes from different branches into a single codebase allows developers to integrate their work seamlessly.

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Q3. What is Configuration Management and its importance?

Configuration management helps to automate and streamline the process of managing infrastructure and application deployments. In DevOps, configuration management is used to ensure that the infrastructure and applications are deployed in a consistent and repeatable manner and that any changes are tracked and managed effectively.

One of the key practices in DevOps is the use of infrastructure as code (IaC), which involves defining the entire infrastructure as a codebase that can be version controlled and managed like any other software code. Configuration management tools are used to automate the provisioning and deployment of infrastructure and to ensure that it remains consistent across different environments.

Some of the common configuration management tools used in DevOps include Chef, Puppet, Ansible and SaltStack.

Key benefits of configuration management are:

• Improved collaboration and communication among team members
• Increased efficiency and productivity
• Better control over the development process
• Improved quality and reliability
• Facilitates compliance

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Q4. What is meant by Infrastructure as code and how to implement IaC?

IaC stands for Infrastructure as Code, which is an approach to managing and provisioning IT infrastructure through code instead of manual processes.

The idea behind IaC is to treat infrastructure as software, where infrastructure resources can be defined and managed using programming languages and tools. This enables teams to version control, test, and deploy infrastructure changes in a repeatable, reliable, and scalable manner. This hugely avoids manual errors while configuring.

A few steps involved to implement IaC are:

1. Choose an IaC resource that suits best to the project. A few are Terraform, Ansible, Chef, Puppet, and CloudFormation.
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2. Write code for Infrastructure. It is generally written in a declarative language such as YAML or JSON, that specifies the desired state of the infrastructure.
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3. Build, test and Deploy the code to configure the infrastructure based on the code
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4. Finally monitor and maintain to identify errors and fix them if needed

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Q5. Describe Containerization.

Containerization is a process of combining or packing an application and all of its dependencies into a single executable package called a container. A container provides a self-contained and isolated runtime environment for the application, which ensures that the application runs consistently across different environments.

Containers play an alternative to traditional virtual machines. Unlike virtual machines, which require a complete operating system to be installed and run, containers only require the necessary dependencies and libraries to be packaged with the application. This results in faster start-up times and lower resource consumption.

Containerization has become a popular approach for deploying and managing applications, especially in cloud computing environments.

Containerization is well known for its key benefits:

• Speed
• Fault isolation
• Efficiency
• Ease of management
• security

Docker, Kubernetes, and Apache Mesos are some popular containerization platforms.
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Intermediate

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Q​​1. Describe the “Shift left” concept in DevOps.

The "Shift Left" concept in DevOps refers to moving testing and quality assurance activities earlier in the software development life cycle (SDLC). That is moving the testing phase as early as possible or integrating the testing phase with development. In traditional SDLC approaches, testing is typically performed towards the end of the development cycle, often resulting in delays and increased costs if issues are found.

With this practice, testing and quality assurance are integrated earlier in the development process, ideally from the initial design phase. Overall, the shift left concept is a key component of a successful DevOps approach, as it helps to ensure that software is delivered quickly, reliably, and with a high level of quality.

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Q2. Define different KPIs that are used for measuring the success of DevOps.

There are several key performance indicators (KPIs) that can be used to measure the success of DevOps implementation. Here are a few examples:

1. ‍Deployment frequency:
   This KPI measures how frequently/often the code changes are deployed to production. A higher deployment frequency indicates that the team is delivering new features and fixes more frequently.
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2. ‍Mean Time to Recovery (MTTR):
   ‍MTTR indicates the time to recover from production incidents or outages. A lower MTTR indicates that the team can quickly identify and fix issues, reducing downtime and improving system reliability.
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3. ‍Change failure rate:
   It calculates the percentage of code changes that result in production incidents. A lower change failure rate indicates that the team is making fewer mistakes and delivering higher-quality code.
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4. ‍Lead time for changes:
   This KPI measures the time it takes to move code changes from development to production. A shorter lead time indicates that the team can deliver code changes more quickly and efficiently.
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5. ‍Mean time between failures (MTBF):
   MTBF measures the average time between failures of a system or application. A higher MTBF indicates that the team is delivering a more reliable system.
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6. ‍Customer satisfaction:
   It gives the details of satisfied customers with the software being delivered. By measuring customer feedback, the team can better understand the impact of their work on end-users.
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7. ‍Defect escape rate:
   It refers to the percentage of defects or issues that are not identified during testing and are found by customers or end-users after the software has been released into production. A low defect escape rate indicates that the software is of higher quality and that the team is effectively testing and identifying issues before the software is released to end users.

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Q3. Differentiate between continuous testing and automation testing.

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Q4. What is the Blue/Green Deployment Pattern?

The blue/green deployment pattern is also referred to as the red/black deployment pattern. This is referred to as a technique used while software deployment. It involves two identical environments and shifting traffic between them while deployments, one of which (the Blue environment) is currently executing in production, while the other (the Green environment) is inactive.

While deploying a new version of the application, switching the traffic is done from the Blue environment to the Green environment. This is achieved by updating the load balancer configuration or DNS settings. As soon as the traffic has been successfully redirected to the Green environment, the Blue environment will be inactive.

Key benefits:

• Helps to achieve reduced downtime
• Rollback capability
• Reduced risk‍
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Similar to Blue/Green Deployment Patterns, to achieve zero or reduced downtime below patterns are used in DevOps:

• Rolling deployment
• Canary deployment
• A/B deployment
• Feature Toggles

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Q5. What is DORA Metrics and how does it help DevOps?

DORA (DevOps Research and Assessment) Metrics are a group of key performance indicators (KPIs) used to assess and measure the performance of software development teams who adopt DevOps practices. The metrics were developed by the DORA research team, which is now a part of Google Cloud.

The four DORA metrics are:

• Deployment Frequency
• Lead Time for Changes
• Mean Time to Restore (MTTR)
• Change Failure Rate
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These metrics help in deriving quantitative measurements of the performance of DevOps teams. Continuous monitoring and improving the analytics help to improve and optimize their processes, leading to faster delivery of high-quality software.

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Q6. What is DevOps as a Service?

DevOps as a Service (DaaS) is a package that includes a set of DevOps tools and services. It is a managed service that aims to automate the entire software development lifecycle, from coding, testing to deployment and monitoring.

DaaS allows companies to focus on developing and delivering innovative and high-quality software while leaving the management and maintenance of the underlying infrastructure to the DaaS provider. It helps organizations with scalability and adapts to changing business needs more quickly.
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Experts

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Q1. What is TOSCA in DevOps?

TOSCA (Topology and Orchestration Specification for Cloud Applications) is a standard language that helps to define and describe the services, relationships, components and dependencies of a cloud computing application. TOSCA helps in the creation of portable and interoperable cloud applications.

In the DevOps process using TOSCA, the architecture, its components and their dependencies can be described. Also, using the TOSCA standard, services that create and modify the DevOps lifecycle processes could be controlled.

TOSCA helps DevOps teams to define their infrastructure as code, which enables them to version control their application architecture, automate the deployment process, and ensure consistency across multiple environments. TOSCA can be integrated with DevOps tools such as Ansible, Terraform, and Kubernetes to automate the deployment and management of cloud applications.

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Q2. Brief about different components of Selenium.

Selenium is an open-source testing framework aimed to support web application testing. It offers a set of tools for automating web browsers and supports multiple programming languages such as Java, Python, Ruby, JavaScript, and C#.

Selenium consists of four components, including:

1. WebDriver
   WebDriver is the main component of Selenium that provides a programming interface to control a web browser's behavior. WebDriver supports multiple browsers such as Chrome, Firefox, Safari, and Internet Explorer.

2. IDE
   Selenium IDE is a browser extension used for recording and playback of test cases. IDE doesn't need any programming knowledge to create automated test scripts. Selenium IDE generates test scripts in different programming languages such as Java, Python, Ruby, and C#.

3. Grid
   Grid is used for running Selenium tests on multiple machines in parallel. It allows running tests simultaneously on different browsers, operating systems, and machines. It acts as a central point for distributing test tasks to multiple nodes.

4. Remote Control (RC)
   Selenium RC is used for controlling browser behavior remotely. It comes with two components RC Client and RC server.

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Q3. List down a few basic Git commands.

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Q4. What are the key aspects of the Jenkins pipeline?

Jenkins is an open-source automation server. It is most popularly used for building, testing, and deploying software. One of the key features of Jenkins is its master-slave architecture. With this architecture, Jenkins supports distributed builds across multiple machines.

Jenkins architecture has two components:

• Jenkins Master/Server
• Jenkins Slave/Node/Build Server
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1. Jenkins Master/Server
Jenkins Master is the central process that manages and coordinates the build, and multiple Jenkins slave nodes that perform the actual builds. The Jenkins master also takes care of scheduling and assigning build jobs to the slave nodes, and consolidating the build results. It also hosts the Jenkins web interface, which allows users to configure the build jobs, view the build results, and manage the Jenkins system.
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2. Jenkins Slave/Node/Build Server
The Jenkins slave nodes are responsible for performing the actual builds. They run the build commands, execute the tests, and generate the build artifacts. The slave nodes are managed by the master server, which assigns them to build jobs based on workload and resource availability. Once a build job is completed, the slave node sends the build results back to the master server for display. The slave nodes can be either physical or virtual machines that are connected to the Jenkins master server over the network.

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Q5. What is meant by a centralized logging solution?

A centralized logging solution is a software platform that brings together log data from multiple sources into a single, easily accessible location. This is typically used in large-scale systems or applications where multiple servers or applications generate logs, and it can be difficult to manage all of the log data in one place.

A centralized logging solution provides several benefits, including:

The few benefits of centralized logging solutions are simplified log management, better security, and improved troubleshooting.

There are several popular centralized logging solutions available, including ELK Stack (Elasticsearch, Logstash, Kibana), Splunk, Graylog, and Fluentd.

Centralized logging solution plays an important role in DevOps by continuous monitoring, altering in case of failures and troubleshooting their systems and applications.