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Implementing a DevOps Pipeline for Seamless Feature

Devops Pipeline


DevOps Pipeline

Based on customer feedback, developers always work towards adding new features and enhancing the How do developers add this feature to the source code and deploy it? How do they find out if the changes made to the source code will not affect the existing functionality of the application? A deployment pipeline helps developers to deal with all these queries.

A deployment pipeline breaks up the build into stages. Developers can track issues in the early stages and fix them quickly. Deployment pipelines are a central part of the development life cycle. It is responsible for detecting performance, security, or usability changes that may cause problems in production. A deployment pipeline provides clear visibility about the production changes to the different teams involved and allows the teams to work collaboratively with a thorough audit trail.

A deployment pipeline ensures that only changes that do not affect overall performance are implemented and deployed each time developers try to deploy the build. Following are the steps to setting up a basic deployment pipeline:

  • Set up a build server.
  • Set up a few test suites.
  • Add a deployment step.


DevOps Pipeline Creation Tools

There are different tools available on the market for creating deployment pipelines.


1. Subversion

Subversion: Apache Subversion (SVN) is an open-source version control system. Subversion maintains changes made to files such as source code, web pages, and other documentation as different versions. At any time, older versions of the file can be recovered to compare the changes or for any other reason.

An important feature of Subversion is to provide collaboration across the globe. So, two people making simultaneous changes to the same file will receive a message and they can collaborate among themselves and final changes will be committed. At any point, the previous version of the file can be found and changes to the new file can be discarded.


2. Another neat tool (ANT)

Apache ANT is a Java-based tool for automating software build processes, which was released as a replacement for the Unix Make build tool. In Apache Ant, build files are scripted in XML, so it is easy to understand and flexible. Figure 16.3 shows some ANT functions.

Several built-in tasks in Ant enable developers to compile, assemble, test, and run Java applications. In addition, developers also use Ant to build non-Java applications, such as C or C++ applications.


3. Jenkins

Jenkins is open-source automation software written in Java. Jenkins helps automate tasks such as Continuous Integration, Continuous Testing, Continuous Deployment, and the technical aspects of Continuous Delivery. It will be installed on the server where a central build is present. Jenkins supports version control tools, such as Accu Rev, CVS, Subversion, Git, Mercurial, Perforce, ClearCase, and RTC. It can run programs written in other tools such as Apache Ant, Apache Maven, and SBT.

In Jenkins, whenever developers commit a version of source code, builds can be triggered. Builds can also be triggered by scheduling via a cron-like mechanism and when a specific build URL is requested. In addition, when one build in a queue completes, the next build is triggered.

After installing Jenkins, users can start creating a pipeline using the different plugins. Users can use Jenkins plugins to implement and integrate their Continuous Delivery pipelines into Jenkins.

Users need to create a Jenkins file, which is a text file where users define a Jenkins pipeline. This file is then checked into source control. Jenkinsfile automatically creates pipelines for all branches and Pull Requests. This file enables you to review code on the Pipeline and helps with the audit trail for the Pipeline. In addition, team members can use this file to edit the pipeline in the future. Defining the pipeline in a Jenkins file and checking it in source control is always recommended rather than defining it in the Web UI.


4. Puppet

Puppet is an open-source automation tool that runs on Unix-based and Microsoft Windows-based systems. Puppet information is stored in files named 'Puppet manifests'.

Puppet automates the process of inspection, delivery, and operation of software. In Puppet, system information is identified via the Factor utility. The Puppet manifests are compiled into a system-specific catalog, which contains resources and resource dependencies. These dependencies are applied to the target system. Puppet then reports on the actions it takes.

There are two versions of Puppet - Puppet Enterprise and Open Source Puppet. Puppet Enterprise provides GUI, API, and command line tools for node management along with the basic functionalities of Open Source Puppet.

Puppet enables organizations to know their detailed infrastructure. It gives a detailed overview of how all the physical components, virtual networks, and cloud infrastructure within an organization are managed. Puppet ensures security and consistency by keeping compliant and giving complete control to teams for making changes as per business needs.

System administrators can use Puppet to inspect, deliver, operate, and future-proof applications around the world. Puppet supports an easy-to-use language, which enables developers to define their needs and infrastructure. Developers can thus share, test, and change applications and cloud platforms. Following are the three basic needs why organizations would use Puppet:

  • To speed up and become agile, so that users can get a faster and better software experience.
  • To automate different tasks to achieve reliability, repeatability, and predictability.
  • To get a complete visible, traceable, and transparent system.

The Puppet tool collects system information to create a customized system configuration with the help of its set of modules. The different modules of Puppet contain parameters, conditional arguments, actions, and templates. There are two ways organizations use Puppet - either as a local system command line tool or in a client-server environment, in which the server acts as the Puppet master. The master then uses the Puppet agent to apply the configuration to multiple clients. The newly provisioned systems can thus be automatically configured in this way.

The following steps are used to define a Puppet workflow to apply configuration to a system:

  • The puppet agent on each system first collects facts, such as hardware, operating systems, package versions, and other information about each system. This information is sent to the puppet master.
  • In reply, the Puppet master creates a custom configuration called a catalog for each system, which is then sent to the Puppet agent.
  • The Puppet agent uses the catalog configuration of the system.
  • In case there are any unsuccessful changes due to the new configuration, the Puppet agent sends the report to the Puppet master.
  • Puppet's API makes these reports available to third-party applications.

The Puppet Enterprise tool simplifies the automation and configuration process. It is capable of making quick and repeatable modifications to the configuration. Puppet also automatically enforces the consistency of systems and devices. Puppet Enterprise provides the following functionalities:

  • Cycle times are minimized. So, more software can be deployed.
  • Changes can be implemented fast.
  • Configuration needs to be defined only once, which can later be applied to all the machines on the network.
  • Configuration drifts can be detected and corrected automatically without the developer's intervention.

Puppet has four use cases - infrastructure, configuration management, failover, and deployment.

1. Puppet infrastructure:

A large network comprises several servers. Puppet can be used to manage different types of servers, such as private or public clouds, data centers, or any workstation. Puppet modules can be used for defining resources within the code. Puppet manifests can be used to define this purpose.


2. Configuration management:

Puppet configuration management defines all the modules installed on the servers in a single location. This simplifies the deployment process for new servers and maintains consistency. In case any changes are made to the source code, they are version-controlled and documented.


3. Failover:

The Puppet Web Ul manually removes nodes from the load balancer rotation. The console RAKE API is also used for the same purpose. Users can make changes easily using the UI. The error rate is low while browsing through the UI. If one of the nodes fails, users can use the API to automate failover and continue operating.


4. Deploys:

Puppet enables developers to customize the deployment process as per the situation or need.


5. Chef

Chef is a configuration management tool that ensures that all relative files and software are present on the appropriate machine, configured correctly, and working as expected. Chef works fast even if users have thousands of servers. This is because Chef manages servers by converting infrastructure into flexible, versionable, human-readable, and testable code. Developers need not change anything manually, the machine setup is described in a Chef recipe and everything is performed automatically.

A cookbook is a collection of recipes; only one task should be included in each cookbook. However, a cookbook can include more than one server configuration. For example, the cookbook for the configuration of a Web application with a database will have two recipes; one for each part.

The cookbooks are stored on a Chef server. When a new Chef client node is introduced into the network, the recipes are sent to this new node so that it can perform the configuration itself.

The client keeps an eye on it continuously to ensure that there are no changes made to the configuration. In case of any changes, the client handles the changes. In case, there are any changes to the recipe, patches and updates are released for deploying the changes. Chef automates the configuration over the cloud irrespective of its size.

Users interact with Chef from their respective workstations, on which users create and test cookbooks with the help of tools, such as Test Kitchen. Users then interact with the Chef server with the help of tools such as knife and other Chef command line tools. Chef manages different nodes, such as physical machines virtual machines, or the cloud. On each node, the Chef client is installed and it performs automation on that node.

The following are some major components of a Chef:

  • Chef Development Kit (Chef DK): It is a package of tools that provides the following tools:
    -- Chef-client
    -- Command line tools:

  • Chef: This tool enables you to work with items in a chef-repo. In chef-repo, cookbooks are authored, tested, and maintained. From here, the policy is uploaded to the Chef server.

  • Knife: This tool enables to interact with nodes on the Chef server. Nodes can be physical machines, virtual machines, clouds, or network devices.
    -- Testing tools, such as Test Kitchen, ChefSpec, Cookstyle, and Food Critic
    -- Chef provisioning
    -- Other tools required to author cookbooks and upload them on the Chef server

  • Chet Server: It is responsible for data configuration. Cookbooks are stored on the Chef server. Cookbooks are the policies uploaded by users, which are applied to nodes. The chef server also stores metadata. Metadata describes each registered node managed by the chef-client. Nodes query the Chef server for configuration details through the chef-client. Configuration details can be recipes, templates, and file distributions.

  • Chef-client: Chef-client is installed on nodes, and it accesses the Chef server from the node to get configuration data. The Chef-client creates cookbooks and defines recipes with the help of Ruby, which is a reference language.

  • Cookbooks and Recipes: Cookbooks define scenarios and it is responsible for configuration and policy distribution. A cookbook contains recipes, which specify the resources to use and the order of their usage. It also contains attribute values, file distributions, templates, and metadata. Workstations upload cookbooks on the Chef server.

    A Chef recipe is a file stored in the cookbook. It groups related resources. The structure of the recipe is defined in the Chef cookbook. Cookbooks and recipes are written using Ruby.

    Chef Automate is a continuous automation platform that provides improved deployment speed and efficiently builds a transparent code base. It also reduces costs and creates comprehensive analytics.


Build, Manage, and Audit:

  • Creates reusable building blocks used in multiple stacks.
  • Checks the code with the state of the infrastructure being managed.
  • Tests that the systems remain in compliance.
  • Scans for known vulnerabilities continuously.
  • Detects versions of installed shells on the systems and reports if any modifications are done.

Collaborate:

  • Developers validate their code on non-critical systems; thereby receiving fast feedback and identifying issues earlier.
  • Changes are tested against downstream dependencies. This prevents unexpected failures.
  • Tests dependencies automatically.
  • As changes are being made, they are tested with the same speed.

Deploy:

  • Builds automated pipelines to enable continuous delivery.
  • When systems are run, they pick up the changes made.

Continuous delivery becomes a speedy process with Chef Automate, which provides an automated workflow with the help of certain DevOps principles. Users can manage infrastructure as well as application code changes by using Chef Automate. Thus, it provides DevOps teams with a common platform throughout the development life-cycle. In case, the teams have different software deployment approaches, Chef Automate can be used to unify the release process.

Chef Automate can be used to upload new and updated cookbooks to the Chef server. It can also be used to publish new and updated cookbooks to a Chef Supermarket and release the source code into a repository. In addition, Chef Automate is capable of pushing source code into production servers in real-time.

6. Combining Tools To Form a DevOps Pipeline

A single tool might not be enough to achieve Continuous Integration Continuous Testing Continuous Deployment or all these tasks. A combination of different tools is used at different stages of software development. This practice gives the perfect results in a short time and software is always ready to release as per market expectations.


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