Software development involves various stages, right from coding to testing and deployment. Since several teams are involved in the entire development lifecycle, it becomes challenging to ensure seamless code changes to enhance the software.
To eradicate complications, developers can automate each stage of the application development lifecycle with CICD workflows. With CICD workflow, developers can linearly write code, integrate code, run test cases, and deploy changes to the software collaboratively in real-time, thereby assuring automatic and reliable software delivery processes.
In this article, you will learn about CICD workflow, different stages or phases of the CICD workflow, best practices to build an end-to-end CICD pipeline, and how to configure a sample workflow using Jenkins.
Table of Contents
Fundamental knowledge of application development lifecycle.
What is CI?
Continuous Integration(CI) is the process of automating the integration of multiple contributors’ code changes into a single software project. It’s a key DevOps best practice that enables developers to quickly merge code changes into a central repository from which builds and tests can be executed. Automated tools are used to check the accuracy of new code before it is integrated.
A source code version control system is central to the CI process. In addition to the version control system, other checks are performed, such as automated code quality tests, syntax style review tools, and so on.
To grasp the significance of CI, it’s helpful to first go over some of the issues that frequently arise due to the lack of CI. When contributing code to the end product without CI, developers must manually coordinate and communicate. Beyond the development teams, this coordination extends to operations and the rest of the company. Product teams must coordinate when features and fixes will be released in what order, as well as who will be responsible for each.
In a non-CI environment, communication overhead can become a complicated and entangled synchronization chore, adding unneeded bureaucratic costs to projects. As a result, code releases are slower and have a higher failure rate, as developers must be sensitive and thoughtful when working with integrations. As the engineering team and codebase grow in size, these risks multiply exponentially.
A disconnect between the engineering team and the rest of the organization can develop without a robust CI pipeline. It can be difficult to communicate between product and engineering. Engineering becomes a black box into which the rest of the team enters requirements and features, and from which they may or may not receive expected results. It will be more difficult for engineering to estimate the time it will take to deliver requests because the time it will take to integrate new changes will become an unknown risk.
CI is referred to as a DevOps and agile best practice in which developers integrate their code changes to the main branch or code repository early and often. By waiting until the end of a project or a sprint to merge all developers’ work, the goal is to reduce the risk of seeing “integration hell.” It helps teams meet business requirements, improve code quality, and increase security by automating deployment.
One of the most significant advantages of CI is that it saves time during the development cycle by identifying and resolving conflicts early on. Putting more emphasis on having a good test suite, it’s also a great way to reduce the amount of time spent fixing bugs and regression. Finally, it aids in the communication of a better understanding of the codebase and the features you’re creating for your customers.
Hevo a Fully-managed Data Pipeline platform, can help you automate, simplify & enrich your data replication process in a few clicks. With Hevo’s wide variety of connectors and blazing-fast Data Pipelines, you can extract & load data from 100+ sources(including 40+ sources) straight into your Data Warehouse or any Databases. To further streamline and prepare your data for analysis, you can process and enrich raw granular data using Hevo’s robust & built-in Transformation Layer without writing a single line of code!
GET STARTED WITH HEVO FOR FREE
Hevo is the fastest, easiest, and most reliable data replication platform that will save your engineering bandwidth and time multifold. Try our 14-day full access free trial today to experience an entirely automated hassle-free Data Replication!
What is CD?
Continuous deployment (CD) is a software engineering approach that involves automating the delivery of software functionalities on a regular basis. CD differs from continuous delivery, which is a similar approach in which software functionalities are frequently delivered and deemed potentially deployable but are never deployed.
For businesses looking to scale their applications and IT portfolio, continuous deployment has several advantages. First, it reduces time to market by eliminating the time lag between coding and customer value—which can range from days to weeks to months.
Regression tests must be automated in order to achieve this, removing the need for costly manual regression testing. For most changes, the systems that organizations put in place to manage large batches of production change, such as release planning and approval meetings, can be eliminated.
CD consists of instantiating a new version of a microservice and retiring the old version once it has drained all the requests in flight in an environment where data-centric microservices provide the functionality and where the microservices can have multiple instances.
When the Continuous Delivery step is extended, the Continuous Deployment phase emerges. The final stage in the pipeline is CD, which refers to the automatic release of any developer changes from the repository to production.
Continuous Deployment ensures that any change that makes it through the production stages reaches the end-users. There is no other way to prevent the deployment of new changes to the output than for the test to fail. This step eliminates the need for human intervention and speeds up the feedback loop with customers.
Because the entire deployment process is now automated, there is no need to stop development for releases. Because only small batches of changes are deployed, the release process is less prone to risks and is easily fixable in the event of any issues.
With each passing day, there is a continuous chain of quality improvements. The development process does not take as long as it used to, such as a month or a year. When we consider continuous deployment from a strategic standpoint, the goal is simple: to reduce the time it takes to write a piece of code, test it to ensure that it works correctly and does not break the application, deploy it to the live environment, and collect user feedback
For teams that do continuous deployment, automation is a critical driver of productivity. Before new code commits can be automated, a robust battery of automated tests must be programmed to ensure that they are functional, and additional tools are needed to abort the deployment process and trigger human intervention if the tests reveal lower-than-expected quality results or outcomes.
Continuous deployment introduces a level of risk to the software release process, as developers frequently commit untested code to the live environment, which could contain bugs. Organizations that use continuous deployment must develop real-time monitoring capabilities of the live environment so that any technical issues that arise after a new release can be quickly identified and addressed.
Understanding CICD Workflow
The CICD (Continuous Integration and Continuous Deployment) practice assures that the life cycle of a software application adheres to predetermined stages for writing code, building, testing, and deploying applications.
In other words, the CICD pipeline is a well-structured framework for developing a full-stack software project. The CICD approach provides continuous integration and delivery, leading to continuous deployment of a software application when a new update is released by the organization.
The CICD workflow or pipeline is made up of a collection of automated procedures and tools that enable developers and operation experts to collaborate on developing and deploying code to a production environment.
The phases of a CICD workflow or pipeline are depicted in the diagram above. At the beginning stage of the development pipeline, a developer writes a code and stores it in the source code repository.
The application is then built using code from the source repository in the following phase. After that, a series of unit tests are run on the newly built application. If any issues or bugs are found, the application is returned to the developer for rectification.
Then, in the UAT (User Acceptance Testing) or interactive testing environment, various testing methods are performed to ensure how the application works in the live or production environment. When the application has passed all test cases and is ready for production, it is transferred to the production environment and deployed for the end-user.
Stages of CICD Workflow
Before releasing a new software version, the CICD pipeline is divided into four major stages or series of steps. Failure at any level often results in notification via email, Slack, or other means, informing the responsible developers about the issue. However, following each successful deployment to production, the entire team is notified via the given medium of communication. The primary stages of CICD workflows are
This is the initial step in any CICD process. Any change in the application or a predefined flag in the source repository will trigger the CICD pipeline at this stage. This stage focuses on source control, including Version Control and Change Tracking. The most popular tools used at the source stage of CICD workflow are SVN, GIT, AWS CodeCommit, and Azure Repos.
This stage of the pipeline converts the source code and all of its dependencies into an executable/runnable instance. At this stage, you combine the source code and its dependencies in preparation for compiling the application. It is done primarily to create a runnable instance of software that can be shipped to the end-user.
Failing to pass the build step indicates a basic project misconfiguration, which should be addressed as soon as possible in the initial stage itself. This step also includes the processing of pipeline construction artifacts.
To centralize the storage process of building artifacts, use a centralized artifact repository like yarn, JFrog, or a cloud-based solution like Azure Artifacts. If there are any issues with the current build, you will be able to roll back to the previous build. Some of the CICD tools that are used in the build stage are Jenkins, Gradle, Azure Pipelines, Travis CI, and AWS Code Build.
In the testing stage of CICD workflow, various automated testing methods are used throughout to validate the application conditions, binaries, configuration, environment, and data.
In addition, automated tests such as integration tests, unit tests, and regression tests are run during the continuous integration and deployment processes.
The purpose of the testing stage is to prevent software bugs from reaching end users. The goal at this point is not just to ensure that all unit tests pass but also that the test standards are maintained and improved as the code base grows. The most popular testing tools used in the CICD workflow are Selenium, Jest, Appium, PHPUnit, Playwright, and Puppeteer.
The code is deployed to production at the end of the CICD workflows. When the application has completed all test case scenarios, it is ready to be deployed into the live or production environment.
This step can be modified to enable any deployment strategy, such as blue-green deployments, canary deployments, and in-place deployments.
End-to-end deployment protocols like Infrastructure Provisioning, Configuration, and Containerization using Terraform, Puppet, Docker, and Kubernetes are also included in the deployment stage. Some of the deployment tools used in the deployment stage of CICD workflow are AWS Code Deploy, Ansible, Azure Pipelines, Chef, and AWS Elastic Beanstalk.
Providing a high-quality ETL solution can be a difficult task if you have a large volume of data. Hevo’s automated, No-code platform empowers you with everything you need to have for a smooth data replication experience.
Check out what makes Hevo amazing:
Sign up here for a 14-day free trial!
- Fully Managed: Hevo requires no management and maintenance as it is a fully automated platform.
- Data Transformation: Hevo provides a simple interface to perfect, modify, and enrich the data you want to transfer.
- Faster Insight Generation: Hevo offers near real-time data replication so you have access to real-time insight generation and faster decision making.
- Schema Management: Hevo can automatically detect the schema of the incoming data and map it to the destination schema.
- Scalable Infrastructure: Hevo has in-built integrations for 100+ sources (with 40+ free sources) that can help you scale your data infrastructure as required.
- Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
Best Practices for Creating a CICD Workflow
The best practices outlined below describe the stages, techniques, methodologies, iterations, and so on that should be introduced or executed to achieve the most significant results from application development to deployment.
- Typically, CICD pipelines have limited capacity, which means that only a limited number of pipelines may run at any given time. As a result, often, resources are idle while developers wait in line for CICD to become available. To eradicate such complications, employ an auto-scaling and pay-as-you-go pricing model, which is a “serverless” CICD approach particularly introduced to enhance developers’ productivity.
- Difficulty with frequently managing CICD infrastructure or reusing existing setup causes friction that will suppress the overall development process. Having a programmable CICD tool that automatically integrates with existing development workflows and keeping all CICD configurations as code that can be reviewed, versioned, and restored by developers alleviates the complexity of managing CICD infrastructure regularly.
- While building CICD workflows, always use a consistent environment because when an application is tested and deployed in a handcrafted environment, it is more likely to fail in the production environment.
- Set up a better code center to run the standard set of tests against each branch to continuously assess the quality of your code.
- Before you begin the transition to CD automation, you must identify and analyze success measures. This will allow you to analyze your application consistently, making progress and refining it wherever appropriate during the deployment cycle.
How to Build a Sample CICD Workflow?
In the following steps, you will learn how to set up a basic CICD workflow with Jenkins.
- Step 1: Before you begin building CICD workflow with Jenkins, ensure that Jenkins is fully configured with the necessary dependencies.
- Step 2: Initially, login to the Jenkins workspace and click on New Item in the left side panel, as shown in the above image.
- Step 3: You have to name the CICD pipeline. Select the “Pipeline” menu and provide the pipeline’s name in the “Enter an item name” field. Click the OK button once you’ve given it a suitable name.
- Step 4: Now, you are all set to configure the CICD pipeline. The pipeline configuration in Jenkins is very straightforward. With the pipeline configuration screen, you can easily configure any end-to-end CICD workflows or pipelines by setting up the pipeline’s build triggers and other settings. The “Pipeline Definition” is the most significant section, as it allows you to describe the pipeline’s stages.
- Step 5: In this case, you use the basic “Hello World” pipeline script.
echo 'Hello World'
- Step 6: After entering the above-given code in the Pipeline Definition section, click on Apply and Save. Now, you successfully configured the sample CICD pipeline.
- Step 7: In the next step, you have to execute the previously configured pipeline.
- Step 8: Click on the “Build Now” menu in the left side panel. The pipeline stages are now being executed, and the results are displayed in the “Stage View” section, as shown in the above image.
- Step 9: By checking the Console Output section in the left panel, you can ensure that the pipeline was successfully executed.
- Step 10: After the pipeline is successfully executed, you can use the “Pipeline timeline” plugin to get a better visualization of pipeline stages. You just need to install the plugin, and you’ll see a “Construction timeline” option within the build stage. By Clicking on the “Construction timeline” option, you can see a timeline of the pipeline events, as shown in the above image.
By following the above-mentioned steps, you successfully configured and executed a CICD pipeline using Jenkins.
In this article, you learned about CICD workflow, different stages or phases of the CICD workflow, best practices to build an end-to-end CICD pipeline, and how to configure a sample workflow using Jenkins. However, you can further proceed with integrating the pipeline with external code repositories, applying automated testing methods, and implementing various deployment strategies like Blue-green and Canary techniques.
Integrating and analyzing your data from a huge set of diverse sources can be challenging, this is where Hevo comes into the picture. Hevo is a No-code Data Pipeline and has awesome 100+ pre-built integrations that you can choose from. Hevo can help you integrate your data from numerous sources and load them into a destination to analyze real-time data and create your Dashboards. It will make your life easier and make data migration hassle-free. It is user-friendly, reliable, and secure.
VISIT OUR WEBSITE TO EXPLORE HEVO
Want to take Hevo for a spin?
SIGN UP and experience the feature-rich Hevo suite first hand.