What Are CI And CD In DevOps And How Do They Work?
CI and CD stand for Continuous Integration and Continuous Delivery. In its most basic form, continuous integration (CI) is a modern software development process in which incremental code adjustments are implemented regularly and reliably. CI-triggered automated build-and-test stages ensure that code changes integrated into the repository are reliable. As part of the CD operation, the code is then provided swiftly and flawlessly. The CI/CD pipeline is a term used in the software industry to describe the automation that allows incremental code changes from programmers' desktops to be delivered rapidly and reliably to output.
What is CI/CD?
CI/CD is a set of principles, techniques, and capabilities that enable software changes of all sorts to be delivered to users in a timely, repeatable, and secure manner. This enables software developers to regularly integrate product or service updates, and IT and operations teams to deliver the security, standards, and confidence that businesses want.
What is Continuous Integration?
Continuous integration (CI) is an automated procedure for continuously merging software development changes. Continuous integration procedures automate the creation, testing, and verification of source code. Dealing with CI capabilities allows developers to speed up their code release cycles, reducing the likelihood of extended feature development cycles and the issues that come with it, such as merge conflicts.
A variant control system that can monitor changes and variants of software code is required for CI. Git is a well-known version control system. You can begin the CI process by using a git workflow. Devs working on a library use version control systems to submit changes to a code base. Once the changes have been approved, the developers working on the codebase incorporate them into the main code line.
The purpose of continuous integration is to create a packaged artifact that is ready to be deployed on a server or computer. A container image, WAR/JAR file, or any other executable packed code is an example of an artifact. From code commit to packed artifact, CI automates the process.
A developer will often commit some script to a version control system like Git, which will initiate the CI process. To assess code quality, this source is frequently scanned or analyzed with a static code analysis tool. The CI system will aim to package or build the code if the source code meets all checks, including unit testing. CI can also include marking or annotating specific parts of code, as well as managing resources like branches inside a version control system.
Enabling CI can be the first step toward your team creating high-quality code. CircleCI, Travis CI, Harness CI, and other continuous integration technologies are available. Please read our article on Continuous Integration Tools to understand more about the options, which range from open-source solutions to managed SaaS solutions.
What is Continuous Delivery?
The purpose of continuous delivery is to put a packed item into production. The whole delivery process, including deployment, is automated using a CD. CD tasks may involve provisioning infrastructure, tracking changes (ticketing), deploying artifacts, verifying and tracking those changes, and ensuring that these changes do not occur if any problems arise.
Certain parts of continuous delivery will be used by some firms to help them maintain their operational duties. A good example is employing a CD pipeline to handle infrastructure deployment. Some organizations will leverage their CD pipelines to coordinate infrastructure setup and configuration using configuration management automated processes such as Ansible, chef, or puppet.
How Do CI and CD Work?
A CI/CD pipeline may appear to be overhead, but it is not. It is essentially an executable definition of the procedures that any developer must take in order to deliver a new edition of a software product. Without an automated pipeline, developers would have to complete these processes manually, which would be significantly less productive.
Most software deployments go through the following stages:
Source Stage
A pipeline run is usually prompted by a source code repository. A change in code alerts the CI/CD tool, which launches the relevant pipeline. Other frequent triggers include workflows that are automatically scheduled or launched by the user and the outcomes of other pipelines.
Build Stage
We integrate the source code and its dependencies to create a runnable version of our product that we may distribute to our customers. Programs written in languages like Java, C/C++, or Go must be compiled, but Ruby, Python, and JavaScript do not.
Cloud-native software is frequently deployed with Docker, in which instance this step of the CI/CD pipeline creates the Docker containers.
Inability to deliver the build stage indicates a fundamental fault with a project's configuration, which should be addressed quickly.
Test Stage
During this phase, we run automated test cases to validate the accuracy of our code and the behavior of our product. The testing stage serves as a safety net, preventing easily reproducible errors from reaching end users.
The developers are responsible for writing tests. In test- or behavior-driven development, the ideal way to construct automated tests is to do that as we write new code.
This phase might span from seconds to hours, based on the scale and complexity of the project. Many large-scale projects conduct testing in stages, beginning with smoke checks that perform rapid sanity checks and progressing through end-to-end integration samples that test the complete system from the user's perspective. To decrease run time, an extended test suite is often parallelized.
Failure during the testing step reveals bugs in code that developers did not anticipate when writing the code. It is critical at this stage to provide developers with feedback as soon as possible, while the issue space is still fresh in their minds and they can sustain the state of flow.
Deploy Stage
We're ready for deployment of our code once we've created a runnable instance that has passed all of the required tests. There are generally numerous deploy environments, such as a "beta" or "staging" system for the product team and a "production" system for end-users.
Teams who have adopted the Agile development methodology, led by tests and real-time monitoring, typically send work-in-progress to a staging system for extra manual testing and assessment, then automatically deploy accepted changes from the top module to output.
Conclusion
To summarise, continuous integration packages and tests software releases and notifies developers if any testing phase fails. Continuous delivery refers to the automated distribution of applications, services, and other technological deployments to the runtime architecture, as well as the execution of additional tests.
Creating a CI/CD pipeline is common practice for companies that often modify their apps and require a dependable delivery method. Once in place, the CI/CD pipeline allows the team to focus on improving apps rather than the complexities of delivering them to diverse environments.