What is a pipeline?
Pipelines are agile DevOps workflows that transform application source code into versioned packages that can be deployed to any environment. It consists of one or more steps in which source code is transformed into a build that is tested and deployed in different environments until it finally reaches end users in a production environment.
Types of CI/CD Pipeline Pattern A
CI/CD pipeline is a runnable specification of the steps a developer needs to perform to deliver a new version of a software product. Without an automated pipeline, engineers would still need to perform these steps manually, and it would be less efficient.
The goal of a successful continuous delivery process is to minimize the time to bring high-quality software to life by practicing agile techniques and automating the entire delivery system. Furthermore, the strategy and structure of the pipeline is largely driven by the appropriate structure and schema. Therefore, pipelines need to be deployment-centric, as typical triggers are deployable artifacts.
Here are the 7 main types of CI/CD pipeline patterns:
1. Build and deploy the model
This model focuses primarily on building a prototype first and then deploying it. One of the benefits of this pattern is that you can deploy this artifact many times after building it once.
The build and deployment model is environment-independent, meaning it does not require any external environment-facing properties or packages. Other than that, this model packages everything together, including the core infrastructure code.
2. Pipeline as Code
Pipeline logic is coded, stored alongside infrastructure code, and containerized runners are used in this pattern. It is managed like normal application code and undergoes a similar review process and branching policy. In addition to this, executing pipelines on containers helps your CI/CD platform support a large number of workloads, although each workload includes its specific build environment to meet its requirements.
For the build environment, the source of the container image is the trusted Docker image. CI runner implementation is automated, unified and hands-free. Also, it can grow to meet demand and stand by during core hours. Subsequently, it minimizes unnecessary delays. Furthermore, secrets are kept outside the pipelines and their output is hidden, enhancing security.
3. Faster team feedback
Every commit automatically triggers the appropriate pipeline, and the build pipeline is specially optimized to report any issues faster. Here, they use parallelization to build pipelines for non-interdependent jobs for speed. Additionally, rapidly built pipelines can be dedicated to running critical jobs in the shortest amount of time.
In addition to this, each successful run produces static analysis results and versioned packages in this schema. You can even enable team notifications about pull request status in email, chat channels, dashboards, and other media.
4. Test Automation Patterns
Automating builds is a core practice in CI pipelines. Additionally, the build process can use a codebase-specific build tool. For example, you can use npm to build your Node Javascript application; a JVM based solution.
Additionally, modern testing frameworks can simulate application development using orchestration packages that need to be deployed in the application. Also, modifying test coverage to cover API changes is an exception to automated testing. Therefore, a pipeline dedicated to test automation may be the best choice.
5. Stable builds
In this mode, each code branch gets a complete staging environment for each branch that can be easily created and destroyed. Here, builds produce versioned packages that are deployed and triggered by automatic or manual events.
Furthermore, each software engineer can delete or trigger the staging environment at any time. CI runners use cloud-native capabilities to assume roles and get the right permissions for project completion.
6. Design parallel workflows
Before creating an application, development teams often practice continuous integration in small chunks of code. It is customary to set linear flow here. The whole thing could be over soon.
One of the common mistakes here is to apply similar linear thinking in the process from continuous integration to continuous delivery. So, if you process things in parallel, your continuous delivery system has to be innovative in handling dependencies.
7. Gripping product releases
You need to integrate tagged releases into production and automate the entire paperwork. In addition, standardized release thresholds and a standardized release process facilitate on-demand releases.
Automated releases leave a transparent paper trail that can be audited for quality and governance. Among other things, a release gate can call an external API and use the response to decide whether to continue an existing release or stop the process.