CI/CD Pipeline Best Practices for Automation and Trunk-based Development

CI/CD pipeline best practices

CI/CD Pipeline Best Practices for Automation and Trunk-based Development

CI/CD pipeline best practices center on automating everything possible from code to production, favoring trunk-based development over branch-per-environment, and building a single artifact that moves through all environments. These principles reduce manual errors and keep delivery consistent as you scale.

The core workflow involves storing all code, configuration files like Kubernetes YAML, and pipeline definitions in Git. Continuous integration triggers automated builds and tests on every change, while continuous delivery or deployment automates the promotion of validated code to environments like DEV, UAT, and PROD.

Tooling flexibility is expected. Teams can choose from Jenkins, GitHub Actions, ArgoCD, Azure DevOps, or similar platforms based on their architecture and budget. The concepts stay the same regardless of the specific tools selected.

Core practices

  1. Automate everything possible Automate testing, building, and deployment to reduce manual errors and speed delivery.
  2. Build once, deploy everywhere Create a single artifact and promote it through DEV, UAT, and PROD for consistency.
  3. Implement comprehensive testing Run unit, integration, and security scans throughout the pipeline.
  4. Favor trunk-based development Use a single main branch and drive promotions via tags or approvals.
  5. Avoid branch-per-environment Separate branches per environment do not scale and cause inconsistencies.
  6. Store everything in Git Keep all code, Kubernetes YAML, and pipeline definitions in Git repositories.
CI/CD Pipeline Best Practices for Automation and Trunk-based Development — infographic

Core Principles for Effective CI/CD

Automate Everything Possible: Automate testing, building, and deployment to reduce manual errors and speed up delivery. "You’re giving the responsibility of 90% of the steps between building software and putting it on a machine to a computer."
Build Once, Deploy Everywhere: Create a single artifact that is promoted through all environments (DEV, UAT, PROD) to ensure consistency. "Your "idea” is the standard. Rebuilding per env is insane."
Implement Comprehensive Testing: Integrate various levels of testing, including unit, integration, and security scans, throughout the pipeline. "Tests would be run during the docker build process ideally, but could be in the .gitlab-ci.yml."

Branching and Source Code Management

Favor Trunk-Based Development: Use a single main/master branch for all development, driving promotions via tags or approvals. "Definitely use trunk based development with a release branching strategy."
Avoid Branch-Per-Environment: Maintaining separate branches for each environment can be difficult to scale and lead to inconsistencies. "Branch-per-environment does not scale. It barely works for 2 environments, nevermind 20+"
Utilize Git for Version Control: Store all code, configuration files (e.g., Kubernetes YAML), and pipeline definitions in Git repositories. "All code, kubernetes yaml, and jenkins pipelines are in git repos"

Key Stages and Tools

Continuous Integration (CI): Focus on automating code integration, building, and initial testing upon every change. "Continuous Integration means something like "every time I make a change to my code, I put it together with the latest version of everyone else's code, then test it to make sure it works together"."
Continuous Delivery/Deployment (CD): Automate the delivery of validated code to various environments, potentially directly to production. "Continuous Deployment means "every time I make a change to my code, it goes to production as fast as possible"."
Tooling Flexibility: The specific tools (e.g., Jenkins, GitHub Actions, ArgoCD, Azure DevOps) depend on the project, architecture, and team preferences, but the underlying concepts remain consistent. "There isn't the holy grail set of tools you should be using. It all depends on what apps your org has and how willing they are to spend money."

Does focusing on automation and trunk-based development align with your current CI/CD goals?

Bottom line

Users highlight that CI/CD pipeline best practices focus on automating software delivery from code to production with efficiency and reliability. This involves a suite of practices and tools tailored to an organization's specific needs and tech stack.

FAQ

What is the build once deploy everywhere strategy in CI/CD?
You create a single artifact once and promote that same artifact through all environments like DEV, UAT, and PROD. Rebuilding separately for each environment creates inconsistencies and is considered a poor practice.
Should I use branch per environment in CI/CD?
No. Branch-per-environment does not scale well and leads to inconsistencies. It barely works for two environments and becomes unmanageable with many more. Trunk-based development with a release branching strategy is preferred.
What tests should run in a CI/CD pipeline?
Pipelines should integrate unit tests, integration tests, and security scans throughout the process. Tests can run during the Docker build step or directly in pipeline definition files like .gitlab-ci.yml.
What is the difference between continuous integration and continuous deployment?
Continuous integration means every code change is merged with the latest version of everyone else's code and tested to ensure it works together. Continuous deployment means every validated change goes to production as fast as possible.
What should be stored in Git for CI/CD pipelines?
All code, configuration files such as Kubernetes YAML, and pipeline definitions like Jenkins pipelines should live in Git repositories. This keeps everything version controlled and consistent.
Which CI/CD tools should I use?
There is no single best set of tools. The choice between Jenkins, GitHub Actions, ArgoCD, Azure DevOps, or others depends on your applications, architecture, and how willing your organization is to spend money.

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