Introduction
The continuous integration/continuous deployment (CI/CD) pipeline consists of automated steps that help deliver new software versions more efficiently via automation. Simply put, CI/CD automation improves software delivery and enables organizations to build high-quality codes faster and more securely.
While CI simplifies integrating source code and software development, enables version control, and promotes seamless collaboration through automation, CD helps with automated testing and deployment. CD reduces the time to deliver and deploy the software and decreases the number of tools used to manage the application lifecycle.
Adopting CI/CD pipeline best practices ensures increased productivity and efficiency, reduced risks of application defects, practical testing and monitoring, and faster code changes.
This cheatsheet discusses the best practices for CI/CD pipelines in detail.
Foundation of a Robust CI/CD Pipeline
CI/CD pipeline automates the software’s building, testing, and deployment after it passes the code commits in test suites. To ensure efficiency in the process, building a solid pipeline is inevitable. Here are a few critical best practices to create a robust CI/CD foundation.
Version Control Integration
Git workflows and branching strategies
Defining Git workflows and branching strategies for the different stages of software development streamlines the version control integration process and helps maintain code quality. The right branching strategies, code reviews, and pull requests reduce conflicts and make it easier to roll back to previous versions.
Commit hygiene and semantic versioning
Frequent and early commits (atomic commits) allow developers to get rapid feedback based on which code changes can be made. Commit hygiene, especially in large projects with huge teams, is essential. There are several best practices to maintain commit hygiene, such as:
- Keeping the commits focused on one primary change affecting the codebase
- Following established patterns in a codebase and maintaining commit consistency
- Crafting detailed commit messages, etc.
Further, semantic versioning is also one of the best CI/CD practices as it helps developers understand the impact of code changes. Automatic semantic versioning significantly helps with rapid software deployment and reduces the risk of human error.
Automated Testing Strategies
Unit, integration, and end-to-end testing
In CI/CD, thorough testing of all code units is essential. The best-automated testing practice is performing unit, integration, and end-to-end tests.
- While unit testing is the fastest testing form, it lets developers verify if the units of code are operating as required.
- Integration testing verifies the behavior of multiple software parts within the program. In short, it verifies the workings of integrated units.
- Lastly, perform end-to-end testing to ensure the system meets the functions as intended.
Test coverage and regression testing
Another CI/CD best practice is to measure how much of the code has been covered by automated testing. Test coverage ensures that the tests performed are comprehensive and the tested codes are well-protected against potential risks.
Regression testing is another CI/CD practice that involves retesting the already tested codes to ensure that the changes made do not trigger new defects in the system. Regression testing maintains codebase integrity and prevents the re-emerging of already-resolved issues.
Build Automation
Build tools and configurations
Building development, testing, and deployment automation requires the right CI/CD tools. Popular CI/CD tools include Jenkins, Travis CI, GitLab, Circle CI, etc. These tools can be configured to automate processes and ensure consistency across different environments.
Artifact management and dependency caching
While version control systems manage dependencies and artifacts, like compiled code, build logs, and test outcomes, the CI/CD pipeline also needs dependency caching. Since developers need to install the same dependencies during the build stage, storing the data helps in quick retrieval. Thus, caching dependencies reduce build times, improving efficiency.
Streamlining CI/CD Workflow
Setting up continuous integration requires strategies that can streamline the integration workflows. Here’s what organizations can do to streamline CI/CD operations.
Parallelization and Concurrent Builds
Maximizing efficiency through parallel execution
Running tasks simultaneously can maximize process efficiency. With concurrency, teams can complete seven tasks (each taking 1 minute to complete) in 1 minute instead of 7 minutes. The tasks can still be done simultaneously if the parallelism is set to 3. With parallelism, the team can run three copies of each of the seven tasks to be completed in a minute, meaning 21 tasks can be finished within a minute.
Strategies for managing dependencies and ensuring consistency
A solid versioning strategy can ensure effective management of dependencies and consistency. Versioning schemes like semantic and lock files, which record the exact dependency versions during development, ensure consistent builds across various environments.
Further, developers can use Infrastructure as Code (IaC) scripts to set up development environments, mirroring production faster. This strategy also ensures consistency across different development stages and reduces issues related to the production environments.
Continuous Integration Best Practices
Frequent and small commits
Regular and atomic commits help produce better-quality software. Each commit triggers a set of automated tests to offer quick feedback on the change made to the codebase. Committing regularly ensures teams stay aligned, promotes effective collaboration, and reduces conflicts in integrating complex changes.
Integration testing as a gatekeeper
Integration testing involves the gradual integration of software components and tests performed to see how these components work as a unified group. In an agile environment, performing integration testing before unit testing ensures rapid fixing of the more significant issues, unlike in the waterfall development model.
Moreover, since integration testing analyzes the workings of different software components, it can help make informed decisions regarding production.
Ensuring Code Quality in the CI/CD Pipeline
Technical debt wastes 23-42% of the developers’ time, which is a risk for businesses. Here are the best practices to ensure perfect code with fast delivery.
Code Quality Checks
Static code analysis
Tools like Veracode, DeepSource, and Codacy use static code analysis to check the code quality without executing it. These tools can efficiently identify bugs, vulnerabilities, and errors before they significantly impact a broader scale. Static code analysis tools can ensure that codes meet the defined standards before deployment to production.
Code review automation
Developers can automate specific aspects of code review, like feedback on code complexity, performance, and maintainability, to reduce manual work. Automation in code review can save time while helping developers optimize code and focus on more critical tasks simultaneously.
Incorporating Security Scans
Integrating security checks into the CI/CD pipeline
Automated security checks, like dynamic scans, running static analytics tools, or penetration tests, within the CI/CD pipeline quickly detect system vulnerabilities. Developers can reduce the risk of exposing system data to malicious cyber-attacks. Moreover, automated security checks in CI/CD best practices can accelerate feedback and problem-solving, ensure security compliance, enhance collaboration, and reduce costs.
Automated vulnerability assessments
These assessments spot the potential issues in the codebase. Tools like Checkmarx and SonarQube can help with dependency analysis, vulnerability detection, and security scanning for different frameworks. Hence, developers can identify potential issues faster and remediate them immediately.
Deployment of Best Practices in CI/CD
Seamless software deployment demands implementing strategies that ensure efficient and rapid deployment and minimum risk.
Blue-Green Deployment Strategies
Minimizing downtime and risk during deployment
Blue-Green deployment is about deploying a new code in a separate environment (the “blue” environment) while the current environment (the “green” environment) is still operational. Implementing this strategy, developers can gradually shift the traffic from the green environment to the blue once the blue environment has been thoroughly tested and validated. This blue-green strategy reduces downtime and risks as the new environment is thoroughly tested before going live.
Rollback mechanisms and version control in deployment
In application deployment, a robust version control system like Git is crucial. Implementing rollback mechanisms in deployment helps developers quickly access the previous stable version if there are issues in the new environment. Tools like Git help developers monitor changes in the codebase and roll back to earlier versions if needed.
Environment Configuration Management
Infrastructure as Code (IaC) principles
IaC automates IT resource provision and management through code. Through IaC, DevOps teams can maintain flexibility and consistency in environments.
- IaC principles include immutable infrastructure, where one infrastructure is replaced with a new one created from a familiar image, with required changes to the latest version.
- Another IaC principle that helps with environment configuration management is idempotency. This principle means regardless of how many times developers run IaC and their starting state, they will end up with the same end state. This IaC principle simplifies infrastructure provisioning and reduces the chances of outcome inconsistency.
Managing configuration drift and environment consistency
Configuration drift happens when the environment configuration changes over time, resulting in potential issues and inconsistency. One way to manage configuration drift is to track environment changes and ensure they align with the desired state. Configuration management tools like Ansible and Puppet can help developers manage configuration drifts. With these tools, developers can ensure a consistent environment free from drifts, minimize the risk of errors, and improve system stability.
Monitoring and Feedback Loops
It is essential to measure the effectiveness of CI/CD pipelines. Developers can track CI/CD process performance and improve using monitoring tools and feedback systems.
Real-time Monitoring
Implementing monitoring tools in the CI/CD pipeline
Monitoring tools provide real-time visibility into the CI/CD pipeline and help with root cause analysis and faster troubleshooting. Observability and monitoring tools like Grafana, Middleware, or Datadog can help developers get end-to-end visibility of the entire application infrastructure and processes. They can identify bottlenecks, performance issues, and pipeline defects in real time and get them resolved quickly.
Proactive issue identification and resolution
As mentioned above, monitoring and observability tools enable proactive identification of potential issues, and developers can take corrective measures before they impact users significantly. Automated alerts and notifications help inform developers of system issues, helping them resolve the problems as they occur without any delay.
Continuous Feedback
Utilizing feedback for process improvement
Continuous feedback is essential in improving the CI/CD pipeline. It helps identify pipeline inefficiencies or quality issues and make amends to improve overall quality. DevOps teams should seek and act on feedback to refine the pipeline processes, workflows, and tools to ensure effective and more efficient software delivery. Incorporating feedback systems into the development process and actively working on them can enhance software quality and user satisfaction immensely.
Metrics and Key Performance Indicators (KPIs) for evaluating CI/CD success
Another important continuous feedback best practice in CI/CD is establishing metrics and KPIs to assess how well the CI/CD pipeline is performing.
Metrics such as build success rate, deployment frequency, lead time, and mean time to recovery provide insights into the reliability and efficiency of the pipeline. Additionally, KPIs should enable developers to measure the impact of the CI/CD pipeline on the business’s overall software delivery performance and help spot areas for improvement.
CI/CD Pipeline Scalability
The next step after successfully building a CI/CD pipeline is to scale. The pipeline must be capable of accommodating the growing needs of a business.
Handling Increased Workloads
Scalable infrastructure considerations
Considering the scalability of the infrastructure supporting the CI/CD pipeline is vital to ensure it handles increased workload well.
- Cloud-based infrastructures like Microsoft Azure or Amazon Web Services (AWS) are scalable and can be provisioned and de-provisioned as necessary.
- Further, orchestration and containerization tools like Docker or Kubernetes can help scale infrastructures to manage increasing resources efficiently.
DevOps teams can ensure consistent and reliable application performance with scalable infrastructure tools.
Strategies for managing larger codebases and teams
Larger codebases and teams require specific strategies for managing complexities and reducing risks.
- Implementing code review processes like pull requests can help ensure that code changes are reviewed and evaluated thoroughly before merging them into the primary branch.
- Version control systems, like Git, can help manage codebase changes and ensure the code is up-to-date.
- Another strategy that teams can implement is using collaboration tools like Slack to help teams communicate and coordinate tasks seamlessly.
These strategies ensure that the complexities of growing teams and codebases are handled efficiently while ensuring enhanced pipeline performance.
Case Studies and Real-world Examples
Considering case studies highlighting the successful CI/CD pipeline implementation, one famous real-world example is Netflix.
Netflix’s CI/CD pipeline is the backbone of its tech stack. The process is highly automated and involves moving code changes rapidly and reliably from development to production.
Here are the critical components of Netflix’s CI/CD pipeline.
Build and Test Automation
Spinnaker is an open-source CD platform that automates Netflix’s build and test processes. It easily integrates with other tools of the streaming platform’s tech stack, like Jenkins, to enable automated testing and deployment.
Deployment Automation
Netflix uses a combination of AWS and Spinnaker to deploy code changes to production. While Spinnaker handles the orchestration of the deployment process, AWS gives the infrastructure for running the application. This ensures reliability and speed in deployment.
Code Repository
Netflix’s codebase is centrally stored in GitHub. Developers work on feature branches, and changes are reviewed through pull requests to ensure the codes are thoroughly reviewed before merging them into the codebase.
Canary Testing
Netflix has a canary testing system evaluates new changes and features in a production-like environment before rolling them out to users. Canary testing allows rolling out changes to fewer users and monitoring them to identify issues. This ensures minimizing the impact of the problems of a more extensive user base.
Monitoring and alerting
Netflix uses tools like Spectator and Atlas to monitor infrastructure and applications in real-time. The monitoring tools provide accurate insights and alert teams as issues arise in the system. It helps Netflix address these defects, ensuring maximum user satisfaction quickly.
Branching model
Developers can create branches for each feature in Netflix’s feature branch workflow. Following review and approval, these branches are merged into the main branch. The code changes review policies in Netflix ensure that they are adequately reviewed and tested. For instance, Netflix has a policy: “All pull requests must pass automated tests before they can be merged into the main codebase.” Further, pull requests undergo approvals from several developers before they get merged.
Further, Netflix uses the trunk-based development approach, frequently merging changes to the main codebase. This enables quick integration of new features and changes while ensuring codebase reliability and stability.
All in all, Netflix’s CI/CD pipeline is designed to enable the streaming platform to launch new features quickly, minimize risks, and maintain user satisfaction.
Conclusion
As discussed, several CI/CD pipeline best practices exist for each pipeline stage — from development to deployment, monitoring, and feedback. These best practices are crucial to building a robust CI/CD pipeline and its successful performance over time.
Along with the implementation of the CI/CD pipeline, best practices like committing early and often, integration testing, version control systems, continuous feedback, real-time monitoring, etc., it is also critical to choose the right tools to carry out the operations.
Adapting each of these best practices will not only ensure a successful CI/CD pipeline but will also improve the software development processes. Thus, the CI/CD best practices will directly impact software delivery quality and business ROI.
Resources
- CI/CD Pipeline
- Website: CI/CD Pipeline practical guide
- A comprehensive guide that covers the basics and advanced concepts of CI/CD Pipeline
- CI/CD Best Practices
- Website: CI/CD best practices for your DevOps team’s success
- A list of the Top 8 CI/CD best practices for your DevOps team’s success
- Learning CI/CD Tools
- Website: Learning CI/CD Tools
- Best Practices for Application and IaC
- The CI/CD Pipelines Best Practices Guide by Jenkins
- Website: Pipeline Best Practices
- Jenkins, one of the most popular CI/CD automation tools, offers a guide outlining best practices for setting up and managing CI/CD pipelines.
- The Twelve-Factor App
- Website: The Twelve-Factor App
- Although not specifically about CI/CD, this methodology outlines principles for building modern, scalable web applications, many of which align closely with CI/CD practices.
