Continuous Integration (CI): Automating the integration of code changes from multiple contributors into a single software project.
Key practices include frequent code commits, automated builds, and testing.
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CI/CD Cheatsheet
A comprehensive cheat sheet covering essential CI/CD concepts, tools, best practices, and workflows for modern DevOps.
CI/CD Fundamentals
Core Concepts
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Continuous Delivery (CD): Extending CI to automatically prepare and release code changes to production or pre-production environments. Focuses on ensuring the software can be reliably released at any time. |
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Continuous Deployment (CD): Further automating CD to automatically deploy code changes to production without explicit approval. Requires robust monitoring and testing to ensure stability. |
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Pipeline: An automated workflow that defines the stages of the CI/CD process, including build, test, and deployment. Pipelines ensure consistency and repeatability. |
Benefits of CI/CD
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Faster Time to Market |
Rapidly deliver new features and updates to users. |
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Reduced Risk |
Automated testing and deployment minimizes errors. |
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Improved Quality |
Continuous testing ensures code meets quality standards. |
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Increased Efficiency |
Automated processes free up developer time. |
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Enhanced Collaboration |
CI/CD fosters better communication and cooperation between development and operations teams. |
Key Metrics
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Deployment Frequency: How often code is deployed to production. |
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Lead Time for Changes: Time taken from code commit to code in production. |
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Mean Time to Recovery (MTTR): Average time to restore service after a failure. |
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Change Failure Rate: Percentage of deployments causing a failure. |
CI/CD Tools
Build Automation
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Jenkins: An open-source automation server widely used for CI/CD. Offers extensive plugins for various tools and platforms. |
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Maven: A build automation tool primarily used for Java projects. Manages dependencies and provides a standard build lifecycle. |
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Gradle: Another build automation tool, also popular for Java, Kotlin, and Android projects. Offers flexibility and performance improvements over Maven. |
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Make: A build automation tool used primarily for C/C++ projects. |
Version Control
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Git |
Distributed version control system for tracking code changes. Platforms like GitHub, GitLab, and Bitbucket provide Git repositories. |
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GitHub Actions |
CI/CD directly integrated into GitHub repositories. |
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GitLab CI/CD |
CI/CD directly integrated into GitLab repositories. |
Configuration Management
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Ansible: An automation tool for configuration management, application deployment, and task automation. Uses a simple, human-readable language (YAML). |
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Chef: A configuration management tool that uses Ruby-based DSL (Domain Specific Language) to define infrastructure as code. |
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Puppet: Another configuration management tool that uses a declarative language to define the desired state of infrastructure. |
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Terraform: An infrastructure as code tool for building, changing, and versioning infrastructure safely and efficiently. |
CI/CD Best Practices
General Practices
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Automate Everything: Automate all repetitive tasks, including build, test, and deployment. |
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Version Control Everything: Keep all code, configurations, and scripts in version control. |
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Test Early and Often: Implement comprehensive testing throughout the CI/CD pipeline. |
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Monitor and Alert: Implement robust monitoring to detect and respond to issues quickly. |
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Small, Incremental Changes: Break down large changes into smaller, manageable increments. |
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Infrastructure as Code (IaC): Manage and provision infrastructure through code. |
Testing Strategies
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Unit Tests |
Test individual components or functions in isolation. |
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Integration Tests |
Test the interaction between different components or services. |
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End-to-End Tests |
Test the entire application workflow from start to finish. |
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Performance Tests |
Measure the performance and scalability of the application. |
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Security Tests |
Identify and mitigate security vulnerabilities. |
Pipeline Stages
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Source: Code repository (e.g., Git) |
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Build: Compile code, package dependencies, and create artifacts. |
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Test: Run automated tests (unit, integration, end-to-end). |
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Package: Create deployable packages (e.g., Docker images). |
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Deploy: Deploy packages to staging or production environments. |
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Monitor: Track application performance and health. |
CI/CD in the Cloud
Cloud Platforms
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AWS: AWS offers a wide range of services for CI/CD, including CodePipeline, CodeBuild, CodeDeploy, and ECS/EKS for container orchestration. |
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Azure: Azure provides Azure DevOps for CI/CD, including Azure Pipelines, Azure Boards, and Azure Repos. It also offers AKS for container orchestration. |
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GCP: GCP offers Cloud Build for CI/CD, along with Google Kubernetes Engine (GKE) for container orchestration. |
Containerization
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Docker |
A platform for building, shipping, and running applications in containers. Containers provide a consistent and isolated environment for applications. |
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Kubernetes |
An open-source container orchestration platform for automating deployment, scaling, and management of containerized applications. |
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Serverless |
Cloud functions like AWS Lambda, Azure Functions, and Google Cloud Functions enable event-driven CI/CD workflows. |
Cloud-Native CI/CD
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Leverage Managed Services: Utilize cloud provider’s managed CI/CD services (e.g., AWS CodePipeline, Azure Pipelines, GCP Cloud Build) for simplified setup and maintenance. |
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Embrace Infrastructure as Code: Define and manage cloud infrastructure using tools like Terraform or CloudFormation for automated provisioning and configuration. |
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Automate Security Scans: Integrate security scanning tools into the CI/CD pipeline to identify vulnerabilities early in the development process. |
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Implement Blue/Green Deployments: Use blue/green deployments or canary releases to minimize downtime and risk during deployments. |