6.5 Continuous integration and continuous deployment (CI/CD)
13 min read•august 20, 2024
CI/CD is a game-changer in software development, automating the build, test, and deployment processes. It enables faster, more reliable software delivery, catching bugs early and streamlining releases. This approach is crucial in cloud computing, allowing teams to quickly iterate and respond to changing needs.
CI/CD offers numerous benefits over traditional deployment methods. It speeds up time-to-market, improves code quality through frequent testing, and boosts efficiency by automating repetitive tasks. This approach enhances collaboration and flexibility, enabling rapid responses to business requirements and customer needs.
CI/CD overview
and (CI/CD) is a software development practice that automates the build, test, and deployment processes, enabling faster and more reliable software delivery
CI/CD is a critical component of modern cloud computing architectures, allowing organizations to rapidly iterate on their applications and respond to changing business needs
Implementing CI/CD pipelines helps teams catch bugs early, reduce manual errors, and streamline the software release process, ultimately leading to higher quality software and faster time-to-market
Benefits of CI/CD
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Faster time-to-market by automating the build, test, and deployment processes, reducing the time required to release new features and bug fixes
Improved code quality through frequent testing and early detection of bugs, preventing issues from propagating to production environments
Increased efficiency and productivity by eliminating manual and repetitive tasks, allowing developers to focus on writing code and innovating
Enhanced collaboration and communication among team members, as CI/CD pipelines provide visibility into the software development process and facilitate shared responsibility for code quality
Greater agility and flexibility to respond to changing business requirements and customer needs, as CI/CD enables rapid iteration and deployment of software updates
CI/CD vs traditional deployment
Traditional deployment processes often involve manual steps, such as building the application, running tests, and deploying to servers, which can be time-consuming, error-prone, and difficult to scale
CI/CD automates these processes, reducing the risk of human error and ensuring consistency across environments (development, staging, production)
In traditional deployments, software updates are typically released in large batches, leading to longer release cycles and increased risk of introducing bugs or compatibility issues
CI/CD enables more frequent and smaller releases, allowing organizations to deliver value to customers faster and with lower risk, as issues can be identified and resolved more quickly
Continuous integration (CI)
Continuous Integration (CI) is a software development practice where developers regularly merge their code changes into a central repository, triggering an automated build and testing process
The goal of CI is to detect and address early in the development cycle, ensuring that the codebase remains stable and functional
CI helps teams maintain code quality, reduce merge conflicts, and catch bugs before they reach later stages of the development process
CI workflow
Developers code changes to a system (Git)
The CI server (, ) detects the changes and triggers an automated build process
The build process compiles the code, runs unit tests, and performs other quality checks (linting, code coverage)
If the build and tests pass, the code changes are considered validated and ready for further testing or deployment
If the build or tests fail, the CI server notifies the development team, who can then investigate and fix the issues before merging the changes
Version control in CI
Version control systems (Git, SVN) play a crucial role in CI by providing a centralized repository for managing code changes and facilitating collaboration among team members
Branching strategies (feature branches, release branches) help isolate work-in-progress code from the main codebase, reducing the risk of introducing instability or conflicts
Pull requests and code reviews enable team members to provide feedback, catch issues, and ensure code quality before merging changes into the main branch
Automated build process
The automated build process is a key component of CI, responsible for compiling the source code, generating artifacts (binaries, packages), and preparing the application for testing and deployment
tools (Maven, Gradle, Make) help standardize and streamline the build process, ensuring consistency across different environments and reducing the risk of manual errors
Automated builds are triggered whenever changes are pushed to the central repository, providing rapid feedback on the health and quality of the codebase
Code quality checks
Code quality checks are automated tests and analyses performed during the CI process to ensure that the codebase adheres to best practices, coding standards, and project guidelines
Static code analysis tools (SonarQube, ESLint) help identify potential issues, such as code smells, security vulnerabilities, and performance bottlenecks
Code coverage tools (JaCoCo, Istanbul) measure the extent to which the codebase is covered by unit tests, helping teams identify areas that require additional testing
Linting tools (Pylint, RuboCop) enforce consistent coding styles and conventions, improving code readability and maintainability
Unit testing in CI
Unit testing is a software testing method where individual units or components of the application are tested in isolation to ensure they function as expected
In CI, unit tests are automatically run as part of the build process, providing rapid feedback on the correctness and reliability of the codebase
Automated unit tests help catch bugs early, reduce the risk of regressions, and provide a safety net for refactoring and code changes
Test-driven development (TDD) is a practice where developers write unit tests before implementing the corresponding code, ensuring that the code is testable and meets the required functionality
CI best practices
Commit code frequently to the central repository to reduce the size and complexity of each integration, making it easier to identify and resolve issues
Keep the build process fast and reliable by optimizing build scripts, caching dependencies, and parallelizing tasks when possible
Ensure that the CI pipeline covers a comprehensive set of tests, including unit tests, integration tests, and acceptance tests, to validate the application at different levels
Maintain a clean and organized codebase by enforcing coding standards, conducting regular code reviews, and refactoring as needed
Treat the CI pipeline as code, version-controlling the configuration files and build scripts to ensure reproducibility and facilitate collaboration
Monitor the CI pipeline for performance, stability, and resource utilization, and optimize as necessary to ensure efficient and reliable builds
Continuous deployment (CD)
Continuous Deployment (CD) is an extension of Continuous Integration (CI) that automatically deploys code changes to production environments after they have passed all the necessary tests and quality checks
CD aims to reduce the time between writing code and releasing it to users, enabling organizations to deliver value faster and more frequently
Implementing CD requires a robust and reliable automated , as well as effective collaboration between development, testing, and operations teams
CD workflow
Once the CI process has validated the code changes and generated the necessary artifacts, the CD pipeline takes over to deploy the application to the target environment
The CD pipeline typically includes stages for deploying to progressively more production-like environments (development, staging, production)
At each stage, the pipeline performs additional tests (integration tests, performance tests) to ensure the application functions correctly in the target environment
If the tests pass, the pipeline proceeds to the next stage, ultimately deploying the application to the production environment
If any tests fail or issues are detected, the pipeline halts the deployment process and notifies the relevant teams for investigation and resolution
Automated deployment pipeline
The automated deployment pipeline is the backbone of CD, orchestrating the flow of code changes from version control to production environments
Deployment automation tools (Ansible, Puppet, Chef) help define and manage the infrastructure and configuration required for each environment, ensuring consistency and reproducibility
The pipeline includes stages for building, testing, and deploying the application, as well as any necessary database migrations, configuration updates, or resource provisioning
Automated deployment pipelines provide visibility into the deployment process, enabling teams to track the progress of each change and quickly identify and resolve issues
Environment management in CD
is the practice of defining, provisioning, and maintaining the infrastructure and configuration required for each stage of the deployment pipeline
(IaC) tools (Terraform, CloudFormation) enable teams to define and manage environments using declarative configuration files, ensuring consistency and reproducibility
Containerization technologies (, Kubernetes) help isolate application dependencies and provide a consistent runtime environment across different stages of the pipeline
Effective environment management ensures that the application is deployed to a predictable and stable environment, reducing the risk of compatibility issues or configuration drift
Configuration management tools
(Ansible, Puppet, Chef) help automate the provisioning, configuration, and management of servers and infrastructure
These tools use declarative configuration files to define the desired state of the infrastructure, ensuring that the environment is consistently provisioned and configured across different stages of the pipeline
Configuration management tools help reduce the risk of manual errors, improve the scalability and reliability of the infrastructure, and enable teams to manage complex environments with ease
Deployment strategies
are techniques used to release new versions of an application to production environments while minimizing downtime and risk
Different deployment strategies (blue-green, canary, ) offer trade-offs between speed, risk, and complexity, allowing teams to choose the most appropriate approach for their specific needs and constraints
Effective deployment strategies help ensure a smooth and reliable release process, enabling organizations to deliver value to users faster and with greater confidence
Blue-green deployments
Blue-green deployment is a strategy where two identical production environments (blue and green) are maintained, with only one environment actively serving traffic at any given time
When a new version of the application is ready for release, it is deployed to the idle environment (green) and thoroughly tested
Once the new version is validated, the router is updated to switch incoming traffic from the old environment (blue) to the new one (green)
If any issues are detected, the router can quickly switch traffic back to the old environment, minimizing the impact on users
enable zero-downtime releases and provide a fast rollback mechanism in case of failures
Canary releases
Canary release is a deployment strategy where a new version of the application is gradually rolled out to a subset of users, allowing the team to monitor its performance and gather feedback before releasing it to the entire user base
The new version (canary) is deployed alongside the existing version (stable), and a small percentage of incoming traffic is routed to the canary
Monitoring and analytics tools are used to compare the performance and behavior of the canary with the stable version, helping identify any issues or anomalies
If the canary performs well, the percentage of traffic routed to it is gradually increased until it completely replaces the stable version
help minimize the blast radius of potential issues, as only a small subset of users is affected if the new version contains bugs or performance problems
Rolling updates
Rolling updates is a deployment strategy where a new version of the application is gradually deployed to a subset of servers or instances, replacing the old version incrementally
The deployment process is typically automated and orchestrated by tools like Kubernetes or AWS CodeDeploy, ensuring a controlled and predictable rollout
During the rolling update, a portion of the servers are taken out of service, updated with the new version, and then reintroduced to the pool of active servers
This process is repeated until all servers are running the new version, minimizing the impact on the overall system availability and performance
Rolling updates help reduce the risk of downtime and provide a more granular control over the deployment process, allowing teams to pause, roll back, or accelerate the update as needed
Rollback strategies
are techniques used to revert a deployed application to a previous stable version in case of issues or failures
Effective rollback strategies help minimize the impact of deployment failures on users and ensure the system can quickly recover to a known good state
Rollback mechanisms can be automated as part of the deployment pipeline, triggered by monitoring alerts or manual intervention
Techniques like blue-green deployments and canary releases inherently provide fast rollback capabilities, as the previous version of the application is readily available
Other rollback strategies include keeping multiple versions of the application running simultaneously, allowing for quick switching between versions, or maintaining a backup of the previous version's artifacts for fast redeployment
CI/CD tools
CI/CD tools are software applications that automate and orchestrate the various stages of the CI/CD pipeline, from building and testing code to deploying and monitoring applications
These tools help streamline the software delivery process, reduce manual errors, and provide visibility into the pipeline's performance and health
Different CI/CD tools offer various features and integrations, allowing teams to choose the most appropriate solution for their specific needs and technology stack
Popular CI/CD platforms
Jenkins is an open-source automation server that supports a wide range of plugins and integrations, enabling teams to build, test, and deploy applications across multiple platforms and languages
GitLab CI/CD is a built-in feature of the GitLab version control platform, providing a complete CI/CD solution with a focus on simplicity and ease of use
is a Microsoft-hosted service that offers a comprehensive set of tools for CI/CD, project management, and collaboration, with tight integration with the Azure cloud platform
is a fully managed CI/CD service provided by Amazon Web Services, enabling teams to build, test, and deploy applications using a variety of AWS services and third-party tools
is a serverless CI/CD platform that allows teams to build, test, and deploy applications using a declarative YAML configuration, with seamless integration with Google Cloud services
Jenkins for CI/CD
Jenkins is a widely-used open-source automation server that provides a flexible and extensible platform for building CI/CD pipelines
It supports a vast ecosystem of plugins, enabling integration with various source control systems, build tools, testing frameworks, and deployment platforms
Jenkins pipelines can be defined using a declarative syntax (Jenkinsfile) or a scripted syntax (Groovy), allowing teams to create complex and customizable workflows
Jenkins provides a web-based user interface for managing jobs, monitoring builds, and visualizing pipeline progress
Its distributed architecture allows teams to scale their CI/CD infrastructure by adding multiple agents and distributing the workload across them
GitLab CI/CD
GitLab CI/CD is a fully integrated CI/CD solution that comes bundled with the GitLab version control platform
It allows teams to define their CI/CD pipelines using a YAML configuration file (.gitlab-ci.yml) stored in the repository, enabling version control and collaboration on the pipeline definition
GitLab CI/CD provides a wide range of built-in features, such as parallel job execution, artifact management, and environment-specific deployments
Its tight integration with GitLab's version control and issue tracking features enables seamless collaboration between development, testing, and operations teams
GitLab CI/CD runners can be hosted on various platforms, including self-hosted infrastructure, cloud providers, and Kubernetes clusters
Azure DevOps
Azure is a cloud-based platform that provides a comprehensive set of tools for CI/CD, project management, and collaboration
It includes Azure Pipelines, a CI/CD service that enables teams to build, test, and deploy applications across multiple platforms and languages
Azure Pipelines supports a YAML-based configuration for defining CI/CD workflows, allowing version control and collaboration on the pipeline definition
The platform offers a wide range of pre-built tasks and integrations with Azure services, such as Azure Web Apps, Azure Kubernetes Service, and Azure Functions
Azure DevOps also provides features like work item tracking, code repositories, and test plans, enabling end-to-end traceability and visibility across the software development lifecycle
AWS CodePipeline
AWS CodePipeline is a fully managed CI/CD service that enables teams to build, test, and deploy applications using AWS services and third-party tools
It provides a visual workflow editor for defining the stages and actions of the CI/CD pipeline, with support for parallel execution and manual approvals
AWS CodePipeline integrates seamlessly with other AWS services, such as AWS CodeBuild for building and testing code, AWS CodeDeploy for deploying applications, and AWS Elastic Beanstalk for managing application environments
The service offers built-in support for popular source control systems, such as GitHub, GitLab, and AWS CodeCommit, as well as integration with AWS Lambda for serverless deployments
AWS CodePipeline provides a centralized view of the pipeline's progress and status, with detailed logs and notifications for each stage and action
Google Cloud Build
Google Cloud Build is a serverless CI/CD platform that allows teams to build, test, and deploy applications using a declarative YAML configuration
It provides a fast and scalable infrastructure for executing build and test workflows, with support for parallel job execution and caching of dependencies
Google Cloud Build integrates natively with Google Cloud services, such as Google Kubernetes Engine, Google App Engine, and Google Cloud Functions, enabling seamless deployment to various target environments
The platform supports a wide range of programming languages, build tools, and testing frameworks, with pre-built builders and the ability to create custom build steps using Docker containers
Google Cloud Build offers a web-based console for managing build triggers, monitoring build progress, and viewing detailed logs and artifacts
CI/CD in cloud computing
CI/CD is a critical component of modern cloud computing architectures, enabling organizations to leverage the scalability, flexibility, and automation capabilities of cloud platforms
Cloud providers offer managed CI/CD services and tools that integrate seamlessly with their respective cloud ecosystems, simplifying the setup and management of CI/CD pipelines
Implementing CI/CD in the cloud allows teams to take advantage of elastic infrastructure, serverless computing, and containerization technologies to build more resilient and scalable applications
CI/CD for cloud-native apps
Cloud-native applications are designed to take full advantage of the cloud computing model, utilizing services like serverless functions, managed databases, and event-driven architectures
CI/CD pipelines for cloud-native apps often involve building and packaging the application components as containers, deploying them to managed container orchestration platforms (Kubernetes), and leveraging serverless functions for event-driven processing
Cloud providers offer native CI/CD services that integrate with their respective serverless and container platforms, such as AWS CodePipeline with AWS Lambda and Amazon ECS, or Google Cloud Build with Google Cloud Functions and Google Kubernetes Engine
These integrated CI/CD solutions enable teams to build, test, and deploy cloud-native applications with minimal infrastructure management overhead, while ensuring high availability and scalability
Serverless CI/CD
Serverless computing is a cloud computing model where the cloud provider dynamically manages the allocation and provisioning of server resources, allowing developers to focus on writing code without worrying about infrastructure management