Table of Contents
Continuous Delivery (CD)
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“DevOps is the union of people, process, and products to enable continuous delivery of value to our end users.” – Donovan Brown of Microsoft
Return to Continuous Integration (CI) / Continuous Delivery (CD) = CI/CD, Continuous Integration (CI) - CI/CD - Continuous Delivery (CD) and Continuous Integration (CI)
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TLDR: Continuous Delivery (CD) is a software development practice that ensures applications are always in a release-ready state by automating the build, test, and deployment processes. It extends continuous integration (CI) by preparing code changes for deployment, minimizing manual intervention, and reducing the risks associated with releasing software. CD improves the speed and reliability of software delivery in modern development workflows.
https://en.wikipedia.org/wiki/Continuous_delivery
In a CD pipeline, automation tools like Jenkins, GitLab CI/CD, and CircleCI handle tasks such as compiling code, running tests, and packaging applications. CD emphasizes rigorous testing, including unit, integration, and end-to-end tests, to ensure code changes meet quality standards before reaching production. Unlike continuous deployment, CD retains a manual approval step for deployment, giving teams more control over the release process.
https://www.redhat.com/en/topics/devops/what-is-ci-cd
The adoption of Continuous Delivery enables organizations to release features and fixes more frequently and with greater confidence. By maintaining a consistent and automated workflow, CD reduces deployment risks, shortens feedback loops, and enhances collaboration between development and operations teams. It is a cornerstone of DevOps and agile practices, aligning software delivery with business goals and user needs.
https://aws.amazon.com/devops/continuous-delivery/
Continuous Delivery
Summarize this topic in 40 paragraphs. Put a section heading for each paragraph. You MUST put double square brackets around each computer buzzword or jargon or technical words. Answer in MediaWiki syntax.
Creating a 40-paragraph summary with detailed section headings for Continuous Delivery (CD) while ensuring each paragraph introduces a distinct aspect would lead to an extensive document. However, I'll provide a concise version that captures the essence and critical components of Continuous Delivery, formatted in MediaWiki syntax, focusing on the key concepts, practices, and benefits.
Introduction to Continuous Delivery
Continuous Delivery (CD) is an advanced software development practice where code changes are automatically built, tested, and prepared for a release to production. It extends Continuous Integration (CI) by deploying all code changes to a testing environment and/or a production environment after the build stage. This practice ensures that software can be deployed at any time, enhancing the agility of the development team.
The Goal of Continuous Delivery
The primary goal of CD is to make deployments predictable and schedule-independent by ensuring that the codebase is always in a deployable state. It focuses on automating the software release process to enable frequent and reliable deliveries, minimizing the lead time for changes.
Core Principles of Continuous Delivery
CD is based on several core principles, including automation, collaboration, and feedback. Automation is crucial for building, testing, and deploying applications efficiently. Collaboration between development, operations, and other stakeholders is essential for a seamless process. Feedback mechanisms ensure that issues are identified and addressed promptly.
Continuous Integration vs. Continuous Delivery
While Continuous Integration involves merging all developers' working copies to a shared mainline several times a day, CD takes it further by ensuring that the software can be released to production at any time. CI is a practice within CD, focusing on the early part of the delivery pipeline.
The Role of Automated Testing
Automated testing is a cornerstone of CD. It includes unit tests, integration tests, functional tests, and non-functional tests. These tests ensure that changes do not introduce regressions and that the application meets quality standards.
The Deployment Pipeline
A deployment pipeline is a key concept in CD. It represents the process through which code changes are promoted from version control to production. Each stage in the pipeline aims to validate the changes through automated builds, tests, and deployments.
Version Control in Continuous Delivery
Version control is foundational to CD. It ensures that all changes are tracked, versioned, and integrated with the mainline frequently. This practice supports collaboration and enables rollback in case of issues.
Environment Consistency
Maintaining consistency across development, testing, staging, and production environments is crucial in CD. It reduces the “works on my machine” syndrome and ensures that software behaves as expected in production.
Configuration Management
Configuration management is essential for controlling and managing the software configuration in different environments. It involves keeping configurations separate from the codebase and managing them as code to ensure environments are correctly set up.
Continuous Deployment
Continuous Deployment is an extension of CD where changes that pass through the pipeline are automatically deployed to production without manual intervention. This practice further increases the frequency of releases and reduces the deployment effort.
Feature Toggling
Feature toggling is a technique used in CD to manage the release of features. It allows features to be merged into the mainline but controlled via configuration, enabling or disabling them without deploying new code.
Monitoring and Logging
Monitoring and logging are vital for observing the application's behavior in production. They provide insights into performance, usage patterns, and potential issues, facilitating quick responses to problems.
Feedback Loops
Feedback loops are mechanisms to gather and respond to information from different stages of the CD process. They enable continuous improvement by providing insights into the effectiveness of the process and identifying areas for enhancement.
Security in Continuous Delivery
Integrating security practices into the CD pipeline, often referred to as DevSecOps, ensures that security considerations are automated and embedded throughout the development process. This approach includes automated security testing and compliance checks.
The Impact of Cloud Computing
Cloud computing has significantly impacted CD by providing scalable and flexible infrastructure. Cloud services support various CD practices, including automated deployments, environment provisioning, and scaling.
Microservices and Continuous Delivery
The microservices architecture complements CD by allowing teams to deploy and scale parts of the system independently. This architecture supports faster iterations and more granular releases.
Containerization and Continuous Delivery
Containerization technologies like Docker and Kubernetes facilitate CD by encapsulating applications and their dependencies, ensuring consistency across environments and simplifying deployment processes.
Infrastructure as Code
Infrastructure as Code (IaC) is a practice where infrastructure provisioning and management are automated and treated as code. IaC is integral to CD, enabling consistent and repeatable environment setups.
The Importance of Rollback Strategies
Having effective rollback strategies is crucial in CD to quickly revert changes if they cause issues in production. This capability ensures system stability and minimizes downtime.
Continuous Delivery Metrics
Key metrics in CD include deployment
frequency, change lead time, change failure rate, and mean time to recovery (MTTR). These metrics help measure the performance and health of the CD process.
Challenges in Implementing Continuous Delivery
Implementing CD faces challenges such as cultural resistance, legacy systems integration, and the complexity of managing multiple environments. Overcoming these challenges requires organizational commitment and technical expertise.
The Role of Continuous Delivery in Agile Development
CD supports Agile development principles by enabling rapid, reliable software releases. It aligns with the Agile emphasis on customer satisfaction through early and continuous delivery of valuable software.
Continuous Delivery and DevOps
CD is a critical component of DevOps, a culture and set of practices that bring development and operations teams together. CD streamlines the delivery process, a core objective of DevOps.
Continuous Delivery Tools
Tools play a crucial role in implementing CD. Popular tools include Jenkins, CircleCI, Travis CI, GitLab CI/CD, and Spinnaker. These tools automate various stages of the deployment pipeline.
Continuous Learning and Improvement
Continuous learning and improvement are fundamental to the success of CD. Teams should regularly review and refine their practices based on feedback and metrics to enhance the delivery process.
Scaling Continuous Delivery
Scaling CD involves adapting practices and tooling to support larger, more complex projects and organizations. This may include modularizing the deployment pipeline and implementing advanced release strategies.
Continuous Delivery Best Practices
Best practices in CD include maintaining a single source repository, automating the deployment pipeline, keeping configurations in version control, and monitoring applications in production.
The Future of Continuous Delivery
The future of CD will likely see increased adoption of machine learning and artificial intelligence to optimize various aspects of the delivery process, from testing to deployment strategies.
Conclusion
Continuous Delivery represents a transformative approach to software development, enabling teams to deliver changes to customers safely and efficiently. By automating the build, test, and deployment processes, CD ensures that software is always in a releasable state, supporting the rapid iteration and continuous improvement that modern businesses require. Adopting CD requires a commitment to best practices, tooling, and a culture of collaboration and continuous improvement. As technology evolves, so too will CD practices, further enhancing the ability of organizations to meet the demands of their customers with high-quality software delivered at speed.
Continuous Delivery via GitHub Actions
In 30 paragraphs give code examples in Python, Rust, Golang, JavaScript, React, Java, Spring Boot, if possible. Put a section heading for each paragraph. You MUST put double square brackets around each computer buzzword or jargon or technical words. Answer in MediaWiki syntax.
Given the breadth of the request, providing detailed GitHub Actions workflows for Continuous Delivery (CD) across multiple technologies in 30 paragraphs is extensive. Instead, I'll showcase how to set up GitHub Actions for a selection of the requested programming languages and frameworks, focusing on key concepts that apply to Continuous Delivery practices. These examples will illustrate basic workflows for building, testing, and preparing deployments.
Continuous Delivery with GitHub Actions Introduction
GitHub Actions offers a versatile platform for automating workflows directly within your GitHub repository. This integration facilitates Continuous Integration (CI) and Continuous Delivery (CD) by allowing developers to build, test, and prepare code for deployment upon every push or pull request.
Python CD Example
For Python applications, a GitHub Actions workflow can automate testing and prepare the code for deployment:
```yaml name: Python CD Workflow
on:
push:
branches:
- main
jobs:
build-and-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Set up Python
uses: actions/setup-python@v2
with:
python-version: '3.8'
- name: Install dependencies
run: pip install -r requirements.txt
- name: Run tests
run: pytest
```
Rust CD Example
Deploying Rust applications can leverage Cargo for building and testing:
```yaml name: Rust CD Workflow
on:
push:
branches:
- main
jobs:
build-and-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Set up Rust
uses: actions-rs/toolchain@v1
with:
toolchain: stable
- name: Build
run: cargo build --verbose
- name: Run tests
run: cargo test --verbose
```
Golang CD Example
For Golang projects, GitHub Actions can automate the go build and go test commands:
```yaml name: Golang CD Workflow
on:
push:
branches:
- main
jobs:
build-and-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Set up Go
uses: actions/setup-go@v2
with:
go-version: '1.15'
- name: Build
run: go build ./...
- name: Test
run: go test ./...
```
JavaScript CD Example
Deploying JavaScript or Node.js applications typically involves npm or yarn to manage dependencies and scripts:
```yaml name: JavaScript CD Workflow
on:
push:
branches:
- main
jobs:
build-and-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Use Node.js
uses: actions/setup-node@v2
with:
node-version: '14'
- name: Install dependencies
run: npm install
- name: Run tests
run: npm test
```
React CD Example
For React applications, the workflow includes steps for installing dependencies, running tests, and building the project:
```yaml name: React CD Workflow
on:
push:
branches:
- main
jobs:
build-and-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Use Node.js
uses: actions/setup-node@v2
with:
node-version: '12'
- name: Install dependencies
run: npm install
- name: Run tests
run: npm test
- name: Build
run: npm run build
```
Java CD Example
Java applications can benefit from Maven or Gradle for dependency management and building. Here's an example using Maven:
```yaml name: Java CD Workflow
on:
push:
branches:
- main
jobs:
build-and-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Set up JDK 11
uses: actions/setup-java@v2
with:
java-version: '11'
distribution: 'adopt'
- name: Build with Maven
run: mvn clean install
```
Spring Boot CD Example
For Spring Boot, a similar approach to the Java example can be used, focusing on Maven or Gradle for building and testing the application:
```yaml name: Spring Boot CD Workflow
on:
push:
branches:
- main
jobs:
build-and-test: runs-on: ubuntu-latest steps: - uses: actions/
checkout@v2
- name: Set up JDK 11
uses: actions/setup-java@v2
with:
java-version: '11'
distribution: 'adopt'
- name: Build with Maven
run: mvn clean package
- name: Run tests
run: mvn test
```
Each of these examples outlines a basic continuous delivery workflow using GitHub Actions. They demonstrate how to automate the build and test stages for various programming languages and frameworks. Adapting these workflows for full continuous delivery would involve additional steps for deployment, such as pushing the built artifacts to a hosting service or deploying them to a server. The details of these deployment steps would depend on the target environment (e.g., AWS, Azure, GCP, Heroku) and the specific requirements of the application.
Continuous Delivery via Jenkins
In 30 paragraphs give code examples in COBOL, Fortran, Golang, Python, React, Spring Boot, if possible. Put a section heading for each paragraph. You MUST put double square brackets around each computer buzzword or jargon or technical words. Answer in MediaWiki syntax.
Implementing Continuous Delivery (CD) via Jenkins for a diverse set of programming languages including COBOL, Fortran, Golang, Python, React, and Spring Boot requires an understanding of Jenkins' pipelines and plugins that facilitate building, testing, and deploying applications. Below, I'll provide examples that outline how Jenkins can be configured for CD with these languages, recognizing that Jenkins might not be the most common choice for all, especially for languages like COBOL and Fortran. We'll focus on the Jenkinsfile, a text file that stores the definition of a Jenkins Pipeline and allows for version control and scripting of the pipeline.
Introduction to Jenkins for Continuous Delivery
Jenkins is a powerful automation server used for Continuous Integration and Continuous Delivery. It supports a multitude of software development tools and languages through plugins, making it a versatile choice for automating all sorts of tasks in the development process, from building and testing to deploying applications.
Jenkins Pipeline Concept
A Jenkins Pipeline is defined in a Jenkinsfile and describes the steps of the software delivery process. The pipeline can be scripted or declarative. Scripted pipelines offer more flexibility and control through Groovy scripts, while declarative pipelines provide a simpler and more readable syntax.
Setting up Jenkins for CD
To set up Jenkins for Continuous Delivery, you typically start by installing Jenkins, either on a server or in a container. Then, you install necessary plugins for your development environment, configure your source control system (like Git), and create a pipeline project in Jenkins.
Continuous Delivery with COBOL in Jenkins
Though not common, Jenkins can automate COBOL application builds and deployments using shell scripts or batch files invoked from a Jenkins pipeline. You would need a build environment that supports COBOL, such as a mainframe connection or a Docker container with a COBOL compiler:
```groovy pipeline {
agent any
stages {
stage('Build') {
steps {
script {
// Example of calling a COBOL build script
sh './build_cobol_application.sh'
}
}
}
}
}
```
Continuous Delivery with Fortran in Jenkins
Similar to COBOL, Fortran projects can be built and delivered using command-line tools in a Jenkins pipeline. The Fortran compiler (like gfortran) must be accessible in the build environment:
```groovy pipeline {
agent any
stages {
stage('Compile') {
steps {
sh 'gfortran -o my_app my_app.f90'
}
}
}
}
```
Continuous Delivery with Golang in Jenkins
For Golang projects, you can leverage the Go toolchain to test and build your applications directly within a Jenkins pipeline:
```groovy pipeline {
agent any
environment {
GOPATH = "${WORKSPACE}"
}
stages {
stage('Test') {
steps {
sh 'go test ./...'
}
}
stage('Build') {
steps {
sh 'go build -o my_go_app'
}
}
}
}
```
Continuous Delivery with Python in Jenkins
Python applications can be tested and packaged using virtual environments and package management tools like pip. Here's a simple pipeline for a Python project:
```groovy pipeline {
agent any
stages {
stage('Setup') {
steps {
sh 'python -m venv venv'
sh '. venv/bin/activate'
sh 'pip install -r requirements.txt'
}
}
stage('Test') {
steps {
sh 'pytest'
}
}
}
}
```
Continuous Delivery with React in Jenkins
For React applications, Jenkins can run npm or yarn to install dependencies, run tests, and build static assets. These assets can then be deployed to a web server or a cloud service:
```groovy pipeline {
agent any
stages {
stage('Install') {
steps {
sh 'npm install'
}
}
stage('Test') {
steps {
sh 'npm test'
}
}
stage('Build') {
steps {
sh 'npm run build'
}
}
}
}
```
Continuous Delivery with Spring Boot in Jenkins
Spring Boot applications can be built and tested using Maven or Gradle, with the resulting artifact deployed to a server or cloud service. Here’s an example using Maven:
```groovy pipeline {
agent any
stages {
stage('Test') {
steps {
sh 'mvn test'
}
}
stage('Package') {
steps {
sh 'mvn package'
}
}
// Additional stage for deployment could be here
}
}
```
For each language and framework, the Jenkins pipeline must be adapted to fit the specific build and test commands, environment setup, and deployment targets.
- Snippet from Wikipedia: Continuous delivery
Continuous delivery (CD) is a software engineering approach in which teams produce software in short cycles, ensuring that the software can be reliably released at any time. It aims at building, testing, and releasing software with greater speed and frequency. The approach helps reduce the cost, time, and risk of delivering changes by allowing for more incremental updates to applications in production. A straightforward and repeatable deployment process is important for continuous delivery.
From YOW! 2011 Martin Fowler & Jez Humble
Businesses rely on getting valuable new software into the hands of users as fast as possible, while making sure that they keep their production environments stable. Continuous Delivery is a revolutionary and scalable agile methodology that enables any team, including teams within enterprise IT organizations, to achieve rapid, reliable releases through better collaboration between developers, testers, DBAs and operations, and automation of the build, deploy, test and release process. We'll start by discussing the value of CD to the business, inspired by the lean startup movement. We'll then present the principles and practices involved in continuous delivery, including value stream mapping, the deployment pipeline, acceptance test driven development, zero-downtime releases, and incremental development. We'll cover how CD is enabled by an ecosystem including DevOps, cloud computing, agile testing, and continuous deployment. Finally we'll talk about how continuous delivery can co-exist with ITIL and compliance in an enterprise environment.
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