Complete CI/CD Fundamentals Cheatsheet: From Concepts to Implementation

Introduction: What is CI/CD and Why It Matters

Continuous Integration and Continuous Delivery/Deployment (CI/CD) are software development practices that enable teams to deliver code changes more frequently and reliably. CI/CD automates the building, testing, and deployment processes, reducing manual errors, providing faster feedback, and shortening time-to-market. This approach transforms traditional development cycles into streamlined workflows that can respond quickly to business needs, customer feedback, and security concerns.

CI/CD Defined:

  • Continuous Integration (CI): The practice of frequently integrating code changes into a shared repository, followed by automated builds and tests
  • Continuous Delivery (CD): The extension of CI that automatically prepares code for release to production, making deployments ready at the click of a button
  • Continuous Deployment (CD): The full automation of the deployment process, with every change that passes all stages automatically deployed to production

Core CI/CD Concepts and Principles

Fundamental Principles

  1. Automation First: Automate everything that can be automated in the build, test, and deployment processes
  2. Fail Fast: Identify and address issues early in the development cycle when they’re easiest to fix
  3. Small, Incremental Changes: Make small, frequent updates rather than large, infrequent ones
  4. Consistency Across Environments: Ensure development, testing, and production environments are as similar as possible
  5. Feedback Loops: Create rapid, clear feedback mechanisms for all stakeholders
  6. Infrastructure as Code (IaC): Define infrastructure through code for consistency and version control
  7. Shift Left: Move testing, security, and quality checks earlier in the development process
  8. Visibility and Traceability: Make the process visible to all stakeholders for alignment and accountability

Key CI/CD Pipeline Components

ComponentPurposeExample Tools
Source ControlCode management and versioningGit, GitHub, GitLab, Bitbucket
Build AutomationCompile code and create artifactsMaven, Gradle, npm, MSBuild
Test AutomationVerify code quality and functionalityJUnit, Selenium, Jest, pytest
Artifact RepositoryStore build outputsNexus, Artifactory, Docker Hub
Deployment AutomationDeploy to environmentsAnsible, Terraform, Kubernetes
OrchestrationManage the pipeline workflowJenkins, GitHub Actions, GitLab CI
Monitoring & FeedbackTrack system health and pipeline successPrometheus, Grafana, DataDog

CI/CD Pipeline: Step-by-Step Flow

1. Code Commit Stage

  • Developer writes code locally and runs local tests
  • Code is committed to version control
  • Commit triggers the CI/CD pipeline
  • Pre-commit hooks can enforce code standards

2. Build Stage

  • Source code is fetched from repository
  • Dependencies are resolved
  • Code is compiled if necessary
  • Build artifacts are created (binaries, containers, etc.)
  • Metadata is attached to build (version, commit hash, timestamp)

3. Test Stage

  • Unit Tests: Test individual components in isolation
  • Integration Tests: Verify components work together
  • Functional Tests: Ensure features work as expected
  • Performance Tests: Check system under load
  • Security Tests: Identify vulnerabilities
  • Test reports are generated and stored

4. Analysis Stage

  • Static Code Analysis: Tools like SonarQube check code quality
  • Security Scanning: Identify vulnerabilities in code and dependencies
  • Compliance Checks: Ensure adherence to standards
  • Quality gates determine if pipeline proceeds

5. Artifact Storage

  • Built and verified artifacts are stored in a repository
  • Artifacts are versioned and properly labeled
  • Dependencies are tracked for future reference

6. Deployment Stages

  • Development: First deployment environment
  • Testing/QA: More comprehensive testing environment
  • Staging: Production-like environment for final verification
  • Production: Live environment serving real users
  • Each environment may have specific verifications and approvals

7. Verification & Monitoring

  • Deployment verification tests run
  • Health checks confirm system functionality
  • Monitoring begins capturing metrics
  • Feedback loops inform team of success or issues

Comparison of CI/CD Approaches

Deployment Strategies

StrategyDescriptionProsConsBest For
Rolling DeploymentUpdate instances incrementally in small batchesLow resource overhead, simple to implementSlower deployment, complex rollbacksApplications with stateless components
Blue/Green DeploymentTwo identical environments; one runs while the other updatesZero downtime, instant rollback capabilityHigher resource cost, complex state handlingCustomer-facing applications needing high availability
Canary DeploymentRelease to small subset of users before full rolloutLimits impact of issues, enables A/B testingMore complex to implement, requires monitoringApplications with diverse user bases
Feature FlagsControl feature availability via configurationDecouple deployment from release, targeted releasesTechnical debt from old flags, testing complexityApplications needing fine-grained control over features
Shadow DeploymentProduction traffic copied to new version without affecting usersZero user impact during testing, real-world verificationComplex setup, high resource overheadMission-critical systems requiring thorough validation

CI/CD Tool Categories

CategoryLocal/Self-Hosted ToolsCloud/SaaS ToolsKey Considerations
CI/CD PlatformsJenkins, TeamCity, BambooGitHub Actions, GitLab CI/CD, CircleCI, Travis CIScalability, integration ecosystem, pricing model
Build ToolsMaven, Gradle, MakeCloud Build, AWS CodeBuildLanguage support, caching capabilities, build speed
Test FrameworksJUnit, pytest, MochaBrowserStack, Sauce Labs, ApplitoolsCoverage capabilities, reporting features, execution speed
Infrastructure ToolsAnsible, Chef, PuppetTerraform Cloud, Pulumi, AWS CloudFormationLearning curve, multi-cloud support, state management
Container OrchestrationKubernetes, Docker SwarmEKS, GKE, AKSComplexity, ecosystem maturity, management overhead
Monitoring SolutionsPrometheus, GrafanaDataDog, New Relic, DynatraceDepth of metrics, alerting capabilities, integration options

Common CI/CD Challenges and Solutions

Challenge: Slow Builds and Tests

Solutions:

  • Implement test parallelization
  • Use incremental builds
  • Optimize test selection to run only affected tests
  • Implement build caching
  • Scale CI infrastructure horizontally
  • Profile and optimize slow tests

Challenge: Environment Inconsistency

Solutions:

  • Adopt containerization with Docker
  • Implement Infrastructure as Code (IaC)
  • Use package managers with locked versions
  • Create environment specifications in code
  • Automate environment provisioning
  • Implement environment validation tests

Challenge: Flaky Tests

Solutions:

  • Implement automatic test retries
  • Track and tag flaky tests
  • Implement quarantine for unreliable tests
  • Add more logging and diagnostics
  • Improve test isolation
  • Eliminate implicit dependencies and race conditions

Challenge: Security Integration

Solutions:

  • Implement automated security scanning
  • Use pre-approved components and dependencies
  • Integrate SAST, DAST, and SCA tools
  • Implement policy as code
  • Add automated compliance checks
  • Create specific security gates for different environments

Challenge: Database Changes

Solutions:

  • Implement database migration tools
  • Version control database schemas
  • Use blue/green for database changes
  • Create automated database tests
  • Implement backward compatible changes
  • Separate code and database deployments

Challenge: Managing Dependencies

Solutions:

  • Implement dependency scanning
  • Use lockfiles to pin dependency versions
  • Create a dependency update pipeline
  • Leverage private artifact repositories
  • Implement dependency caching
  • Automate dependency updates with security validation

CI/CD Implementation By Team Size

Small Teams/Startups

  • Pipeline Focus: Simple, minimal approvals, fast feedback
  • Tool Recommendations: GitHub Actions, GitLab CI/CD, CircleCI
  • Strategy: Start with a simple pipeline, prioritize automation over process
  • Key Metrics: Build time, deployment frequency, failure rate

Mid-Size Organizations

  • Pipeline Focus: Environment promotion, parallel testing, security checks
  • Tool Recommendations: Jenkins, AWS CodePipeline, Azure DevOps
  • Strategy: Standardize pipelines, define quality gates, implement IaC
  • Key Metrics: Lead time, MTTR, test coverage, security findings

Enterprise

  • Pipeline Focus: Compliance, governance, multi-team coordination
  • Tool Recommendations: Enterprise Jenkins, GitLab Ultimate, TeamCity
  • Strategy: Pipeline templates, approval workflows, audit trails
  • Key Metrics: Change failure rate, SLA compliance, security posture

CI/CD Configuration Examples

GitHub Actions Basic CI Workflow (YAML)

name: Basic CI Workflow
on: [push, pull_request]
jobs:
  build-and-test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Set up language runtime
        uses: actions/setup-node@v2
        with:
          node-version: '16'
      - name: Install dependencies
        run: npm ci
      - name: Run linting
        run: npm run lint
      - name: Run tests
        run: npm test
      - name: Build application
        run: npm run build

Jenkins Declarative Pipeline (Jenkinsfile)

pipeline {
    agent any
    stages {
        stage('Build') {
            steps {
                sh 'mvn clean compile'
            }
        }
        stage('Test') {
            steps {
                sh 'mvn test'
            }
            post {
                always {
                    junit '**/target/surefire-reports/*.xml'
                }
            }
        }
        stage('Package') {
            steps {
                sh 'mvn package'
                archiveArtifacts artifacts: 'target/*.jar', fingerprint: true
            }
        }
        stage('Deploy to Dev') {
            when {
                branch 'develop'
            }
            steps {
                sh './deploy.sh dev'
            }
        }
    }
}

GitLab CI/CD Pipeline (.gitlab-ci.yml)

stages:
  - build
  - test
  - deploy

variables:
  IMAGE_TAG: $CI_REGISTRY_IMAGE:$CI_COMMIT_REF_SLUG

build:
  stage: build
  script:
    - docker build -t $IMAGE_TAG .
    - docker push $IMAGE_TAG

test:
  stage: test
  script:
    - docker pull $IMAGE_TAG
    - docker run $IMAGE_TAG npm test

deploy:
  stage: deploy
  script:
    - kubectl set image deployment/app app=$IMAGE_TAG
  environment:
    name: production
  only:
    - main

Best Practices and Tips

CI Best Practices

  • Make the main/master branch always deployable
  • Run tests locally before committing
  • Fix broken builds immediately as highest priority
  • Keep the CI pipeline fast (under 10 minutes if possible)
  • Make build logs easily accessible and readable
  • Use consistent build environments
  • Include static analysis as part of the pipeline
  • Clean test data between test runs

CD Best Practices

  • Ensure every change goes through the pipeline
  • Use feature flags to separate deployment from release
  • Implement blue/green or canary deployments
  • Create automated rollback capabilities
  • Make deployment a one-click operation
  • Maintain configuration in code
  • Test the deployment process itself
  • Deploy to a clone of production first

Security Integration Best Practices

  • Include security scanning in every pipeline
  • Scan both custom code and dependencies
  • Fail builds for critical security issues
  • Add compliance verification
  • Use secrets management solutions (not hardcoded)
  • Implement least privilege principle in CI/CD systems
  • Scan container images for vulnerabilities

Monitoring Best Practices

  • Monitor build health and duration
  • Track deployment frequency and success
  • Implement automated post-deployment tests
  • Set up alerting for pipeline failures
  • Track mean time to recovery (MTTR)
  • Measure business impact of CI/CD (delivery speed)
  • Use dashboards for pipeline visibility

Key CI/CD Pipeline Metrics

MetricDescriptionTarget
Deployment FrequencyHow often code is deployed to productionDaily/weekly for most applications
Lead Time for ChangesTime from commit to production deployment<1 day for high-performing teams
Mean Time to Recovery (MTTR)Time to restore service after incident<1 hour for high-performing teams
Change Failure Rate% of deployments causing failures<15% for high-performing teams
Build Success Rate% of successful pipeline executions>95%
Build DurationTime to complete pipelineIdeally <10 minutes (CI), <1 hour (full CD)
Code Coverage% of code covered by automated testsProject-specific, typically >80%
Defect Escape RateBugs that reach productionShould decrease over time

Resources for Further Learning

Official Documentation

Books

  • “Continuous Delivery” by Jez Humble and David Farley
  • “DevOps Handbook” by Gene Kim, Jez Humble, Patrick Debois, and John Willis
  • “Accelerate” by Nicole Forsgren, Jez Humble, and Gene Kim
  • “Infrastructure as Code” by Kief Morris
  • “Site Reliability Engineering” by Google

Online Training

Communities

Remember that implementing CI/CD is a journey rather than a destination. Start small, continuously improve, and adapt your pipeline to your team’s specific needs and workflows. Successful CI/CD implementation requires both technical tools and organizational culture changes to achieve the full benefits of automation, reliability, and speed.

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