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Welcome — in this lesson you’ll learn what AWS CodePipeline is and how it streamlines deployments for your applications using an automated CI/CD flow. At a high level, CodePipeline orchestrates an ordered sequence of stages (source → build → test → deploy) so code changes flow from a repository to a runtime environment with minimal manual intervention. When integrated with CodeBuild, CodePipeline detects source changes, triggers builds, and advances build artifacts into deployment stages such as Amazon ECS to update running services. Why use CodePipeline? It breaks the release process into observable, automatable steps so you can isolate failures quickly, enforce quality gates, and accelerate safe deliveries. How CodePipeline typically works (high level):
  1. A change is pushed to the source repository (for example, CodeCommit or GitHub).
  2. CodePipeline detects that change and pulls the latest code (Source stage).
  3. The code moves into a Build stage (for example, CodeBuild) that compiles, tests, and produces artifacts.
  4. Artifacts are passed forward to Test and Deploy stages; the Deploy stage updates the runtime environment (for example, an ECS service).
  5. Optional Approval stages can require manual confirmation before progressing to production.
Key pipeline stages (typical):
The image is an overview diagram of AWS CodePipeline showing the stages of the pipeline: Source Stage using AWS CodeCommit, followed by Build Stage, Deploy Stage, and ending with deployment to Amazon Elastic Container Service (Amazon ECS).
Core capabilities and behaviors of AWS CodePipeline
  • CI/CD orchestration: Automates the flow from source to deployment, enabling continuous integration and continuous delivery (CI/CD).
  • Pluggable actions: Orchestrates actions across AWS services (CodeBuild, Lambda, ECS, S3, CloudFormation) and third‑party tools (GitHub, Jenkins).
  • Artifact passing: Artifacts produced in one stage are passed to downstream stages so each stage operates on the exact outputs of the previous step.
  • Event-driven triggers: Pipelines can start automatically on source changes, be triggered manually, or started via scheduled or external events.
  • Observability and notifications: Execution history, stage logs, and integration with CloudWatch, Amazon SNS, and other monitoring tools provide visibility and alerting for pipeline runs.
  • Managed service: CodePipeline is serverless from the user perspective — no control plane infrastructure to provision or manage.
Remember: CodePipeline orchestrates actions but does not replace them. Each action (for example, a CodeBuild project or an ECS deploy) executes with its own IAM permissions and configuration. Ensure actions have the required roles and access to the artifacts and resources they need.
The image is an overview of AWS CodePipeline, highlighting its features: continuous integration and delivery, integration with AWS and third-party tools, real-time monitoring, notifications, scalability, and flexibility. Each feature is represented in colorful boxes with icons.
Scaling and usage patterns
  • Small teams: Simple linear pipelines (Source → Build → Deploy) provide fast feedback and automated deployments.
  • Complex enterprises: Pipelines can include parallel actions, multiple environments (dev/stage/prod), manual approvals, and cross-account deployments.
  • Integration: CodePipeline integrates with your existing toolchain while giving you end-to-end visibility for every release.
Next steps
  • Build a sample pipeline: Connect CodeCommit → CodeBuild → ECS to see artifacts flow automatically from source to running containers.
  • Add testing and approval gates: Enforce quality checks and manual approvals before production rollouts.
  • Monitor and iterate: Use CloudWatch and SNS to observe pipeline runs and alert on failures.
Links and references That concludes this lesson — you now understand what CodePipeline is, its core stages, and how it helps automate deployments from CodeCommit to ECS.

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