Deployment And Delivery Design — AWS Cloud Practitioner (CLF-C02)
Rollback speed and blast radius pick the deployment model
CodeDeploy automates application deployments with configurable traffic shifting and automatic rollback triggers. CloudFormation manages infrastructure state — not application release cadence. ECS and EKS introduce container-level deployment strategies like blue/green and rolling when containerization is already in play. The exam's deciding constraint is usually: how fast must you roll back, and how much traffic can an error reach before rollback fires.
What This Pattern Tests
The exam tests deployment pipeline design with service-appropriate strategies. CodePipeline orchestrates source-build-test-deploy stages with manual approval gates. CodeDeploy supports blue/green on ECS (shift traffic between task sets), canary on Lambda (shift 10% then all), and rolling on EC2. For DOP-C02, CloudFormation StackSets deploy infrastructure across multiple accounts and regions simultaneously, while change sets preview modifications before execution. For AIF-C01 and MLS-C01, SageMaker Pipelines orchestrate ML workflows — data processing, training, evaluation, and model registration — with Model Registry tracking model versions and approval status before deployment to endpoints. The trap is using CodeDeploy for ML model deployment (SageMaker Pipelines handles the ML lifecycle) or CloudFormation direct updates without change sets in production.
Decision Axis
Deployment risk tolerance and workload type determine the pipeline: application code uses CodePipeline, infrastructure uses CloudFormation StackSets, ML models use SageMaker Pipelines.
Associated Traps
More Top Traps on This Exam
Decision Rules
Whether to provision and redeploy infrastructure using a repeatable IaC template (CloudFormation) or through manual Console interactions that cannot enforce environment parity or prevent configuration drift.
Domain Coverage
Difficulty Breakdown