AWS CDK
Independent PiSkill directory guide. The original skill remains hosted by AWS Agent Toolkit.
What is AWS CDK?
Supports authoring, deploying, refactoring, and troubleshooting AWS CDK infrastructure in TypeScript or Python, including stack design, constructs, drift, imports, and safe deployment workflows.
What does AWS CDK do?
AWS CDK is an AWS Agent Toolkit skill for authoring and maintaining infrastructure as code with the AWS Cloud Development Kit. It supports TypeScript and Python workflows for stack design, constructs, deployment, refactoring, imports, drift and troubleshooting while keeping infrastructure changes reviewable.
Who is AWS CDK best for?
- Developers provisioning AWS with TypeScript or Python
- Teams replacing manual infrastructure with CDK
- Projects refactoring large CDK stacks
- Engineers troubleshooting synth or deployment issues
Common use cases
- Create a new CDK stack and reusable constructs
- Refactor infrastructure without losing resources
- Import existing AWS resources into CDK management
- Diagnose synthesis, deployment or drift problems
How does AWS CDK work?
The skill maps the infrastructure goal to CDK stacks and constructs, generates or refactors code using supported patterns, then verifies synthesis and deployment-related behavior. It also helps reason about imports and drift so changes do not accidentally replace or orphan existing resources.
Key benefits
- Brings infrastructure logic into normal application languages
- Supports reusable constructs and stack organization
- Encourages verification before infrastructure deployment
- Useful for both greenfield and existing AWS environments
Things to know
- Infrastructure changes can be destructive if diffs are not reviewed
- AWS permissions and environment bootstrapping still matter
- Complex migrations may require resource-specific import or retention strategies
Compatible tools
Frequently asked questions
What does the AWS CDK skill do?
Can it work with existing AWS resources?
Related skills
AWS CloudFormation
Guides infrastructure-as-code work with AWS CloudFormation, including template authoring, deployment, troubleshooting, stack behavior, dependencies, and production-safe infrastructure changes.
AWS Compute
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AWS Containers
Guides container workloads on AWS across services such as ECS and ECR, with production-oriented patterns for images, task definitions, deployments, networking, scaling, and troubleshooting.
AWS Observability
Helps implement and troubleshoot AWS observability using services such as CloudWatch, X-Ray, and CloudTrail for logs, metrics, traces, alarms, diagnostics, and operational visibility.
Python Environment Setup for Hugging Face Cloud
Sets up an isolated Python environment for Hugging Face cloud and SageMaker workflows with an appropriate Python version and current AWS tooling.
AWS Context Discovery
Discovers the active AWS profile, region, account, and caller identity before Hugging Face cloud or SageMaker work so later steps use the correct AWS context.