Please follow the getting started guide to get your machine configured.
Because this is a monorepo, VS Code/Cursor and the like can be slow to load, because it needs to run checks on the Python code for every single project.
Instead, load only the code for the task you're working on by navigating to File -> Open Workspace from File...
and selecting the workspace file (eg week5/1-hello-world/1-hello-world.code-workspace
).
You can deploy projects from GitHub actions. You must run from your own fork to do so.
-
Deploy the CloudFormation stack
This command will create the IAM role that GitHub Actions will use to deploy your stacks. Replace
<your-org>
and<your-repo>
with your GitHub organization and repository name.
aws cloudformation deploy \
--template-file github-actions.yaml \
--stack-name github-actions-role \
--parameter-overrides GitHubOrg=<your-org> GitHubRepo=<your-repo> \
--capabilities CAPABILITY_NAMED_IAM
After deployment, get the RoleArn
output from the stack.
aws cloudformation describe-stacks \
--stack-name github-actions-role \
--query "Stacks[0].Outputs[?OutputKey=='RoleArn'].OutputValue" \
--output text
- Set the
AWS_ROLE_ARN
in GitHub
The RoleArn
from the previous step needs to be configured as a repository variable in GitHub.
- Navigate to your repository on GitHub.
- Go to
Settings
>Secrets and variables
>Actions
. - Click
New repository secret
. - Name the variable
AWS_ROLE_ARN
. - Paste the
RoleArn
value from the previous step. - Click
Add variable
.
- Navigate to the
Actions
tab in your GitHub repository. - In the left sidebar, select the workflow you want to run (e.g.,
Deploy Hello World
). - Click the
Run workflow
dropdown, and then click theRun workflow
button to start the deployment.
- Automated deployments and CI/CD with agentic workflows
- Building agentic applications with AWS CDK
- Creating and using tools in agentic applications
- Integrating MCP
- GenAI Security
- GenAI security techniques
- Creating and using AI Guardrails
- Beyond chat: Automated document processing workflows
- Automated document processing and embedding creation
- Effective RAG use
- Capstone project: Building a real production application