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06-deploying-cycle.md

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DEPLOYING CYCLE


Deploying commands

Purpose Command Explanation
Initial Project Setup pip install -r requirements.txt Installs the Python dependencies listed in requirements.txt using pip.
cdk bootstrap aws:/// Bootstraps the environment with the necessary resources like an S3 bucket for deployment assets.
Deployment cdk synth Generates the CloudFormation template based on your CDK app, allowing you to review it before deployment.
cdk deploy Deploys the stack(s) defined in your CDK app to your AWS account.
cdk diff Displays the differences between the deployed stack and the changes in your CDK app.
Future Management cdk deploy Deploys any updates or changes to your stack(s) after making modifications to your CDK app.
cdk destroy Destroys the deployed stack(s) and deletes all associated resources.
conda update --all Updates all packages within your Conda environment to the latest versions.

Theoretical steps

The following are the steps that CDK performs to interpret and generate the necessary infrastructure in AWS.

What it does is the following:

  1. It interprets all the code that is at the App level. It performs the synthesis action (cdk synth) to generate artifacts for Cloudformation.
    • This assumes that it checks all the constructs and generates the Cloudformation templates. Generate unique ids (arn) for each of the assets.
    • The assets are understood as the project files (scripts, dockerfiles, etc..).
  2. At this point the CDK starts bootstrapping (cdk bootstrap) to create the environment where all the assets will be stored.
    • Creates an stack (often called CDKToolkit) with all the necessary resources to make the deployment.
    • For example, in this bucket you will store the docker image while you are converting it before loading it to ECR.
  3. The App is deployed.
    • The App is in charge of generating the App Tree from which all its constructs will hang.
    • Each construct will perform the following series to generate the CF code:
      • prepare > validate > synthesize
    • Start the deployment in AWS


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