1. Building Docker Containers for AI Workloads with AWS CodeBuild


    To build Docker containers for AI workloads with AWS CodeBuild, you will need to create a build project within AWS that specifies how to build your container. This involves defining a build environment, the location of the source code, the build commands (usually in a buildspec file), and where to store the resulting Docker image. This process can be automated using Pulumi, an infrastructure as code tool.

    Here is what you will achieve with the Pulumi program:

    1. Create a CodeBuild project.
    2. Define the environment where your Docker container will be built, which includes the type of instance, the Docker image to use for builds, and the necessary IAM permissions.
    3. Specify the source repository for your AI application code.
    4. Define a buildspec file where you will describe the steps needed to build your Docker container.
    5. Configure where the built Docker image will be stored. Typically, this would be Amazon Elastic Container Registry (ECR).

    Below is a detailed Pulumi Python program that accomplishes these steps:

    import pulumi import pulumi_aws as aws # Define the Amazon ECR repository where the Docker images will be stored. ecr_repository = aws.ecr.Repository('ai-app-repo') # IAM role and policy that will be used by AWS CodeBuild to interact with other AWS services. codebuild_role = aws.iam.Role('codebuild-role', assume_role_policy=pulumi.Output.all( ec2_principals=aws.iam.get_principal("ec2.amazonaws.com"), codebuild_principals=aws.iam.get_principal("codebuild.amazonaws.com") ).apply(lambda principals: f""" {{ "Version": "2012-10-17", "Statement": [ {{ "Effect": "Allow", "Principal": {{ "Service": [{principals.ec2_principals}, {principals.codebuild_principals}] }}, "Action": "sts:AssumeRole" }} ] }} """)) # The policy attached to the role. It must provide enough permissions for CodeBuild to build Docker images and push them to ECR. codebuild_policy = aws.iam.RolePolicy('codebuild-policy', role=codebuild_role.id, policy=pulumi.Output.all(ecr_repository.repository_url).apply(lambda url: f""" {{ "Version": "2012-10-17", "Statement": [ {{ "Effect": "Allow", "Action": [ "logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents" ], "Resource": "*" }}, {{ "Effect": "Allow", "Action": [ "ecr:GetAuthorizationToken", "ecr:BatchCheckLayerAvailability", "ecr:PutImage", "ecr:InitiateLayerUpload", "ecr:UploadLayerPart", "ecr:CompleteLayerUpload" ], "Resource": "{url}" }} ] }} """)) # Creation of the AWS CodeBuild project. codebuild_project = aws.codebuild.Project('ai-codebuild-project', service_role=codebuild_role.arn, source=aws.codebuild.ProjectSourceArgs( type='GITHUB', location='https://github.com/your-org/your-ai-app-repo.git' # Replace with your repository URL. ), artifacts=aws.codebuild.ProjectArtifactsArgs( type='NO_ARTIFACTS' ), environment=aws.codebuild.ProjectEnvironmentArgs( compute_type='BUILD_GENERAL1_SMALL', # Choose the appropriate instance type. image='aws/codebuild/standard:2.0', # Use the standard Docker image provided by AWS CodeBuild. type='LINUX_CONTAINER', privileged_mode=True, # Required for building Docker images. environment_variables=[ aws.codebuild.ProjectEnvironmentEnvironmentVariableArgs( name='AWS_DEFAULT_REGION', value='us-west-2' # Specify the region your services are located in. ), aws.codebuild.ProjectEnvironmentEnvironmentVariableArgs( name='AWS_ACCOUNT_ID', value=codebuild_role.arn.apply(lambda arn: arn.split(':')[4]) # Extract the AWS account ID from the role ARN. ), aws.codebuild.ProjectEnvironmentEnvironmentVariableArgs( name='IMAGE_REPO_NAME', value=ecr_repository.name # Use the ECR repository created above. ), aws.codebuild.ProjectEnvironmentEnvironmentVariableArgs( name='IMAGE_TAG', value='latest' # Tag for the Docker image that will be built. ), ] ), build_timeout=60, # Set the build timeout in minutes. # Define the instructions for CodeBuild to build your Docker image in buildspec. # A buildspec is a collection of build commands and related settings, in Yaml format, # that CodeBuild uses to run a build. buildspec=pulumi.Output.all(ecr_repository.repository_url).apply(lambda url: f""" version: 0.2 phases: pre_build: commands: - $(aws ecr get-login --no-include-email --region $AWS_DEFAULT_REGION) build: commands: - docker build -t $IMAGE_REPO_NAME:$IMAGE_TAG . - docker tag $IMAGE_REPO_NAME:$IMAGE_TAG {url}:$IMAGE_TAG post_build: commands: - docker push {url}:$IMAGE_TAG """)) # Output the CodeBuild project name and the ECR repository URL where the image will be stored. pulumi.export('codebuild_project_name', codebuild_project.name) pulumi.export('ecr_repository_url', ecr_repository.repository_url)


    • ECR Repository: The Docker images are pushed to this repository after being built.
    • IAM Role and Policy: AWS CodeBuild needs permissions to interact with other services, such as pushing the Docker images to ECR and writing logs.
    • CodeBuild Project: This defines the build environment settings and points to the source code location and buildspec file.
    • Environment Variables: These are used by AWS CodeBuild during the build. For example, they identify the AWS ECR repository where Docker images will be stored.
    • Buildspec: This file contains a set of instructions which tells CodeBuild how to build your Docker image.
    • Exports: The pulumi.export statements at the end of the program output the CodeBuild project name and the ECR repository URL, which are useful when integrating with other CI/CD pipelines or for reference.

    Remember to replace 'https://github.com/your-org/your-ai-app-repo.git' with the actual URL of your AI application's GitHub repository.

    This is a comprehensive program that should work out of the box for creating a Docker container build system for AI workloads using AWS CodeBuild and Pulumi. Remember to have your Pulumi and AWS credentials set up prior to running this program.