1. Large Language Model API Hosting on AWS Lambda


    Hosting a Large Language Model API on AWS Lambda involves creating a serverless compute environment where your API code can execute. AWS Lambda allows you to run code without provisioning or managing servers, and you pay only for the compute time you consume. Integrating an API with AWS Lambda can be done through Amazon API Gateway, which will handle the HTTP requests and route them to your Lambda function.

    Here's an outline of the steps involved:

    1. Create an AWS Lambda Function: This is where your API logic will reside. You'll need to package your code and dependencies in a way that Lambda can execute.
    2. Set Up Amazon API Gateway: You'll configure an HTTP endpoint that listens for requests and forwards them to your Lambda function.
    3. Permissions: Proper permissions need to be set so that API Gateway can invoke your Lambda function.
    4. Deployment: After setting up the resources, you deploy your API to make it accessible from the internet.

    Now let's dive into the Pulumi code to accomplish this.

    import pulumi import pulumi_aws as aws # Define the IAM role that will allow the Lambda function to run lambda_role = aws.iam.Role("lambdaRole", assume_role_policy="""{ "Version": "2012-10-17", "Statement": [{ "Action": "sts:AssumeRole", "Effect": "Allow", "Principal": { "Service": "lambda.amazonaws.com" } }] }""") # Attach the AWSLambdaBasicExecutionRole policy to the role created above policy_attachment = aws.iam.RolePolicyAttachment("lambdaPolicyAttachment", role=lambda_role.name, policy_arn="arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole") # Create the Lambda function lambda_function = aws.lambda_.Function("myApiLambdaFunction", role=lambda_role.arn, runtime="python3.8", # Replace with the runtime of your choice handler="app.handler", # Replace with your handler file and method code=pulumi.FileArchive("./api_code.zip"), # The path to the zipped code timeout=30, # The function's maximum execution time memory_size=1024) # Adjust memory based on your needs # Define an API Gateway to make the Lambda function accessible over HTTPS api_gateway = aws.apigatewayv2.Api("myApiGateway", protocol_type="HTTP") # Create a default route linked to the Lambda function integration = aws.apigatewayv2.Integration("myLambdaIntegration", api_id=api_gateway.id, integration_type="AWS_PROXY", # This integrates the API with Lambda integration_uri=lambda_function.invoke_arn ) # Set up the route to invoke the Lambda integration route = aws.apigatewayv2.Route("anyRoute", api_id=api_gateway.id, route_key="$default", # This is the default route. You can define specific routes as required. target=pulumi.Output.concat("integrations/", integration.id) ) # Deploy the API Gateway deployment = aws.apigatewayv2.Deployment("apiDeployment", api_id=api_gateway.id, # Enforce a new deployment when the API gateway or the route is modified triggers={"redeployment": pulumi.Output.all(api_gateway.id, route.id).apply(lambda args: str(hash(args)))}, opts=pulumi.ResourceOptions(depends_on=[route]) ) # Create a stage for deploying stage = aws.apigatewayv2.Stage("apiStage", api_id=api_gateway.id, name="v1", deployment_id=deployment.id, auto_deploy=True ) # Give the API Gateway permission to invoke the Lambda function invoke_permission = aws.lambda_.Permission("apiGatewayInvoke", action="lambda:InvokeFunction", function=lambda_function.name, principal="apigateway.amazonaws.com", # This is important for allowing invocation via API Gateway source_arn=stage.execution_arn.apply(lambda execution_arn: f"{execution_arn}*/*") ) # Export the API endpoint URL pulumi.export("api_url", pulumi.Output.concat("https://", api_gateway.id, ".execute-api.", pulumi.get_region(), ".amazonaws.com/", stage.name))

    Here’s a walkthrough of each part of the program:

    • IAM Role and Policy: We create an IAM role with a policy that allows Lambda to execute and log to CloudWatch.
    • Lambda Function: We define our Lambda function, setting the runtime, handler, and uploading our zipped codebase.
    • API Gateway: Set up an HTTP API Gateway as the front door to access our Lambda.
    • Lambda Integration: Create an integration to connect API routes to our Lambda function.
    • Route: A default $default route is used to forward all requests to the Lambda integration.
    • Deployment: We create a deployment to make our API live.
    • Stage: Stages are "environments" for deployments. We define a v1 stage.
    • Permissions: It's essential to give API Gateway permission to invoke your Lambda function.
    • Export API URL: Finally, we export the URL for the deployed API so that you can access it externally.

    To run this program, you must have:

    • Python 3 installed
    • Pulumi CLI installed
    • AWS CLI configured with credentials

    After setting your Pulumi project and installing the required Python packages, execute pulumi up to deploy the resources to AWS.

    Please replace "app.handler" and "./api_code.zip" with the appropriate handler path and Lambda deployment package path, respectively. The handler is the entry point to your application, typically formatted as "filename.method". The deployment package should contain your application code and all dependencies.