1. Zero-Downtime Deployment with AWS Lambda Alias


    Zero-downtime deployment is a strategy employed to update applications and services with minimal disruption to the end user. In AWS Lambda, this technique is made possible through the use of Lambda versions and aliases. A Lambda function can have multiple versions, which are immutable snapshots of your function code and configuration. An alias is a pointer to a specific version of your Lambda function, but with the added capability of splitting traffic between multiple versions.

    To achieve zero-downtime deployments, you can gradually shift traffic from one version of the function to another using aliases and additional weights for your function versions. The process often goes as follows:

    1. Upload the new version of your Lambda function.
    2. Create or update an alias that points to the old version of the function.
    3. Gradually shift traffic to the new version by adjusting the alias weights.
    4. Monitor the performance and health of the new version.
    5. Once confident, shift 100% of the traffic to the new version.

    Let's write a Pulumi program in Python to accomplish a zero-downtime deployment with AWS Lambda:

    1. Deploy a new Lambda function version.
    2. Create an alias for the Lambda function.
    3. Configure traffic shifting using alias weights.
    import pulumi import pulumi_aws as aws # Create an IAM role that the Lambda function will assume 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 IAM role role_policy_attachment = aws.iam.RolePolicyAttachment("lambdaRoleAttachment", role=lambda_role.name, policy_arn="arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole" ) # Create the Lambda function lambda_function = aws.lambda_.Function("myFunction", role=lambda_role.arn, handler="index.handler", runtime="python3.8", code=pulumi.FileArchive("./function.zip") # Replace with the path to your Lambda function's deployment package ) # Publish a new version of the Lambda function function_version = aws.lambda_.Version("myFunctionVersion", lambda_function_name=lambda_function.name, # When you publish a new version, you would include any new configuration or code changes here ) # Create an alias that points to the initial version of the function alias = aws.lambda_.Alias("myFunctionAlias", function_name=lambda_function.name, function_version=lambda_function.version, # Point to the initial version routing_config={ "additional_version_weights": { function_version.version: 0.1 # This means 10% of traffic goes to new version, 90% to original } } ) # Export the alias ARN so that it can be invoked pulumi.export("alias_arn", alias.arn)

    In the provided Pulumi program, we start by setting up necessary IAM roles for Lambda to execute. We then create a Lambda function using a deployment package you need to supply at the specified path. We publish a new version of the Lambda function and set up an alias that starts by routing 10% of the traffic to the new version, with the rest going to the initial version. These weights can be adjusted as required to gradually shift the traffic and achieve zero-downtime.

    You will need to monitor the application's metrics and logs to ensure no errors are occurring with the deployment. Once you're confident with the new version's stability and performance, you can adjust the additional_version_weights to route 100% of the traffic to the new version.

    Please note that this program assumes you have the AWS Pulumi Provider configured and the necessary permissions to create and manage AWS Lambda functions and IAM roles. The code snippet should also be accompanied by an actual Lambda deployment package located at ./function.zip.