create-function

--function-name <value>

[--runtime <value>]

--role <value>

[--handler <value>]

[--code <value>]

[--description <value>]

[--timeout <value>]

[--memory-size <value>]

[--publish | --no-publish]

[--vpc-config <value>]

[--package-type <value>]

[--dead-letter-config <value>]

[--environment <value>]

[--kms-key-arn <value>]

[--tracing-config <value>]

[--tags <value>]

[--layers <value>]

[--file-system-configs <value>]

[--image-config <value>]

[--code-signing-config-arn <value>]

[--architectures <value>]

[--zip-file <value>]

[--cli-input-json <value>]

[--generate-cli-skeleton <value>]

Many people consider AWS Lambda to be a little confusing, but it is not. 

It is just a simple four-step process that begins with uploading code to AWS Lambda.

The next step is to set up your code to trigger from other AWS services, HTTP endpoints, or mobile apps.

AWS Lambda will only run a code when it is triggered and will only use the computing resources needed to run it.

fn = lambda_.Function(self, "MyFunction",

    runtime=lambda_.Runtime.NODEJS_16_X,

    handler="index.handler",

    code=lambda_.Code.from_asset(path.join(__dirname, "lambda-handler"))

)

import boto3

from azure.identity import DefaultAzureCredential

from azure.graphrbac import GraphRbacManagementClient

​

def lambda_handler(event, context):

    # Configure Azure AD authentication

    credential = DefaultAzureCredential()

    tenant_id = '<your-azure-ad-tenant-id>'

    subscription_id = '<your-azure-subscription-id>'

    graph_client = GraphRbacManagementClient(credential, tenant_id)

​

    # Retrieve user information from Azure AD

    user_id = event['user_id']  # Assuming the user ID is passed in the Lambda event

    user = graph_client.users.get(user_id)

    organization = graph_client.organizational_hierarchies.get(user.user_principal_name)

​

    # Transform and map hierarchy data

    agent_hierarchy = transform_hierarchy(organization)

​

    # Update Amazon Connect agent hierarchy

    connect_client = boto3.client('connect')

    update_agent_hierarchy(connect_client, agent_hierarchy)

​

    return {

        'statusCode': 200,

        'body': 'Agent hierarchy updated successfully.'

    }

​

def transform_hierarchy(organization):

    # Transform and map the Azure AD organization hierarchy to Amazon Connect agent hierarchy

    # Implement your logic here based on your specific mapping requirements

    # Return the transformed hierarchy structure

    pass

​

def update_agent_hierarchy(connect_client, agent_hierarchy):

    # Update the Amazon Connect agent hierarchy using the provided agent_hierarchy

    # Implement the necessary logic to create or update queues, routing profiles, etc.

    # using the connect_client

    pass