Calling AWS Lambda from Genesys Architect: IAM Role Configuration and Invocation

What You Will Build

• A Python script that retrieves your Genesys Cloud OAuth token and uses the requests library to invoke a specific AWS Lambda function via the Genesys Cloud Data Action API.
• A Terraform configuration that creates the necessary AWS IAM Role and Policy to allow Genesys Cloud to assume the role and invoke the Lambda function.
• The integration logic to map Genesys conversation context to Lambda input parameters.

Prerequisites

• Genesys Cloud Account: An organization with an active subscription that includes the Architect feature.
• AWS Account: An active account with permissions to create IAM Roles, IAM Policies, and Lambda functions.
• IAM Permissions: You must have the iam:CreateRole, iam:AttachRolePolicy, and lambda:CreateFunction permissions in your AWS account.
• SDK/API Version: Genesys Cloud Platform API v2.
• Language/Runtime: Python 3.9+ for the invocation script; Terraform 1.0+ for the infrastructure setup.
• External Dependencies:
  • Python: requests, python-dotenv
  • Terraform: aws provider

Authentication Setup

To interact with the Genesys Cloud API, you must use OAuth 2.0 Client Credentials flow. Genesys Cloud does not support username/password authentication for API access. You need a Machine-to-Machine (M2M) application registered in Genesys Cloud.

1. Go to Admin > Security > OAuth 2.0.
2. Create a new Client ID.
3. Assign the following scopes to the client:
   • data:action:execute (Required to invoke data actions)
   • architect:flow:view (Optional, for verifying the data action configuration)

The following Python code demonstrates how to acquire and cache a token. In a production environment, you should implement token caching to avoid hitting the /oauth/token endpoint on every request, as this is rate-limited.

import requests
import os
from typing import Optional

class GenesysAuth:
    def __init__(self, client_id: str, client_secret: str, base_url: str):
        self.client_id = client_id
        self.client_secret = client_secret
        self.base_url = base_url.rstrip('/')
        self.token_url = f"{self.base_url}/oauth/token"
        self.access_token: Optional[str] = None

    def get_access_token(self) -> str:
        """
        Retrieves an OAuth access token from Genesys Cloud.
        Returns the raw token string.
        """
        if self.access_token:
            return self.access_token

        headers = {
            "Content-Type": "application/x-www-form-urlencoded"
        }
        data = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret
        }

        response = requests.post(
            self.token_url,
            headers=headers,
            data=data
        )

        if response.status_code != 200:
            raise Exception(f"Failed to acquire token: {response.status_code} {response.text}")

        token_data = response.json()
        self.access_token = token_data.get("access_token")
        
        if not self.access_token:
            raise Exception("Access token not found in response")

        return self.access_token

Implementation

Step 1: Configure AWS IAM Role for Genesys Cloud

Genesys Cloud acts as an external entity that needs to assume an IAM role in your AWS account to invoke Lambda functions. You cannot pass AWS credentials directly into Genesys Cloud. Instead, you configure a Trust Relationship.

The trusted entity for Genesys Cloud is specific. You must allow the Genesys Cloud service principal to assume the role.

Create a file named main.tf with the following Terraform configuration. This creates the IAM Role and attaches the necessary policy to allow Lambda invocation.

# main.tf

terraform {
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
}

provider "aws" {
  region = "us-east-1"
}

# 1. Define the IAM Policy Document for the Role
data "aws_iam_policy_document" "genesys_assume_role" {
  statement {
    actions = ["sts:AssumeRole"]

    principals {
      type        = "Service"
      identifiers = ["genesyscloud.amazonaws.com"]
    }

    # Optional: Restrict to specific external IDs if required by your security policy
    # condition {
    #   test     = "StringEquals"
    #   variable = "sts:ExternalId"
    #   values   = ["your-external-id-here"]
    # }
  }
}

# 2. Create the IAM Role
resource "aws_iam_role" "genesys_lambda_invoker" {
  name               = "GenesysCloudLambdaInvoker"
  assume_role_policy = data.aws_iam_policy_document.genesys_assume_role.json
}

# 3. Define the Policy to Allow Lambda Invocation
data "aws_iam_policy_document" "lambda_invoke_policy" {
  statement {
    actions = [
      "lambda:InvokeFunction",
    ]

    resources = [
      # Replace with your actual Lambda ARN or use a variable
      "arn:aws:lambda:us-east-1:123456789012:function:MyGenesysLambda"
    ]
  }
}

# 4. Attach the Policy to the Role
resource "aws_iam_role_policy" "genesys_lambda_invoke" {
  name = "AllowLambdaInvoke"
  role = aws_iam_role.genesys_lambda_invoker.id

  policy = data.aws_iam_policy_document.lambda_invoke_policy.json
}

# Output the Role ARN for use in Genesys Cloud
output "iam_role_arn" {
  value = aws_iam_role.genesys_lambda_invoker.arn
}

Apply this configuration using terraform apply. Record the iam_role_arn output. This ARN is required for the Genesys Cloud Data Action configuration.

Step 2: Configure the Data Action in Genesys Cloud

While the primary focus is code, the Data Action must exist in Genesys Cloud to be invoked. You can create this via the UI or API. Here is the API approach to create a Data Action that invokes a Lambda function.

The Data Action definition requires the type to be aws-lambda. You must provide the arn of the Lambda function and the roleArn of the IAM role created in Step 1.

def create_lambda_data_action(auth: GenesysAuth, name: str, lambda_arn: str, role_arn: str):
    """
    Creates a Data Action in Genesys Cloud that invokes an AWS Lambda function.
    
    Args:
        auth: GenesysAuth instance
        name: Name of the Data Action
        lambda_arn: ARN of the AWS Lambda function
        role_arn: ARN of the IAM Role Genesys Cloud will assume
    """
    token = auth.get_access_token()
    base_url = auth.base_url
    endpoint = f"{base_url}/api/v2/architect/datadefinitions"

    # Define the Data Action body
    data_action_body = {
        "name": name,
        "type": "aws-lambda",
        "description": "Invokes AWS Lambda from Genesys Architect",
        "properties": {
            "arn": lambda_arn,
            "roleArn": role_arn,
            "timeout": 30000 # Timeout in milliseconds
        },
        "inputParameters": [
            {
                "name": "conversationId",
                "description": "The unique ID of the Genesys conversation"
            },
            {
                "name": "transcript",
                "description": "The current transcript of the conversation"
            }
        ],
        "outputParameters": [
            {
                "name": "responseMessage",
                "description": "Message returned from Lambda"
            }
        ]
    }

    headers = {
        "Authorization": f"Bearer {token}",
        "Content-Type": "application/json"
    }

    response = requests.post(
        endpoint,
        headers=headers,
        json=data_action_body
    )

    if response.status_code in [200, 201]:
        print(f"Data Action created successfully: {response.json().get('id')}")
        return response.json().get('id')
    else:
        raise Exception(f"Failed to create Data Action: {response.status_code} {response.text}")

Step 3: Invoke the Data Action via API

Once the Data Action is created, you can invoke it. In Architect, this is done via a “Data Action” block. Programmatically, you use the /api/v2/analytics/conversations/details/query endpoint for analytics, but for real-time invocation during a flow, you typically use the specific Data Action execution endpoint or simulate the flow execution.

However, the most direct way to test and invoke a Data Action outside of a running flow is using the data:action:execute scope. Genesys Cloud does not expose a direct “execute data action by ID” endpoint for arbitrary invocation outside of a flow context in the public API documentation for general use. Instead, Data Actions are primarily consumed within Architect Flows.

To demonstrate the mechanism of how Genesys Cloud invokes Lambda, we will look at how you would test the Lambda function directly with the payload structure Genesys Cloud sends, and then how to verify the Data Action configuration via API.

Testing the Lambda Payload Structure:

Genesys Cloud sends a JSON payload to the Lambda function. The structure depends on your inputParameters definition.

import json

def simulate_genesys_payload(conversation_id: str, transcript: str) -> dict:
    """
    Simulates the payload Genesys Cloud sends to the Lambda function.
    """
    payload = {
        "conversationId": conversation_id,
        "transcript": transcript,
        "genesysContext": {
            "organizationId": "your-org-id",
            "flowId": "your-flow-id",
            "timestamp": "2023-10-27T10:00:00Z"
        }
    }
    return payload

# Example usage
test_payload = simulate_genesys_payload("conv-123456", "Customer: Hello, I need help.")
print(json.dumps(test_payload, indent=2))

Verifying Data Action Configuration:

To ensure the IAM role and Lambda ARN are correctly set, you can fetch the Data Action definition.

def get_data_action(auth: GenesysAuth, data_action_id: str):
    """
    Retrieves a Data Action definition to verify configuration.
    """
    token = auth.get_access_token()
    base_url = auth.base_url
    endpoint = f"{base_url}/api/v2/architect/datadefinitions/{data_action_id}"

    headers = {
        "Authorization": f"Bearer {token}"
    }

    response = requests.get(
        endpoint,
        headers=headers
    )

    if response.status_code == 200:
        return response.json()
    else:
        raise Exception(f"Failed to retrieve Data Action: {response.status_code} {response.text}")

Complete Working Example

This script combines authentication, Data Action creation, and verification. It assumes you have already created the Lambda function and IAM role in AWS.

import os
import requests
from typing import Optional, Dict, Any

# --- Configuration ---
GENESYS_CLIENT_ID = os.getenv("GENESYS_CLIENT_ID")
GENESYS_CLIENT_SECRET = os.getenv("GENESYS_CLIENT_SECRET")
GENESYS_BASE_URL = os.getenv("GENESYS_BASE_URL", "https://api.mypurecloud.com")
LAMBDA_ARN = os.getenv("AWS_LAMBDA_ARN")
IAM_ROLE_ARN = os.getenv("AWS_IAM_ROLE_ARN")
DATA_ACTION_NAME = "TestLambdaInvocation"

# --- Authentication Class ---
class GenesysAuth:
    def __init__(self, client_id: str, client_secret: str, base_url: str):
        self.client_id = client_id
        self.client_secret = client_secret
        self.base_url = base_url.rstrip('/')
        self.token_url = f"{self.base_url}/oauth/token"
        self.access_token: Optional[str] = None

    def get_access_token(self) -> str:
        if self.access_token:
            return self.access_token

        headers = {"Content-Type": "application/x-www-form-urlencoded"}
        data = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret
        }

        response = requests.post(self.token_url, headers=headers, data=data)
        
        if response.status_code != 200:
            raise Exception(f"Auth failed: {response.status_code} {response.text}")

        self.access_token = response.json().get("access_token")
        return self.access_token

# --- API Functions ---
def create_lambda_data_action(auth: GenesysAuth, name: str, lambda_arn: str, role_arn: str) -> str:
    token = auth.get_access_token()
    endpoint = f"{auth.base_url}/api/v2/architect/datadefinitions"

    data_action_body = {
        "name": name,
        "type": "aws-lambda",
        "description": "Automated Lambda Data Action",
        "properties": {
            "arn": lambda_arn,
            "roleArn": role_arn,
            "timeout": 30000
        },
        "inputParameters": [
            {"name": "inputValue", "description": "Value to process"}
        ],
        "outputParameters": [
            {"name": "result", "description": "Processed result"}
        ]
    }

    headers = {
        "Authorization": f"Bearer {token}",
        "Content-Type": "application/json"
    }

    response = requests.post(endpoint, headers=headers, json=data_action_body)
    
    if response.status_code in [200, 201]:
        action_id = response.json().get('id')
        print(f"Created Data Action ID: {action_id}")
        return action_id
    else:
        raise Exception(f"Creation failed: {response.status_code} {response.text}")

def verify_data_action(auth: GenesysAuth, data_action_id: str) -> Dict[str, Any]:
    token = auth.get_access_token()
    endpoint = f"{auth.base_url}/api/v2/architect/datadefinitions/{data_action_id}"
    
    headers = {"Authorization": f"Bearer {token}"}
    response = requests.get(endpoint, headers=headers)
    
    if response.status_code != 200:
        raise Exception(f"Verification failed: {response.status_code} {response.text}")
    
    return response.json()

# --- Main Execution ---
def main():
    if not all([GENESYS_CLIENT_ID, GENESYS_CLIENT_SECRET, LAMBDA_ARN, IAM_ROLE_ARN]):
        raise EnvironmentError("Missing required environment variables")

    try:
        # 1. Authenticate
        auth = GenesysAuth(GENESYS_CLIENT_ID, GENESYS_CLIENT_SECRET, GENESYS_BASE_URL)
        print("Authentication successful.")

        # 2. Create Data Action
        action_id = create_lambda_data_action(auth, DATA_ACTION_NAME, LAMBDA_ARN, IAM_ROLE_ARN)

        # 3. Verify Configuration
        config = verify_data_action(auth, action_id)
        print("Data Action Configuration:")
        print(f"  Name: {config['name']}")
        print(f"  Type: {config['type']}")
        print(f"  Lambda ARN: {config['properties']['arn']}")
        print(f"  Role ARN: {config['properties']['roleArn']}")

    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    main()

Common Errors & Debugging

Error: 403 Forbidden - IAM Role Trust Relationship

Cause: The IAM Role created in AWS does not allow the Genesys Cloud service principal to assume it.
Fix: Ensure the trust policy includes "Service": "genesyscloud.amazonaws.com". If you are using an External ID, ensure it matches exactly in both the IAM policy condition and the Genesys Cloud configuration (if exposed).

// Correct Trust Policy Example
{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "Service": "genesyscloud.amazonaws.com"
      },
      "Action": "sts:AssumeRole"
    }
  ]
}

Error: 403 Forbidden - Lambda Permission Missing

Cause: The IAM Role attached to the Data Action does not have the lambda:InvokeFunction permission for the specific Lambda ARN.
Fix: Attach a policy to the IAM Role that explicitly allows invocation of the target Lambda.

// Correct Inline Policy Example
{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": "lambda:InvokeFunction",
      "Resource": "arn:aws:lambda:us-east-1:123456789012:function:MyGenesysLambda"
    }
  ]
}

Error: 500 Internal Server Error - Lambda Timeout

Cause: The Lambda function takes longer to execute than the timeout configured in the Data Action.
Fix: Increase the timeout property in the Data Action definition (max 30,000 ms for synchronous invocations) or optimize the Lambda code.

Error: 401 Unauthorized - Invalid Token

Cause: The OAuth token has expired or was generated with insufficient scopes.
Fix: Ensure the M2M client has the data:action:execute scope. Regenerate the token if it is older than the expiry time (usually 1 hour).

Official References

• Genesys Cloud Data Actions API Documentation
• AWS IAM Roles for Service
• AWS Lambda Permissions
• Genesys Cloud OAuth 2.0