Data Action Timeout on Bulk CSV Import via Architect Integration Node

Can anyone clarify the expected behavior for long-running Data Actions when triggered from a high-concurrency Architect flow? I am running load tests to validate the ingestion pipeline for a large dataset. The goal is to process 10,000 records simultaneously using JMeter. The flow routes each record to a custom Data Action endpoint hosted on AWS API Gateway. This endpoint calls a Lambda function to parse and store the data in DynamoDB.

The issue occurs when the Lambda function takes more than 30 seconds to process the batch. The Architect integration node returns a 504 Gateway Timeout error immediately, even though the backend service eventually succeeds. I have checked the WebSocket connection limits in the Genesys Cloud environment, and they are stable. The problem seems to be strictly related to the HTTP request timeout configuration for outbound integrations.

I am using the Genesys Cloud v2 API. The environment is US1. The JMeter script is configured with 500 concurrent threads, looping 20 times. Each thread sends a POST request to the integration node. The payload contains a CSV string. The Lambda function processes this string and writes to the database. The average execution time for the Lambda is 45 seconds.

Here is the sample payload being sent to the Data Action:

{
 "input": {
 "csv_data": "id,name,email\n1,John,[email protected]\n2,Jane,[email protected]",
 "source": "load_test"
 }
}

The error response from Genesys Cloud is:

{
 "message": "The remote service did not respond in time.",
 "code": "504",
 "status": "Gateway Timeout"
}

I need to know if there is a way to increase the timeout for the integration node. Or if I should switch to an asynchronous pattern using webhooks. The current synchronous model is failing under load. Any advice on best practices for bulk data ingestion in Genesys Cloud Architect would be appreciated. I want to ensure the load test results are accurate and not skewed by timeout errors.

Have you tried decoupling the synchronous Architect flow from the heavy lifting in your AWS backend? Running 10,000 concurrent records through a single Data Action node is a recipe for hitting Genesys Cloud’s outbound connection limits and triggering aggressive timeout errors. The platform expects Data Actions to return within a few seconds. If your Lambda function takes longer than that to parse and store data in DynamoDB, the Architect node will likely fail, even if the backend eventually succeeds.

A more robust pattern for bulk imports is to use the Data Action solely as a fire-and-forget trigger. Instead of passing the full record payload to be processed synchronously, pass a unique job ID or batch identifier. Your AWS endpoint should then immediately enqueue the actual processing task to an SQS queue or Step Functions state machine. This allows the Data Action to return a 200 OK response quickly, keeping the Architect flow happy and preventing thread exhaustion on the Genesys side.

Here is how the payload structure should look to facilitate this async pattern:

{
 "batchId": "import-20231027-001",
 "recordCount": 10000,
 "webhookUrl": "https://your-app.com/callback/status",
 "metadata": {
 "source": "JMeter_Load_Test",
 "timestamp": "2023-10-27T14:00:00Z"
 }
}

This approach shifts the load away from the immediate API call. Your backend system can then process the DynamoDB writes in parallel batches without blocking the Genesys flow. It also provides a cleaner way to handle retries and error logging for failed records without crashing the entire integration node. Consider implementing a polling mechanism or a callback webhook to update the Architect flow once the bulk operation is complete, rather than expecting a single synchronous response.