Could someone clarify why the Data Action integration times out when syncing metadata for our 15 APAC BYOC trunks?
The Architect flow stalls at the HTTP request step. We see a 504 Gateway Timeout after 30 seconds, despite the endpoint responding in <2s via curl. This happens only during peak load in Asia/Singapore timezone.
{
"error": "GATEWAY_TIMEOUT",
"step": "sync_trunk_metadata"
}
Is there a hidden rate limit on the Analytics API?
This has the hallmarks of a classic case of the Data Action engine struggling with concurrent metadata writes rather than a network latency issue. When dealing with 15 BYOC trunks in APAC, the volume of metadata objects generated during peak hours can easily exceed the default throughput limits of the standard HTTP request step in Architect. The 504 timeout you are seeing is often the gateway dropping the connection because the downstream service is saturated with concurrent requests, even if individual endpoints respond quickly via curl.
For legal discovery and bulk export workflows, I usually recommend bypassing the synchronous HTTP request step entirely. Instead, use the Recording API to push metadata to an S3 bucket asynchronously. This decouples the trunk registration process from the metadata sync, preventing the gateway timeout. You can configure a Data Action to trigger a “Put Object” request to your S3 bucket whenever a new trunk metadata event occurs. This approach ensures that the chain of custody remains intact while offloading the processing burden from the Genesys Cloud gateway.
Here is a sample configuration for the Data Action:
{
"trigger": "TrunkMetadataUpdated",
"action": {
"type": "S3Upload",
"bucket": "legal-discovery-metadata-apac",
"key": "trunks/${trunkId}/metadata.json",
"payload": {
"trunkId": "${trunkId}",
"timestamp": "${timestamp}",
"metadata": "${metadata}"
}
}
}
This method also provides a clearer audit trail, which is critical for legal hold requirements. The S3 integration handles retries and backoff automatically, reducing the risk of data loss during peak load. Make sure your IAM roles have the necessary permissions for the S3 bucket to avoid access denied errors.