What’s the best way to configure a Data Action within an Architect flow to handle high-latency responses from a legacy CRM integration without triggering a generic timeout error? The current setup utilizes a standard HTTP POST request to update customer records post-interaction. During peak hours in the Europe/Paris timezone, specifically between 10:00 and 12:00 CET, the integration endpoint experiences increased load, causing response times to exceed the default 30-second threshold. This results in a 504 Gateway Timeout error within the flow, causing the interaction to fail and requiring manual reprocessing by the quality team. The business requirement is to ensure that all customer data updates are persisted reliably, even if the response is delayed, without blocking the agent from returning to the queue. The current error logs indicate a failure at the ‘Update Customer Record’ step, with no clear indication of whether the request was eventually processed by the backend system or dropped entirely. This inconsistency makes it difficult to validate data integrity for compliance reporting.
The environment is a multi-tenant Genesys Cloud instance with BYOC configuration for edge clusters. The Data Action is configured with a retry policy of three attempts, with a 5-second delay between retries. Despite this, the cumulative timeout still exceeds the flow’s execution limits during high-traffic periods. The question is whether there is a recommended pattern for implementing asynchronous processing or queuing mechanisms within Architect to decouple the flow execution from the integration response time. Alternatively, is there a specific configuration in the Data Action settings that allows for longer timeout durations or better error handling for partial successes? The goal is to maintain a seamless agent experience while ensuring that all business-critical data updates are captured accurately. Any insights into best practices for integrating with high-latency external systems in this context would be appreciated, particularly regarding how to monitor and report on these asynchronous transactions within the Performance dashboard.