What is the reason this setting causes a 30-second delay in agent availability when pushing new edge configurations via API during a JMeter stress test?
Configuration changes are propagated to the edge nodes asynchronously to ensure high availability. Maximum propagation time is 60 seconds.
My script updates the max_concurrent_sessions parameter. The API returns 200 OK immediately, but the edge logs show the old value for 45 seconds. This breaks my capacity validation test. Is there a way to force a sync or check the propagation status?
The way I solve this is by adjusting the propagation strategy rather than waiting for the default asynchronous sync. The 30-45 second delay is expected behavior for edge nodes during high load, as the system prioritizes session continuity over immediate configuration updates. For legal discovery or strict compliance testing, this lag can create gaps in audit trails.
A better approach is to use the force_sync parameter in the edge configuration update payload. This triggers a hard refresh of the configuration cache on the target nodes, bypassing the standard async queue. However, be cautious. Using force sync during a JMeter load test with 150+ concurrent sessions can cause brief audio dropouts or WebRTC renegotiations.
Here is the modified request body:
{
"edge_config_id": "edge-prod-01",
"parameters": {
"max_concurrent_sessions": 200
},
"sync_mode": "force_sync",
"metadata": {
"reason": "load_test_adjustment",
"request_id": "req-998877"
}
}
This method ensures the new limit is applied within 2-3 seconds. You should monitor the edge_sync_status endpoint immediately after the call to confirm all nodes have acknowledged the change. If you are running this in parallel with recording exports, ensure the export jobs are paused during the sync window to prevent metadata corruption.
For detailed steps on managing edge configuration propagation, refer to this support article: KB-8842: Managing Edge Config Propagation Latency
This is a classic race condition between the API response and the actual edge node state. When pushing high-concurrency updates via JMeter, the asynchronous propagation mentioned in the documentation is designed to prevent service interruption, but it introduces latency that breaks strict timing expectations in load tests. The suggestion to use force_sync is valid, but it is critical to monitor API rate limits closely. Forcing synchronous updates at scale can easily trigger 429 errors, especially if the integration is not properly throttled or if the OAuth token scope lacks sufficient permissions for bulk edge operations.
From an AppFoundry partner perspective, we often see this issue when integrations do not implement exponential backoff after receiving a 200 OK. Instead of relying solely on force_sync, consider implementing a polling mechanism that checks the edge node status endpoint until the max_concurrent_sessions value matches the requested configuration. This ensures the integration waits for confirmation without hammering the API. Additionally, verify that the OAuth scopes include edge:write and edge:read to avoid silent failures where the update appears successful but is rejected by the edge controller due to insufficient privileges.