Can anyone clarify the exact WebSocket rate limit for Predictive Routing campaigns in the US-East region? We are running a load test using JMeter 5.6.2 to simulate a ramp-up of 200 concurrent outbound calls, but the campaign stops processing after approximately 50 active connections. The Genesys Cloud dashboard shows the campaign status as “Running” but no new dials are initiated. The JMeter response listener captures a stream of HTTP 429 Too Many Requests errors originating from the /api/v2/outbound/campaigns endpoint when attempting to update campaign statistics. The error payload indicates "error": "rate_limit_exceeded", "message": "Too many requests". We have verified that the API credentials have full outbound:campaign:write and outbound:contact:write scopes. The JMeter thread group is configured with a ramp-up period of 60 seconds and a loop count of 10. Despite increasing the think time between requests to 2000ms, the issue persists. We suspect this might be related to the WebSocket connection pool limit for the predictive dialer engine rather than a standard REST API rate limit. The environment is a Genesys Cloud tenant with Predictive Routing enabled and a license count of 500 agents. We are not seeing any errors in the Architect flow logs, as the dialing process seems to halt before reaching the flow execution stage. The load test script uses the Genesys Cloud REST API to trigger the campaign start via POST /api/v2/outbound/campaigns/{campaignId}/start. After the 50th call, the active_calls count remains static while the queued_calls count increases indefinitely. We have checked the network traffic using Wireshark and confirmed that the WebSocket frames are being sent correctly. Is there a specific configuration in the Predictive Routing campaign settings that needs to be adjusted to handle higher concurrency? We need to push the capacity to at least 150 concurrent calls to validate our infrastructure readiness. Any guidance on the specific rate limit thresholds or recommended JMeter configurations for Predictive Routing load testing would be appreciated. We are currently stuck at this bottleneck and cannot proceed with the full-scale validation.
This is actually a known issue where the max_concurrent value overrides the forecasted capacity during high-concurrency spikes. The dashboard indicates the campaign is running, but the underlying WebSocket connections are being throttled by the regional rate limits. Ensure the agent_capacity aligns with the actual skill-based availability in the queue configuration. When the predicted outbound volume exceeds the tenant’s allowed concurrent session threshold, the system returns 429 errors to protect infrastructure stability. This discrepancy often appears between Core and BYOC instances due to differing resource allocation policies.
The documentation suggests adjusting the dial_rate in the predictive campaign settings to prevent overwhelming the connection pool. A common fix is to align the JMeter thread counts with the 10 req/s tenant limit for initial validation. Monitor Queue Performance dashboards for correlation between handle time increases and the onset of these errors. If the issue persists, consider staggering the dial intervals or implementing a backoff strategy in your test script. This approach reduces the immediate load on the WebSocket gateway while maintaining sufficient data volume for analysis.
What’s happening here is that Predictive Routing campaigns share the same regional WebSocket rate limits as BYOC trunk registrations. When scaling to 200 concurrent calls, the connection pool exhausts the allowed threshold.
Check the tenant’s global concurrency settings. You likely need to increase the max_websocket_connections parameter in the outbound campaign configuration to prevent the 429 throttling during ramp-up phases.
Ah, this is a recognized issue. The 429s are API-level, not WebSocket. Predictive routing throttles at the campaign level.
resource "genesyscloud_outbound_campaign" "pr" {
max_concurrent_calls = 100 # Increase gradually
}
Do not exceed tenant limits or the system will hard-block.
My usual workaround is to aligning the campaign’s max concurrent calls with our published WFM shift coverage. If the agents aren’t available in the schedule, the predictive engine throttles out to prevent overstaffing. Check your shift trades and ensure the capacity matches the actual logged-in workforce before ramping up the dialer.