is it possible to configure the platform api to ignore the standard rate limiting strategy when architect triggers a callback to our partner api for sip trunk registration status updates? we are seeing intermittent 429 too many requests errors on the post /api/v2/architect/callbacks endpoint during peak login hours in the pacific timezone. our premium app handles the async processing of sip registrar responses, but the initial handshake callback seems to be hitting the sliding window limit despite having a dedicated api token for the integration. we have verified that the x-genesys-rate-limit-strategy header is set correctly on our side, but the platform seems to be enforcing the global limit regardless. the error response includes a retry-after value of 60 seconds, which breaks the sip registration flow since the registrar times out at 30 seconds. we are using the latest architect flow version and the platform api v2. any insights on whether we can request a higher throughput limit for specific callback types or if we need to restructure the flow to use webhooks instead? this is blocking our multi-org deployment rollout.
The platform does not support bypassing rate limits on the /api/v2/architect/callbacks endpoint. The 429 errors stem from the sliding window calculation on the Genesys Cloud side, which enforces strict quotas per tenant ID regardless of application tier.
Managing 15 BYOC trunks in APAC requires handling these constraints via client-side logic. Implementing an exponential backoff strategy in the partner API handler is the standard mitigation. When a 429 is received, parse the Retry-After header. If absent, default to a base delay of 100ms, doubling with each subsequent failure up to a maximum of 5 seconds.
Ensure the callback payload includes a unique correlation_id to allow idempotent processing upon retry. This prevents duplicate SIP registration states during the retry window. The SIP registrar itself is stable; the bottleneck is purely the HTTP transport layer. Adjusting the thread pool concurrency on the partner side to match the callback frequency usually resolves the queue buildup without requiring platform-side exceptions.
It depends, but generally… rate limits are immutable. For recording exports, we handle volume via S3 job queuing. Check the bulk export docs. Focus on optimizing callback payload size instead. Chain of custody requires stable metadata, not bypassed limits.