How should I properly to handle rate limiting when performing bulk capacity planning updates across multiple Genesys Cloud organizations via the Platform API?
Our AppFoundry integration synchronizes workforce data for a large enterprise client. We are currently using the POST /api/v2/wfm/capacityplanning/capacity endpoint to push updated shift data. The issue arises when processing more than 500 concurrent requests across ten different orgs. We are hitting strict rate limits, resulting in 429 Too Many Requests responses.
The standard backoff strategy documented in the API reference seems insufficient for our volume. We are using the Genesys Cloud Node.js SDK v4.5.0. Our current implementation retries with an exponential backoff starting at 1 second, doubling up to 32 seconds. However, the Retry-After header often suggests waiting significantly longer, sometimes up to 60 seconds, which breaks our real-time sync SLA.
We have attempted to stagger requests using a token bucket algorithm, but the rate limit appears to be applied per org, not globally. This means we are throttled on individual orgs even if the total request count across all orgs is within global limits.
Specific error details:
- Endpoint:
POST /api/v2/wfm/capacityplanning/capacity - Error Code: 429
- Message: “Too Many Requests”
- Retry-After: Variable (10-60 seconds)
Is there a recommended pattern for batching these requests? We considered using the bulk API endpoints, but those are limited to scheduling, not capacity planning. Should we be implementing a queueing mechanism on our end to serialize requests per org? Or is there a way to negotiate higher rate limits for AppFoundry partners?
Any insights from other partners dealing with high-volume WFM integrations would be appreciated. We need to maintain sub-minute latency for our dashboard updates.