Hello colleagues. I am participating in the early beta for Genesys Cloud Predictive Routing. My current task is to synchronize our custom agent proficiency scores into the platform using the routing API. Because we have many agents, our Python script makes thousands of PUT requests to /api/v2/routing/skills and /api/v2/routing/predictive/kpis. I receive the error 429 Too Many Requests very often, which forces my script to pause and delays the entire synchronization process. Is there a more efficient way to update predictive routing data in bulk without triggering these API rate limits?
Hello. I perform performance load testing for large deployments. The standard Platform API restricts you to 300 requests per minute per token.
If you send thousands of requests at the same time, the API gateway will immediately block your application to protect the platform. When you do a massive update like this, you should try to use a bulk endpoint.
For routing skills, you can use the bulk update endpoint /api/v2/routing/skills/bulk which allows you to update multiple records in one single HTTP request. This will solve your 429 errors instantly.
For continuous synchronization of Predictive Routing data at scale, utilizing synchronous REST APIs is fundamentally inefficient. Architecturally, you must decouple the sync process. Deploy an AWS EventBridge integration bound to the Genesys Cloud event bus.
Route the v2.routing.queues.{id}.users events directly to an Amazon SQS queue. An AWS Lambda function can then process these messages asynchronously, aggregate the KPI score updates, and execute the bulk PUT requests in controlled batches.
This eliminates the rate limiting constraints and reduces overall API consumption.