My current config is completely failing…
Inspecting the request headers shows correct Authorization Bearer tokens. Any insights on the throttling logic for script actions?
This has the hallmarks of a classic concurrency bottleneck rather than a standard rate limit issue. The scripting API has strict burst thresholds that trip quickly during load tests, even if the hourly quota remains open.
Try implementing an exponential backoff strategy in your Architect flow. Wrap the REST action in a loop with a delay step. This smooths the request spike and prevents the 429 rejection entirely.
Make sure you check how your Architect flow handles the initial burst of requests before applying generic backoff. Coming from a Zendesk background, we often rely on the platform to queue and throttle internally, but Genesys Cloud’s Scripting API is much stricter about concurrent execution limits per tenant. The 429 error here isn’t just about total volume; it’s about the spike of simultaneous connections trying to execute the same script version.
Instead of a simple delay loop, which can slow down overall throughput, consider implementing a “throttling gate” using a Data Action. You can create a simple SQL or HTTP action that checks a shared state (like a database row or a lightweight external counter) to limit active executions. This mimics the queueing behavior we are used to in Zendesk ticket routing but gives you explicit control in Genesys Cloud.
Here is a conceptual structure for the Architect flow:
flow:
- step: check_throttle
type: data_action
action: check_concurrent_count
on_success:
- step: execute_script
type: script_action
script_id: "your_script_uuid"
on_success:
- step: decrement_count
type: data_action
action: release_slot
- step: wait_retry
type: wait
duration: 500ms # Small jitter to avoid thundering herd
on_timeout:
- goto: check_throttle
This approach prevents the API from rejecting requests by managing concurrency at the flow level. It’s a bit more setup than Zendesk’s automatic handling, but it ensures stability during load tests. Also, verify that your script version is published and stable; unpublished drafts can sometimes cause unexpected latency spikes that trigger throttling.
You need to reconsider the assumption that a simple delay loop solves the concurrency bottleneck. While exponential backoff is a standard pattern, applying it blindly to Scripting API calls during high-concurrency load tests often masks deeper architectural flaws rather than resolving them. The 429 error you are seeing is likely not just about total volume but specifically about the spike of simultaneous connections trying to execute the same script version. Genesys Cloud’s Scripting API enforces strict concurrent execution limits per tenant, which are significantly tighter than general REST API rate limits.
When managing multiple BYOC trunks, I have observed similar behavior where burst traffic triggers these limits even if the hourly quota appears open. The issue is that the platform queues requests internally, but once the concurrent threshold is hit, it rejects new executions immediately. A simple delay loop does not address the root cause of the spike; it merely spreads it out, which can still overwhelm the API if the load test continues to generate requests faster than they can be processed.
Instead, consider decoupling the script execution from the immediate user interaction. Use a Data Action to queue the job for asynchronous processing. This approach ensures that the request is accepted and handled in the background, preventing the 429 error from impacting the user experience. Here is a recommended configuration for handling this:
| Component | Configuration |
|---|---|
| Data Action | Queue job for async processing |
| Retry Policy | Exponential backoff with jitter |
| Max Retries | 3 |
| Timeout | 5000ms |
This method aligns with best practices for handling bulk operations and high-concurrency scenarios. It also provides better visibility into job status and allows for more granular control over error handling. Ensure that your Architect flow is designed to handle asynchronous responses correctly, as this will require adjustments to how you track and manage the execution state.
The official documentation states that script execution limits are tied to concurrent runtime slots, not just api request counts. when you see 429s despite available headers, it is usually because the platform has hit the max concurrent script instances for that specific version. this is different from standard api rate limiting.
check the performance dashboard under queue activity or agent performance views. if you see a spike in “script execution errors” or “timeout” metrics during the load test, it confirms the bottleneck is resource contention, not network throttling. the suggestion above about backoff helps, but you also need to review the script complexity. if the script triggers heavy rest api calls internally, it holds the execution slot longer, causing more collisions.
try simplifying the script logic or increasing the timeout threshold in the flow configuration. also, verify if the script is being cached correctly. if each request triggers a fresh compilation, the overhead will trigger the 429s faster. focus on the execution duration metrics in the dashboard to identify if the scripts are running longer than expected.