Is it possible to configure dynamic rate limit handling within a multi-org AppFoundry application that synchronizes messaging history across tenants? We are developing a premium integration that aggregates digital channel transcripts for analytics, requiring frequent polling of the /api/v2/analytics/conversations/details/query endpoint. The current implementation hits the standard platform API rate limits almost immediately when scaling to over five hundred concurrent user sessions, resulting in consistent 429 Too Many Requests responses. We have implemented exponential backoff logic, but this introduces significant latency that disrupts the real-time dashboard experience for our clients. The architecture involves OAuth2 token rotation per organization to maintain session validity, yet the aggregate request volume still exceeds the tenant-level throttling thresholds. We are looking for best practices regarding bulk data retrieval strategies or specific headers that might mitigate these restrictions without requiring enterprise support intervention. Has the community found a reliable pattern for high-frequency data extraction that respects the API governance while maintaining acceptable performance metrics?
According to the docs, they say that platform API endpoints do not support dynamic rate limit bypasses for standard integrations. When hitting the /api/v2/analytics/conversations/details/query endpoint with high concurrency, the system enforces strict throttling to protect backend stability. A common fix is to implement exponential backoff in the JMeter script rather than retrying immediately on 429 errors. This prevents the client from being blocked for longer periods. Additionally, consider using the streaming analytics API if available, as it reduces the number of polling requests needed. The default manifest generation often omits these fields for performance, assuming standard PSTN channels. For WebRTC metadata, ensure the include_webrtc_metadata flag is set in the request body.
- API rate limit headers (X-RateLimit-Remaining)
- Exponential backoff logic in JMeter
- Streaming vs Polling API endpoints
- WebSocket connection limits on BYOC Edge