Influencer monetization platforms depend entirely on accurate, up-to-the-minute engagement data. At Curved Lab, our background worker infrastructure continuously synchronizes video view counts, comments, and engagement rates across YouTube Data API v3, TikTok Open API v2, and Meta Graph API v18 for thousands of campaign deliverables.
However, each platform imposes drastically different rate-limiting constraints: YouTube enforces a strict 10,000-unit daily quota where search queries cost 100 units, while TikTok and Meta enforce short-window burst limits that trigger immediate 429 penalties. Here is how we architected a resilient background sync engine that never breaches upstream rate limits.
The Unified Rate Limiter: Redis Leaky Bucket
Rather than letting worker threads fire unmetered requests against third-party endpoints, all outgoing social API queries are queued through a distributed Redis Leaky Bucket coordinator. Each social network provider is assigned its own dedicated bucket with defined capacity and leak rates matching their official SLA constraints.
