How Workers powers our internal maintenance scheduling pipeline

This post details the development of a maintenance scheduling pipeline using Cloudflare Workers. Key technical contributions include: 1. Designing a graph processing interface inspired by Facebook's TAO to model objects (e.g., routers) and associations (e.g., Aegis pools) for maintenance constraints. 2. Implementing a fetch pipeline middleware layer for Workers to handle subrequest limits, including request deduplication (inspired by Go's singleflight), LRU caching, CDN caching, and backoff retries. 3. Demonstrating a 100x reduction in response sizes and achieving ~99% cache hit rate through targeted data fetching and the fetch pipeline.