A Typhoon Tracker Built in One Sleepless Night Is Now Open for Anyone to Harden

Disaster-information tools often fail exactly when they are needed most because they depend on databases, auth, or ad infrastructure that collapses under load or connectivity loss. This tracker’s architecture—a single stateless Worker, pure functions, and cache merging instead of overwriting—is a replicable pattern for any crisis dashboard where uptime is non-negotiable and the audience is panicked, mobile, and bandwidth-constrained.

Typhoon Bavi Tracker puts Chinese, Japanese, American, and Taiwanese forecast models on one MapLibre GL map so the convergence—or divergence—of predicted landfall is immediately visible. A city impact countdown estimates arrival time based on wind speed and vector math, while a shareable deep link focuses the map on a specific city. Real-time RSS news aggregation and a static emergency guide round out the tool, which runs entirely on a Cloudflare Worker with no database and a deliberate bias toward simplicity so it stays up when infrastructure around it fails.

The creator, HiSt, built it after finding no single source that answered three urgent questions during a typhoon: where it is, how long until it hits, and what to do now. The code is intentionally minimal—pure functions for normalization and impact calculation, a Worker that only proxies and caches, and a strict rule that a bad data fetch must never overwrite a good cache snapshot.

The repository is now open for contributions, with a task list prioritized by human impact over technical novelty. Adding a city is a one-line change; multi-typhoon support, localized shelter guides, PWA offline caching, and i18n are all on the roadmap. The project’s open-source rationale is blunt: disaster information should not be locked in anyone’s server, and a community can sustain what one person’s late-night burst of energy cannot.

A map style loading error is the main technical complaint, acknowledged by the author as a likely intermittent network glitch. Several people report the site failing to load or getting stuck fetching data. The speed of development draws curiosity about the underlying server setup and AI tooling, while a request for a technical deep-dive on the Cloudflare deployment template goes unanswered. One commenter notes a competing Zhejiang-based tracker but concedes this version packs more information.