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cloud-architecture-cloudflarelisted

Cloudflare edge/serverless architecture knowledge — compute (Workers isolates/Containers, smart placement), Pages, storage (R2/D1/KV/Durable Objects/Vectorize), messaging (Queues), AI (Workers AI/AI Gateway), and origin pooling (Hyperdrive/Cache API). CPU-time and subrequest limits, consistency tradeoffs, failure modes, and request+CPU pricing gotchas (no R2 egress). Activate when the active cloud is Cloudflare and the work involves designing, scaling, costing, or diagnosing Cloudflare architecture (Workers CPU limits, D1 write limits, KV eventual consistency, Durable Object single-threading, R2 egress savings, subrequest caps).
eric-sabe/engsys · ★ 1 · DevOps & Infrastructure · score 67
Install: claude install-skill eric-sabe/engsys
# Cloudflare Architecture Knowledge Service-level detail for a Cloudflare-backed project. Pairs with Melvin's cloud-agnostic diagnostic checklist (traffic pattern, state location, SLAs, blast radius, cost explosion, coordination, limits, observability) — this pack supplies the Cloudflare-specific answers for each. Cloudflare's model is fundamentally different from AWS/Azure: there are no regions you provision into and no VMs — code runs in **V8 isolates** at the edge POP nearest the user, and state lives in purpose-built edge primitives. For concrete project topology, cost tiers, and stack context, read the architecture docs named in `CLAUDE.md`. ## Compute ### Workers (isolates) - **No cold starts.** Workers run as **V8 isolates**, not containers/VMs — a new isolate spins up in <5ms (often "zero" perceived) because there's no OS/runtime boot. This is the headline architectural difference from Lambda/Cloud Functions/Container Apps: the "scale to zero costs you a cold start" tradeoff that dominates AWS/Azure design simply doesn't exist here. Design for it — short-lived, stateless request handlers are ideal. - **CPU-time limit, not wall-clock.** The cap is **CPU time**, default **30s** on paid, configurable up to **5 minutes** (`limits.cpu_ms` in `wrangler.toml`, max 300000). Free plan is **10ms** CPU/request. Crucially, **time spent awaiting I/O (fetch, KV, D1) does not count** against CPU time — a Worker can wait minutes on a slow subrequest and burn near-