edge-computing

# Edge Computing Edge runtimes move logic closer to users—with **strict CPU/time limits**, **different APIs** than full Node, and **tenant isolation** requirements. ## When to Offer This Workflow **Trigger conditions:** - Auth, redirects, or personalization at the CDN layer - HTML rewriting, A/B assignment, or bot mitigation at the edge - Global latency SLOs for read-heavy paths **Initial offer:** Use **six stages**: (1) workload fit, (2) edge vs origin split, (3) data & state, (4) security & tenancy, (5) limits & cost, (6) testing & rollout). Confirm platform (Workers, Lambda@Edge, Fastly Compute, etc.). --- ## Stage 1: Workload Fit **Goal:** Prefer short, CPU-light, request-scoped work—not long jobs or huge body buffering. **Exit condition:** Explicit list of what remains on origin (heavy SSR, large uploads). --- ## Stage 2: Edge vs Origin Split **Goal:** Document what runs where: geo headers, redirects, cache key logic, A/B bucketing, partial HTML injection. ### Practices - Cache `Vary` and cookie behavior documented to avoid wrong personalization leakage --- ## Stage 3: Data & State **Goal:** If using edge KV/Durable Objects/regional stores, state consistency (eventual vs strong) and rate of round-trips to origin. --- ## Stage 4: Security & Tenancy **Goal:** Validate JWT/session at edge; isolate tenants; never embed secrets in deploy bundles visible to clients. --- ## Stage 5: Limits & Cost **Goal:** Wall-clock CPU limits, request size caps, egress pricing; graceful degradation or fallback to origin. --- ## Stage 6: Testing & Rollout **Goal:** Canary per region/PoP; synthetics from multiple locations; compare p95 vs origin-only path. --- ## Final Review Checklist - [ ] Workload fits edge constraints - [ ] Edge vs origin responsibilities documented - [ ] State/consistency strategy clear - [ ] Multi-tenant security reviewed - [ ] Limits, cost, fallback documented - [ ] Multi-region validation performed ## Tips for Effective Guidance - Edge runtimes differ from full Node—verify available APIs (fs, streams, crypto). - Read platform-specific cold-start and isolate model docs. ## Handling Deviations - Hybrid: edge for headers/cache only; heavy compute stays on origin.