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April 18, 20256 min read

Edge Deployments Explained: Why Your Users Will Thank You

Moving compute closer to your users cuts latency by orders of magnitude. Here is what changes — and what does not — when you deploy to the edge.

LF

Lena Fischer

Staff Engineer


When a user in Tokyo hits an endpoint deployed in us-east-1, they are paying a ~150ms round-trip tax before your application code even runs. Edge deployments eliminate this tax by running your code in a datacenter geographically close to each request.

The shift is not just topological. Edge runtimes are typically V8-isolate-based (Cloudflare Workers, Deno Deploy) rather than Node.js processes, which means cold-start overhead drops from seconds to under a millisecond. You get a fundamentally different latency profile.

The trade-off is runtime constraints: no filesystem access, limited CPU time per request, and a smaller subset of Node.js APIs. For most HTTP handlers — routing, authentication, SSR, API proxying — these constraints are invisible. For heavy CPU work or legacy Node.js dependencies, you will need a hybrid strategy.

At Barefoot we run every deploy preview on the edge by default. Production traffic is automatically routed to the nearest region. The result: median TTFB under 40ms globally, without any application-level changes from our customers.

Getting started is straightforward. Annotate your handlers with `@edge` or set `runtime: "edge"` in your config. Barefoot handles region rollout, health checks, and failover automatically. If an edge region degrades, traffic silently reroutes to the next nearest healthy node.

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