Infrastructure & Edge
Run code close to where the work actually happens.
Place compute across edge runtimes, regional services, and container platforms without rewriting the application for each one.
Compute is no longer one tier. A request can be served from an edge runtime in milliseconds, from a regional container holding warm state, or from a long-running job in a home region. What matters next is placement: which work belongs where, and what it costs in latency, complexity, and portability to decide wrongly.
This is where architectures quietly lock in. A function written for one provider’s runtime is hard to move. Cold starts appear under real traffic. Regional services become the default because the edge tier could not reach the data it needed.
Edge Compute & Runtimes treats placement as a design decision rather than a default. It gives the team a clearer way to choose runtimes, contain provider-specific surface area, and keep the same application deployable across Cloudflare Workers, AWS Lambda, Google Cloud Run, and Azure Functions. What matters next is latency, portability, and a clearer way to scale.
Let’s get going
- Start with one latency-sensitive path — Pick a single route, API, or rendering path where moving compute closer to the request produces a measurable improvement without touching the rest of the system.
- Separate the runtime from the logic — Keep provider-specific bindings at the edge of the codebase so the same handler can run on an edge runtime, a container, or a regional function.
- Prove the placement under real traffic — Measure cold starts, tail latency, and cost at the chosen tier before extending the pattern across the application.
Outcomes
- Lower latency at the edge — Requests are served closer to users, with fewer round trips to a home region and steadier behavior under uneven global load.
- Portable application surface — Provider-specific code stays contained, so runtime decisions can change without a rewrite.
- Predictable scaling behavior — Compute scales with traffic in a way the team can reason about, model, and budget for.