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What happens to a request when it hits a Netlify Edge Function?
The path has several stages: the edge node handles TLS and route matching; Netlify identifies the service and selects a compute node; that node locates or fetches the required images; then a MicroVM runs the function and returns its response to the request chain.
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1. The edge node terminates TLS and matches the route
Netlify says a request arrives at the edge node closest to the client. That node terminates TLS and checks the request path against the Edge Function routes configured for the deploy. If no route matches, the request continues along the ordinary cache-and-origin path. If a route matches, the edge node forwards it to a compute node within Netlify’s network. Previously, the matched request left Netlify’s network for a hosted execution service before returning.
2. The edge node describes the function service
Before forwarding the request, the edge node writes a machine specification. It names three images—the runtime, Netlify’s platform image, and the customer’s Edge Function image—and sets CPU, memory, and connection limits. The specification accompanies each request.
Netlify combines a hash of that specification with site-specific information to produce a service ID. As Netlify describes it, differences in code or environment variables result in separate services rather than sharing a MicroVM. Netlify presents this separation as a security-isolation property.
3. A compute node finds the service and its images
The selected compute node checks whether the service ID already exists. If it does, the node forwards the request into that service’s MicroVM. If not, it creates the service and checks whether its required images are already on disk. Missing images are fetched from the edge node. Netlify says this means a region fetches only images for functions that receive traffic there.
4. Node affinity helps keep services warm
Netlify uses rendezvous hashing so that requests for the same service tend to reach the same compute node. This can keep the MicroVM warm and the function code on disk and in cache, reducing cold starts. The trade-off is concentration: too much stickiness can leave a popular service overloading one node.
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Netlify says it relaxes stickiness above a threshold and spreads the service across a slice of nodes to handle traffic spikes and limit interference with other services. A node encountering the function for the first time must fetch and cache its code, so that first request bears the fetch cost.
5. A Firecracker MicroVM starts or restores and runs the function
Each Edge Function runs in its own Firecracker MicroVM. Netlify reports that MicroVM creation takes under a millisecond and start time is about 2 ms at p99. The environment uses a stripped-down Linux system. Its uncompressed EROFS image is mounted and memory-mapped, so the system need not read unused portions of the bundle before execution.
Netlify says it takes snapshots after the JavaScript server begins listening. When a MicroVM becomes idle, it scales to zero; the next invocation starts from a snapshot. The snapshot is also memory-mapped, avoiding the need to wait for the entire snapshot to be read into memory. Netlify credits Unikraft’s product with managing boot, snapshot, restore, and scale-to-zero.
6. The function response rejoins Netlify’s request chain
An Edge Function can return a response directly, redirect, rewrite to a URL on the same site, modify a downstream response as middleware, or continue the chain. A direct response ends the chain. If a function returns undefined or an empty return, processing continues. After Edge Functions for the initial path have run, Netlify evaluates redirect rules and proceeds to static content or a serverless function as applicable. The API behavior is documented in Netlify’s Edge Functions API documentation.
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In its September 29, 2026 announcement, Netlify reported a warm-invocation median (p50) of about 5–6 ms on the new infrastructure, compared with 25–40 ms on the previous infrastructure. Netlify defines the warm measurement as routing to a compute node, entering the MicroVM, running the function, and producing response headers. It is not the elapsed time for every full page request, which can also include network, origin, browser, and application work.
| Metric | Netlify’s reported figure and scope |
|---|---|
| Warm invocation median (p50) | About 5–6 ms on the new infrastructure, versus 25–40 ms on the previous infrastructure; Netlify, September 29, 2026. |
| p99 invocations | 47.4% faster; Netlify, September 29, 2026. |
| Availability | 99.998%; Netlify, September 29, 2026. |
| Edge Function log delivery | 5x faster; Netlify, September 29, 2026. |
| Cold invocations | About 1.2% of invocations, with about 9 ms average image-fetch time when a request arrives in a region where no compute node has seen the function before; Netlify, September 29, 2026. |
| Warm full path | About 6 ms added by the full path on a warm instance; Netlify, September 29, 2026. |
| Daily execution volume | About one billion Edge Functions run each day, according to Netlify on September 29, 2026; this is vendor-stated operational context, not an independent volume audit. |
Netlify characterizes the warm path this way: “That’s the whole path, and on a warm instance it adds about 6ms.” This is the announcement’s figure, not an independent benchmark. The sources cited here do not provide an independent replication of Netlify’s performance, availability, or volume claims, so treat them as vendor-reported metrics rather than universal guarantees.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What changes for a site owner?
Netlify says the new architecture is serving production traffic at the same pricing, with no customer migration step or project changes required. The customer-facing handler and route configuration remain the same. That means the infrastructure change does not itself require rewriting an Edge Function, though whether a function runs still depends on its route matching the request.
Netlify’s runtime remains Deno-based, and Edge Functions are written in JavaScript or TypeScript. Functions are version-controlled, built, and deployed with the rest of the site. Netlify documents uses such as localization, authentication, personalization, redirects, and other request-time behavior; responses can also be cached when configured. See the Netlify Edge Functions overview.
How should you scope and troubleshoot an Edge Function?
Netlify’s implementation guide, dated August 25, 2026, recommends keeping routes narrow and checking the route and framework behavior before investigating the underlying infrastructure. Its current documented limits are 50 ms of CPU per request (excluding resource wait), 512 MB of memory, and 20 MB of compressed code. Netlify’s announcement says these limits came from the isolate-based execution model and may be revisited; it does not say they have already changed. See the implementation guide for current guidance.
- Confirm the route matches. Define a route explicitly. Netlify warns that a function without a route may deploy without an error or warning and never execute.
- Avoid an unnecessarily broad catch-all. A route such as
/*can match static assets, adding latency and an invocation for each matching request. - Check for framework-generated middleware. An adapter may already provide the behavior; adding a duplicate function can do redundant work.
- Use
context.next()only when downstream content is needed. It continues to the downstream asset or serverless function on the same internal path, and Netlify cautions that continuing adds latency. - Configure both parts of caching. Netlify says caching requires manual cache mode and appropriate response headers; either one alone is insufficient.
When is an Edge Function the wrong place for the work?
Edge Functions are aimed at short request/response work near the request path. For longer-running or database-heavy tasks, background or scheduled work, heavy Node dependencies, or memory needs above the documented edge limit, Netlify’s guide points developers to Netlify Functions instead. The decision is not simply about which option is faster: database or service topology, runtime and package compatibility, execution and memory limits, and whether a function must wait for or modify a downstream response all affect the fit.
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