5x faster Edge Functions: V8 isolates to Firecracker MicroVMs
All of it runs on a full JavaScript runtime that scales with our customers’ traffic. This poses a significant technical challenge, as we strive to make the latency as low as possible. To run tens, sometimes hundreds of thousands, of edge functions per second, we need to process each request, route it correctly, allocate compute capacity, and boot both our platform code and the customer’s code.
- ▪All of it runs on a full JavaScript runtime that scales with our customers’ traffic.
- ▪This poses a significant technical challenge, as we strive to make the latency as low as possible.
- ▪To run tens, sometimes hundreds of thousands, of edge functions per second, we need to process each request, route it correctly, allocate compute capacity, and boot both our platform code and the customer’s code.
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Story provenance
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Record
| Original publisher | Netlify |
| Canonical URL | https://www.netlify.com/blog/edge-functions-firecracker-microvms/ |
| Publication time | Wed, 30 Sep 2026 18:17:45 +0000 |
| Retrieval time | 2026-09-30T18:37:06.492Z |
| Last seen | 2026-09-30T18:37:22.174Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | sahnjw-D3kQQ · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
About a billion Edge Functions run on Netlify every day — Sunweb personalizing pages, Loto-Québec routing traffic on a cookie check, and hundreds of thousands of other sites doing everything from personalization to routing to auth. All of it runs on a full JavaScript runtime that scales with our customers’ traffic. This poses a significant technical challenge, as we strive to make the latency as low as possible. To run tens, sometimes hundreds of thousands, of edge functions per second, we need to process each request, route it correctly, allocate compute capacity, and boot both our platform code and the customer’s code. All of that has to happen within milliseconds.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Netlify.
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