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Rate Limiting at the Edge with KV Storage

Rate Limiting at the Edge with KV Storage

By Gcore

August 27, 2026

2 min read

Orange outline illustration of a data security workflow with user access, verification, and storage.

Security at the edge means threats are stopped before they reach your infrastructure. By implementing security logic in FastEdge workers, you can validate, filter, and block requests at the closest edge location to the user — providing the fastest possible response for legitimate traffic while protecting your origin servers.

This post looks at Rate Limiting at the Edge with KV Storage — one of several security patterns available in the FastEdge Rust SDK.

What It Does

Implement per-client rate limiting using edge KV storage. Protect your origin from abuse without centralized rate limiting infrastructure.

Processing security logic at the edge provides several benefits: reduced latency for end users, reduced load on origin servers, and a smaller attack surface. Malicious traffic is absorbed by the edge network before it reaches your infrastructure.

Implementation

Here is how you implement this pattern using the FastEdge Rust SDK:

use fastedge::{ body::Body, http::{Request, Response, StatusCode, Error}, }; #[fastedge::http] fn main(req: Request<Body>) -> Result<Response<Body>, Error> { // Extract security-relevant headers let country = req.headers() .get("geoip-country-code") .and_then(|v| v.to_str().ok()) .unwrap_or("unknown"); let user_agent = req.headers() .get("user-agent") .and_then(|v| v.to_str().ok()) .unwrap_or("unknown"); // Block known bad actors at the edge if blocked_country(country) { return Response::builder() .status(StatusCode::FORBIDDEN) .header("content-type", "text/plain") .body(Body::from("Access denied")); } if is_malicious_agent(user_agent) { return Response::builder() .status(StatusCode::FORBIDDEN) .body(Body::from("Blocked")); } // Forward to origin Response::builder() .status(StatusCode::OK) .body(Body::from("Hello, verified user!")) } fn blocked_country(country: &str) -> bool { matches!(country, "XX" | "YY" | "ZZ") } fn is_malicious_agent(agent: &str) -> bool { agent.contains("curl") || agent.contains("python-requests") }

Deploy

For the complete implementation with all features, including rate limiting, IP allowlists, and request transformation, clone the SDK repository and check the example:

git clone https://github.com/G-Core/FastEdge-sdk-rust.git cd FastEdge-sdk-rust/examples/cdn/rate_limiting cargo build --release

Important: Edge security complements — but does not replace — server-side validation. Always enforce critical authentication and authorization at the origin. Think of edge security as your first line of defense, not your only one.

Performance Impact

All security checks at the edge run in WebAssembly with sub-millisecond overhead. Header inspection, GeoIP lookups, and pattern matching add virtually no latency — typically 10–50 µs per check. This means you can layer multiple security patterns without worrying about performance degradation.

Markdown file content converting to HTML output with gears representing the process.

Rendering Markdown to HTML at the Edge

Running compute at the edge means you can transform and optimize content before it reaches your users — with sub-millisecond cold starts and no additional infrastructure. Every FastEdge worker runs on WebAssembly, providing sandboxed, predi

Data processing flow connecting two system windows with a central document icon.

Reading and Modifying HTTP Bodies at the Edge (Part 2)

One of the most powerful features of edge computing is the ability to inspect and route traffic before it ever reaches your origin server. FastEdge gives you full programmatic control over request routing at every edge location worldwide.In

Secure data processing diagram with input form, protective shield, and validated output display.

Parse and Validate Form Data at the Edge

Visualizing image file size reduction from 2.4MB to 320KB through an optimization process.

On-the-fly Image Optimization at the Edge

Digital panel with lightning bolt icon, emitting orange data streams or energy.

Manipulating Headers at the Edge

Conceptual diagram illustrating an Edge Worker connecting databases, code, cloud, and analytics.

Making Outbound Requests from the Edge

FastEdge workers aren't limited to just responding to incoming requests — they can also make outbound network requests to external services. This opens up a world of possibilities: aggregating data from multiple APIs, proxying requests to u

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