CDNs have served static assets for decades — images, CSS, JavaScript files cached at edge locations around the world. But the edge is no longer just a cache layer. Modern edge platforms run application code, execute database queries, and render entire pages at locations within 50 milliseconds of every user on the planet. Here is how edge delivery networks work today and how to use them effectively.
From Static Caching to Dynamic Compute
Traditional CDNs cache content at Points of Presence (PoPs) distributed globally. When a user in Tokyo requests a file, the nearest PoP serves it instead of making a round trip to your origin server in Virginia. This works perfectly for assets that rarely change. But most modern web applications generate content dynamically — personalized pages, authenticated API responses, search results.
Edge compute platforms like Cloudflare Workers, Vercel Edge Functions, and Deno Deploy changed this by running application logic at the edge. Instead of caching a static response, the edge node executes your code and generates the response on the spot. The user gets a response from a server 20 miles away rather than 5,000 miles away, and the content is fresh and personalized.
Edge-Compatible Database Access
The biggest challenge with edge compute is data. Your code runs at 200+ global locations, but your database is in one region. A function running at the edge in São Paulo still needs to query a PostgreSQL database in US-East-1, which adds 150ms of network latency and defeats the purpose of edge deployment.
Several approaches have emerged to solve this. Read replicas can be deployed in multiple regions, so edge functions query the nearest copy. Distributed databases like CockroachDB and PlanetScale automatically replicate data globally. For read-heavy workloads, edge key-value stores like Cloudflare KV and Vercel Edge Config provide single-digit millisecond reads at every edge location.
The pattern that works best for most applications is a split approach: read from edge-local data stores and write to a centralized database. The edge function checks a local cache or read replica first. If the data is fresh, it responds immediately. If not, it falls back to the origin database. Writes always go to the primary database, and replication propagates changes to edge stores within seconds.
Optimizing Cache Hit Rates
Even with dynamic content, caching remains your most powerful tool. The key is understanding which parts of a page are shared and which are personalized. A product page's description, images, and reviews are the same for everyone — cache them aggressively. The user's cart count, login state, and recommended products are personal — render them client-side or through a separate API call.
Stale-while-revalidate cache headers are essential for edge delivery. They tell the edge to serve cached content immediately while fetching a fresh copy in the background. Users always get a fast response, and the content updates within seconds. This technique alone can increase cache hit rates from 40% to over 90% for most web applications.
Cache keys should be as specific as necessary and no more. Including unnecessary query parameters or headers in the cache key creates duplicate cache entries for identical content. Use Vary headers carefully and strip tracking parameters before they reach your cache layer.
Monitoring Edge Performance
Edge monitoring requires thinking globally. A performance regression in Asia-Pacific might not show up in your aggregate metrics if most of your traffic is in North America. Break your monitoring dashboards down by edge location, not just by endpoint. Track cache hit ratios, origin fetch latency, and edge compute time separately.
Real User Monitoring (RUM) data is more valuable than synthetic tests for edge optimization because it shows actual user experience across all the geographic locations your customers are in. Correlate RUM data with edge metrics to identify which locations need better caching strategies, additional read replicas, or code optimization. The goal is consistent sub-100ms Time to First Byte everywhere in the world.