Why Edge Computing

Edge computing executes code at servers geographically close to users rather than in centralized data centers. The result is lower latency — a request that would take 200ms to a US data center from Southeast Asia takes 20ms to a local edge node. At Nexis Limited, we use edge computing for latency-sensitive operations and content personalization across our global user base.

Edge Computing Platforms

Cloudflare Workers

V8 isolate-based compute running across 300+ edge locations. Sub-millisecond cold starts. Supports JavaScript, TypeScript, Rust (via WASM), and Python. Paired with Workers KV (key-value storage), Durable Objects (stateful compute), D1 (edge SQLite), and R2 (object storage). Our preferred platform for edge workloads.

Vercel Edge Functions

Edge functions integrated into the Vercel deployment platform. Run Next.js middleware, API routes, and server components at the edge. Seamless integration with the Next.js framework — ideal for Next.js applications that need edge rendering or API processing.

AWS Lambda@Edge / CloudFront Functions

Lambda@Edge runs Node.js or Python functions at CloudFront edge locations. CloudFront Functions run lightweight JavaScript at the edge for request/response manipulation. Best for AWS-centric architectures.

Deno Deploy

Globally distributed edge runtime based on Deno. Supports TypeScript natively. Simple deployment model with instant global distribution.

Use Cases

Content Personalization

Customize content at the edge based on user location, device, language, or session data without round-tripping to the origin server. Serve region-specific pricing, localized content, or device-optimized responses from the nearest edge location.

Authentication and Authorization

Validate JWT tokens, check API keys, and enforce access control at the edge. Unauthorized requests are rejected at the edge without consuming origin server resources. This provides both security and performance benefits.

A/B Testing

Route users to different content variants at the edge based on cookies, headers, or random assignment. The edge function selects the variant and serves the appropriate content, avoiding the latency of origin-based A/B testing.

URL Rewriting and Redirects

Handle URL redirects, rewrites, and vanity URLs at the edge. Migrating hundreds of URLs during a website redesign? Handle redirects at the edge with near-zero latency instead of routing through your application server.

Rate Limiting and Bot Protection

Implement rate limiting at the edge to protect your origin from abuse. Detect and block bot traffic before it reaches your infrastructure. Edge-based limiting handles high-volume attacks without scaling your application servers.

Constraints and Limitations

  • Execution time limits: Edge functions typically have short execution time limits (10-30 seconds). Long-running tasks must be offloaded to traditional servers or background workers.
  • Limited runtime APIs: Edge runtimes do not support all Node.js APIs. File system access, native modules, and some Node.js built-ins are unavailable.
  • Cold starts: While minimal for V8-isolate platforms (Cloudflare Workers, Deno Deploy), container-based edge platforms (Lambda@Edge) can have noticeable cold starts.
  • Data locality: Edge functions run close to users but far from your database. Edge-to-origin database queries negate latency benefits. Use edge-compatible databases (D1, Turso) or cache data at the edge.

Architecture Patterns

  • Edge + origin: Handle lightweight, latency-sensitive tasks at the edge. Proxy complex requests to origin servers. Most practical starting point.
  • Full edge: Run the entire application at the edge using edge databases and storage. Possible for simpler applications but challenging for complex data-intensive workloads.
  • Edge cache + origin compute: Cache rendered pages at the edge with stale-while-revalidate. Origin handles rendering and data processing. Cache provides fast responses while origin handles complexity.

Conclusion

Edge computing is not a replacement for traditional servers — it is a complementary layer that handles latency-sensitive, lightweight tasks close to users. Start with specific use cases (auth, redirects, personalization) and expand edge usage as your team gains experience. The latency improvements for global users are significant.

Optimizing global performance? Our team implements edge computing strategies for worldwide deployments.