Edge Computing Architecture Template

Edge computing adds complexity. If your users are concentrated in one geography (e.g., a B2B SaaS serving US enterprise customers), a single-region deployment with a CDN for static assets may achieve adequate latency without edge compute. Similarly, if your workload is write-heavy and requires strong consistency, the synchronization overhead of edge computing may negate the latency benefits. Evaluate each use case individually using the evaluation matrix above.

Edge nodes typically cannot connect directly to a centralized database with acceptable latency. Instead, use one of three patterns: (1) Cache read-only data at the edge with TTL-based invalidation. (2) Use an edge-native database (CockroachDB, PlanetScale, Turso) that replicates globally. (3) Queue writes at the edge and batch-send to the central database asynchronously. The right pattern depends on your consistency requirements.

[Multi-region deployment](/templates) runs your full application stack in 2-5 cloud regions for availability and reduced latency. Edge computing runs lightweight processing at dozens or hundreds of locations, typically at CDN points of presence or colo facilities. Multi-region is about redundancy and reducing latency by 50-100ms. Edge computing is about reducing latency to single-digit milliseconds and processing data where it originates.

Use the edge platform's built-in analytics (Cloudflare Analytics, CloudFront real-time metrics) for aggregate metrics. Add custom telemetry in your edge functions (execution time, cache hit/miss, origin fetch latency) and ship it to your central observability platform (Datadog, Grafana Cloud). Set up synthetic monitoring from 10+ global locations to measure end-to-end latency from the user's perspective, not just edge function execution time. ---