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Edge Computing: Bringing Serverless Closer to Users

Explore edge computing and serverless functions. Learn to deploy code at the edge for ultra-low latency and global performance.

B
Bootspring Team
Engineering
February 26, 2026
7 min read

Edge computing moves computation closer to end users, dramatically reducing latency. This guide explores edge platforms, use cases, and implementation patterns.

Understanding Edge Computing

Traditional cloud functions run in specific regions. Edge functions run globally, close to your users:

Traditional: User (Tokyo) ──────────────────> Server (US-East) ~200ms latency Edge: User (Tokyo) ──> Edge Node (Tokyo) ~20ms latency

Edge Platforms Compared

Cloudflare Workers

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Vercel Edge Functions

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Deno Deploy

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Common Edge Use Cases

1. Geolocation-Based Routing

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2. A/B Testing at the Edge

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3. Authentication at the Edge

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4. Image Optimization

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5. Rate Limiting

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Edge Data Storage

KV Storage (Key-Value)

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Durable Objects (Stateful)

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D1 (SQLite at the Edge)

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Edge Limitations

Understanding constraints is crucial:

ConstraintCloudflareVercel EdgeDeno Deploy
CPU time10-50ms25s50ms
Memory128MB128MB512MB
Bundle size1MB2MBNo limit
Subrequests50251000

Working Within Limits

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Deployment Workflow

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Monitoring Edge Functions

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Conclusion

Edge computing enables ultra-low latency for global users. Start with simple use cases like geolocation or caching, then expand to more complex patterns as you understand the constraints. The key is knowing when edge makes sense versus traditional serverless.

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