What is the difference between edge and cloud computing?

Cloud computing centralises processing in large data centres. Edge computing distributes processing to locations closer to users or data sources. They are complementary: edge handles time-sensitive, high-frequency processing, while cloud handles complex analytics, storage, and compute-intensive tasks. Most modern architectures use both.

Do I need edge computing?

Consider edge computing if: your users need very low latency (under 50ms), you process large volumes of IoT data, you need to reduce cloud bandwidth costs, or you want to process data locally for privacy reasons. For standard web applications, a good CDN may provide sufficient edge capability without the complexity of full edge computing.

How does edge computing work for websites?

For websites, edge computing typically means running server-side logic at CDN edge locations using services like Cloudflare Workers or Vercel Edge Functions. This enables: personalisation without origin server round-trips, A/B testing at the edge, authentication and authorisation closer to users, and API routing with reduced latency.

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Edge Computing

Also known as:edge processingdistributed computingfog computing

Processing data closer to the source of data generation rather than in a centralised data centre, reducing latency and bandwidth usage for time-sensitive applications.

In-Depth Explanation

Edge computing processes data at or near the physical location where it is generated, rather than sending everything to a centralised cloud data centre. By bringing computation closer to data sources, it reduces latency, conserves bandwidth, and enables real-time processing.

Edge computing architecture:

Edge devices: IoT sensors, cameras, industrial controllers
Edge servers: Local processing nodes near data sources
Edge cloud: CDN-like distributed computing (Cloudflare Workers, AWS Lambda@Edge)
Regional cloud: Cloud data centres in nearby geographic regions
Central cloud: Traditional centralised cloud processing

Edge computing use cases:

IoT data processing: Filtering and analysing sensor data locally
Content delivery: Serving web content from nearby edge nodes
Real-time analytics: Processing data streams with minimal delay
Video processing: Surveillance and quality control at the source
Retail: In-store analytics, point-of-sale, inventory scanning
Manufacturing: Machine monitoring, quality control, predictive maintenance

Edge computing for web applications:

Cloudflare Workers: Run JavaScript at the edge globally
AWS Lambda@Edge: Run functions at CloudFront edge locations
Vercel Edge Functions: Server-side logic at the edge
Deno Deploy: JavaScript/TypeScript at the edge
Fastly Compute@Edge: High-performance edge computing

Benefits:

Low latency: Sub-millisecond processing for nearby users
Bandwidth reduction: Only relevant data sent to central cloud
Reliability: Local processing continues during internet disruptions
Privacy: Sensitive data can be processed locally without leaving the premises
Scalability: Distributed processing across many edge locations

Business Context

Edge computing enables real-time application experiences that centralised cloud cannot provide, with response times under 50ms compared to 100-300ms for traditional cloud architecture.

How Clever Ops Uses This

Clever Ops implements edge computing solutions for Australian businesses, from CDN-based edge functions for web applications to IoT edge processing. We design architectures that process data locally in Australia while synchronising with central cloud systems, ensuring fast performance for Australian users and reduced data transfer costs.

Example Use Case

"An Australian media website deploys Cloudflare Workers to handle personalisation, A/B testing, and authentication at the edge, reducing page load time by 40% for Australian users and eliminating the need for requests to traverse to a US-based origin server."