Explain Edge Functions vs Cloud Functions.
Edge functions run code close to the user on globally distributed edge nodes for ultra-low latency, while Cloud functions execute in regional serverless backends designed for heavier workloads and deeper integrations.
When to Use
-
Edge Functions:
- Authentication/token checks
- Geo-based personalization
- A/B testing and feature flags
- Bot filtering, request shaping
- Content caching and revalidation
-
Cloud Functions:
- Payment processing
- Database transactions
- File/image/video transformations
- ETL pipelines, cron jobs
- Long-running API workflows
Example
A user requests a homepage. An edge function adds a geo-specific banner instantly, while a cloud function later generates and stores the invoice.
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Why Is It Important
Understanding the distinction helps you optimize for latency, cost, scalability, and compliance, ensuring you design systems that balance user experience with backend power.
Interview Tips
- Clarify latency vs. compute requirements.
- Mention data locality and vendor limits.
- Suggest hybrid design: edge for fast response, cloud for heavy lifting.
- Back your answer with SLAs or cost reasoning.
Trade-offs
- Edge: Speed, global reach, scale-to-zero → limited runtime, compute, and storage.
- Cloud: More compute, libraries, integrations → higher latency, regional coupling.
Pitfalls
- Assuming edge always beats cached cloud responses.
- Writing to a single-region DB from multiple edges.
- Running CPU-heavy workloads at the edge.
- Ignoring observability and rollout control.
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