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Case Study // CloudFront

CLOUDFRONT
AT SCALE.

CloudFront is the edge layer that makes 1M RPS practical by offloading origin traffic via caching and absorbing global spikes.

Client Overview

Operational Challenges

Engineering teams needed predictable performance, lower risk, and cleaner deployment confidence under real traffic patterns.

polesim analyze --service cloudfront --window 30d
> Risk pattern identified in peak load windows
> Recommended simulation profile generated
Key Config

Enabled

true
Performance Signal

Price Class

PriceClass_100
Recommended Workflows

Implementation Focus

  • Invalidate Cache - Create an invalidation (use sparingly)
  • Toggle Maintenance - Flip to a maintenance response at the edge
  • Simulate Cache Hit Ratio - Estimate origin offload via caching
High-Impact Notes

What To Optimize First

  • Global edge distribution (low latency, global scale)
  • Can sustain very high request rates; origin becomes the bottleneck
  • Built-in TLS, HTTP/2+HTTP/3, compression, geo controls
  • Cache effectiveness depends on cache keys (headers/cookies/query strings)
Next Step

USE PINPOLE.CLOUD TO IMPROVE THIS ARCHITECTURE.

Simulate before deploying, reduce failure risk, and turn configuration insights into reliable implementation plans.

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