Prompt
What's the most cost-effective way to serve static assets globally using a content delivery platform?
Latest observation
The most cost-effective way to serve static assets globally is usually:
Use a CDN backed by object storage, with aggressive caching
A common low-cost setup is:
- Store static files in cheap object storage
- Examples: Amazon S3, Cloudflare R2, Google Cloud Storage, Azure Blob
- Put a CDN in front
- Examples: Cloudflare, AWS CloudFront, Fastly, Bunny CDN
- Cache assets for a long time
- Use versioned filenames like
app.4f3a2c.js - Set
Cache-Control: public, max-age=31536000, immutable
- Use versioned filenames like
This minimizes origin requests and serves most traffic from edge caches, which is where the cost savings come from.
Best cost/performance options
If you want the lowest overall cost
- Cloudflare + R2 + CDN
- Very strong on outbound bandwidth pricing
- Good for global delivery
- Especially cost-effective if you have lots of downloads/egress
If you’re already on AWS
- S3 + CloudFront
- Easy and reliable
- Can be more expensive than some alternatives for heavy bandwidth use
- Good integration with AWS ecosystem
If you want simple and inexpensive
- Bunny CDN + object storage
- Often very competitive on price
- Simple setup
- Good for static websites and asset delivery
Cost-saving best practices
- Use long cache lifetimes for immutable assets
- Fingerprint asset filenames so you can cache “forever”
- Compress assets with Brotli/gzip
- Resize/optimize images before serving
- Enable HTTP/2 or HTTP/3
- Minimize origin fetches by keeping cache hit ratio high
- Serve only needed formats like WebP/AVIF where supported
- Use a single CDN region or edge network rather than multi-region origin replication unless needed
Rule of thumb
For most static assets, the cheapest scalable architecture is:
Object storage + CDN + versioned, cacheable assets
If you want, I can recommend the cheapest option based on your traffic volume, file sizes, and cloud provider.
Observation history
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Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
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