Content delivery network costs.

CDN (Content Delivery Network) pricing has three components: data transfer out to users, HTTP request count, and storage of cached files. Data transfer dominates for video and image-heavy sites; request count dominates for API-heavy sites. Typical pricing: 0.05-0.12/GB transfer, 0.50-2 per million requests, 0.02-0.05/GB storage monthly.

5,000 GB transfer × 0.08 = 400. 20M requests × 1 per million = 20. 500 GB storage × 0.023 = 11.50. Total ~432/month. Small ecommerce sites typically run 100-500 monthly CDN; mid-market streaming or news sites 2k-20k; major platforms 100k+. AWS CloudFront, Cloudflare, Fastly are the main providers with similar pricing.

Free tiers (Cloudflare free, AWS free tier) cover small sites entirely. Past small-scale, transfer volume scales costs fastest. Video streaming at 1080p burns 3-5 GB per user per hour; even modest streaming volumes produce meaningful CDN bills. Compression (Brotli, WebP images) and smart caching cut bills 30-50% for most sites.

Run it with sensible defaults

Using monthly gb transferred of 5,000, cost per gb of 0.08, monthly requests of 20, cost per million requests of 1, the calculation works out to 431.50. Nudge the inputs toward your own situation and the output recalculates instantly. The defaults are meant as a starting point, not a recommendation.

The levers in this calculation

The inputs — Monthly GB Transferred, Cost per GB (£), Monthly Requests (millions), Cost per Million Requests (£), and Storage (GB) — do not pull with equal force. Frequency and unit price pull the total in different directions. The biggest surprise for most people is how small recurring amounts compound into large annual figures — that's where this calculation earns its keep.

How the math works

Total = (transfer × rate) + (requests × rate per million) + (storage × rate). All component-wise summed monthly. The working is transparent — you can verify every step yourself in the formula section below. No black box, no opaque "proprietary model".

What to do with a low result

A disappointing result is information, not a judgement. Pick the single input that dragged the figure down most and focus the next quarter on that one factor. Breadth-first improvement rarely works; depth-first on the worst input usually does.

What this doesn't capture

The score is a composite of the inputs you provide. Life context — job security, family obligations, health, housing — doesn't appear in the math but shapes the real picture. Use the number as a prompt, not a verdict.