How CDNs Work
A CDN operates by maintaining a network of Points of Presence, abbreviated PoPs, distributed across geographic regions. When a user requests a resource such as a JavaScript bundle, CSS file, image, or API response, the request is routed to the nearest PoP rather than to your origin server. If the PoP has a cached copy of the response that is still within its Time to Live, it returns the cached response immediately without contacting the origin. If the cache is empty or stale, the PoP fetches the resource from your origin, stores it in cache, and returns it to the user. Subsequent requests for the same resource from the same geographic region are served entirely from cache until the TTL expires or the cache is explicitly invalidated. The latency reduction from CDN caching is most significant for users geographically distant from your origin server. A UK-based user accessing a product whose origin server is in us-east-1 might experience 150ms of network latency without a CDN and under 20ms with CDN edge nodes in London or Frankfurt. For AI products where LLM inference latency is already a user experience consideration, reducing all other latency sources through CDN caching makes a meaningful difference to overall perceived responsiveness.
What to Cache for AI Products
AI product architecture creates specific caching decisions that are different from traditional SaaS products. Static assets, including JavaScript bundles, CSS files, fonts, and images, should always be cached at the CDN with long TTLs and cache-busted by content hash on deployment, which is the default behaviour on Vercel and most modern deployment platforms. The more interesting question is whether API responses can be cached. For AI product APIs, caching LLM responses is worth serious consideration. If your product generates a weekly market report, a product description, or a fixed knowledge base answer, the LLM response for a given input is deterministic enough to cache. Cache the response keyed on the input prompt hash, set a TTL appropriate to how frequently the answer might change, and serve cached responses for repeated identical queries. This can dramatically reduce LLM API costs and response latency for common queries. The cases where you should not cache are real-time personalised generation, conversation history that varies by user session, and any response that must reflect the most current data. Semantic caching, where you cache responses for queries that are semantically similar rather than identical, is an emerging pattern supported by libraries such as GPTCache and built into some LLM gateway products.
Modern CDNs: Beyond Static Files
The leading CDN providers have expanded significantly beyond static asset caching. Cloudflare, in particular, has evolved into a full application delivery platform. Cloudflare Workers allow arbitrary JavaScript to run at the edge, enabling personalisation, authentication, A/B testing, and request transformation without an origin server round-trip. Cloudflare's WAF provides application-level attack protection. Cloudflare R2 provides S3-compatible object storage with no egress fees when served through the CDN. AWS CloudFront integrates natively with all AWS services including Lambda at the Edge for serverless functions running at CDN PoPs, and provides real-time analytics through CloudFront access logs. Vercel's Edge Network is a CDN purpose-built for Next.js that caches static assets automatically and supports edge functions running in Next.js middleware, enabling per-request logic at the CDN layer. For AI products on Vercel, the Vercel Edge Network provides CDN functionality with no separate configuration, caching static assets from the first deployment.
CDN Configuration for UK and EU Markets
For AI products serving UK and EU customers, CDN configuration has compliance dimensions worth considering. GDPR requires that personal data transferred outside the UK and EEA has appropriate safeguards in place. CDN access logs containing IP addresses and user agents are personal data under GDPR. If your CDN PoPs are operated by a US provider, ensure you have a DPA with the CDN provider that covers EU personal data in access logs, and that Standard Contractual Clauses or equivalent UK safeguards are in place for the transatlantic log transfer. Cloudflare, AWS CloudFront, and Fastly all provide GDPR-compliant DPAs. For products with strict data residency requirements, some enterprise CDN configurations allow you to restrict which PoP locations serve your traffic, keeping user request data within the EEA. Geo-blocking configuration at the CDN layer can also enforce regulatory restrictions on which geographic markets can access your AI product, which may be relevant for EU AI Act compliance if your product has geographic deployment restrictions.
CDN Performance for AI Product Workflows
Beyond static asset delivery, CDNs contribute to AI product performance in several workflow-specific ways. Document uploads that users submit for AI processing can be accelerated by routing the upload through CDN edge nodes that handle connection establishment close to the user and transfer to your origin over an optimised backbone connection. CDN caching of API responses for common AI queries reduces both latency and LLM API cost. CDN-level rate limiting protects your LLM API budget by throttling abusive request patterns before they reach your application layer, which is cheaper than handling rate limiting at the application level. For AI products that serve generated images, CDN caching of image generation outputs, with TTL set to match the expected reuse window, prevents redundant image generation for identical prompts. The performance gains from these CDN patterns compound with the latency already introduced by LLM inference, making CDN configuration a worthwhile performance investment for any AI product with real user traffic.
Choosing a CDN Provider
Cloudflare, AWS CloudFront, Fastly, and Vercel's built-in Edge Network are the providers most relevant to UK AI startups. Cloudflare is the default recommendation for teams that want a single platform handling CDN, DDoS protection, WAF, DNS, edge functions, and R2 storage with straightforward pricing and a generous free tier. AWS CloudFront is the natural choice for teams already deeply invested in AWS, where native integration with S3, Lambda, and CloudWatch reduces configuration complexity. Fastly offers superior cache control granularity and very fast cache purging, making it the choice for products with frequently changing content where stale cache is a real problem. Vercel's Edge Network requires no separate CDN configuration for teams on Vercel and handles all static asset caching and edge middleware automatically. Most AI product teams on Vercel have no need to add a separate CDN on top of the Vercel Edge Network. Teams with custom infrastructure on AWS or GCP should evaluate Cloudflare or CloudFront based on their existing cloud provider relationships and the specific performance and compliance requirements of their product.