Full text search, please :)
Inverted indexes are almost always eventually consistent, and easy to integrate in a distributed context.
- Store documents into R2 or Durable Objects or KV or (Cloudflare future storage).
- Create inverted index files (similar to Lucene)
- Cache the inverted index files at the edge. Cloudflare’s bread and butter.
- Run query execution nodes at the edge. Deal with the occasional cache miss by proxying to a different region.
- Its impossible to deal with relevance or ranking for that many different use cases. Let the clients control every aspect of relevancy and ranking, e.g. Similar to the flexibility of ElasticSearch.
R2 will be amazing for hosting computer vision datasets and models.
It is for a cloud hoster. But ML does not take advantage of cloudflare's competitive edge ( their SDN ).
In the same way, i don't think docker containers are an interesting/good fit ( i could be wrong on this though)
Edit: i was wrong...
Which is absolutely where CF are headed, as evidenced by R2.
Don’t forget that S3 was the first AWS product. It’s fitting that it’s also CF’s first real foray into cloud-land.
I thought that ai wasn't interesting on the edge.
Already really impressed with Cloudflare Sites and planning to adopt Images soon.
You guys deliver at a dizzying pace, it's truly incredible.