Well it deserves a blog post to describe how things work a bit, but roughly the things that help on the load are: - fragment caching with redis/rails 3 (with s

Well it deserves a blog post to describe how things work a bit, but roughly the things that help on the load are: - fragment caching with redis/rails 3 (with some warmup script) - the full search is handled by solr - nginx and passenger are quite fast I still need to make some work to compress the js/css together. The images themselves are served by Amazon. On the size of the list: well I really have a bias toward "data aggregation". My two previous side-projects (http://www.learnivore.com http://www.learnivore.com and http://www.toutpourmonipad.com/ http://www.toutpourmonipad.com/) were already "ETL"-based. I have another project where I will manually curate the list, though... I think both approaches (data-driven or manually curated) have their pros and cons... Glad you like it in all cases!