YouTube Scalability

How does YouTube deal with the huge amounts of data that it must manage?

I found it interesting in light of my own comments on YouTube’s 45 TB a while back.

Here are my notes from his talk, a mix of what he said and my commentary:

In the summer of 2006, they grew from 30 million pages per day to 100 million pages per day, in a 4 month period. (Wow! In most organizations, it takes nearly 4 months to pick out, order, install, and set up a few servers.)

YouTube uses Apache for FastCGI serving. (I wonder if things would have been easier for them had they chosen nginx, which is apparently wonderful for FastCGI and less problematic than Lighttpd)

YouTube is coded mostly in Python. Why? “Development speed critical”.

They use psyco, Python -> C compiler, and also C extensions, for performance critical work.

They use Lighttpd for serving the video itself, for a big improvement over Apache.

Each video hosted by a “mini cluster”, which is a set of machine with the same content. This is a simple way to provide headroom (slack), so that a machine can be taken down for maintenance (or can fail) without affecting users. It also provides a form of backup.

The most popular videos are on a CDN (Content Distribution Network) – they use external CDNs and well as Google’s CDN. Requests to their own machines are therefore tail-heavy (in the “Long Tail” sense), because the head codes to the CDN instead.

Via Sam Ruby.

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