I think you're on to something when you contrast the 2 problem domains. Number of requests is a very naive way to look at load factors.
At the startup I work, we've got 25-30 Million users, many stats similar to Tumblr, and we're running it on about 250 Ec2 instances of varying size. I think if Tumblr's numbers are high at all -- due to rapid iterations and no time to focus on deep optimizations -- it's maybe 10-15% high, not 90%.
I'm saying this because I've seen periods where our usage numbers are somewhat flat, even falling, but our hardware demands rise as we provide more features. When there's just one or two primary ways to use a service (eg "I post status updates and comment on my friends' status updates") it can be quite easy to optimize. But add features. Photos. Chat. An in-house ad serving platform. I18N. Etc. You have different types of interactions with different acceptable service levels and varying storage requirements.
At the startup I work, we've got 25-30 Million users, many stats similar to Tumblr, and we're running it on about 250 Ec2 instances of varying size. I think if Tumblr's numbers are high at all -- due to rapid iterations and no time to focus on deep optimizations -- it's maybe 10-15% high, not 90%.
I'm saying this because I've seen periods where our usage numbers are somewhat flat, even falling, but our hardware demands rise as we provide more features. When there's just one or two primary ways to use a service (eg "I post status updates and comment on my friends' status updates") it can be quite easy to optimize. But add features. Photos. Chat. An in-house ad serving platform. I18N. Etc. You have different types of interactions with different acceptable service levels and varying storage requirements.