We’re quite addicted to data pr0n here at Flickr. We’ve got graphs for pretty much everything, and add graphs all of the time.
One of the most interesting parts of running a large website is watching the effects of unrelated events affecting user traffic in aggregate. Web traffic is something that companies typically keep very secret, and often the only time engineers can talk about it is late at night, at a bar, and very much off the record.
There are many good reasons for keeping this kind of information confidential, particularly for publicly traded companies with complicated disclosure requirements. There are also downsides, the biggest being that is difficult for peers to learn from each other and compare notes.
John Allspaw recently created a WebOps Visualizations group on Flickr for sharing these kinds of graphs with the confidential information removed. Here’s an example of a traffic drop seen both by Flickr & by Last.FM that coincided with President Obama’s inauguration.
Similar traffic drop on Last.FM seen on the right
Google saw a similar drop as well
Was it because everybody went to Twitter?
Besides being an interesting story, sharing these kinds of graphs help people build better monitoring tools and processes. As just one example: How should the WebOps team respond to this dip in traffic? Is it an outage? The inaguration was a very well known event and so it’s easy to explain the drop in traffic… what happens when a similar drop in traffic occurs? Should the WebOps team be looking at CNN (or trends in twitter) along with everything else?
How do you tell when that unexpected 10% drop in traffic is really just people with something more important to do than browse your site?
(Note: Updated since original posting to add Google & Twitter graphs and annotations, and to switch the Last.FM graphic with an annotated one after I got permission.)