tldr; Do we have data on the number of compressed vs. uncompressed requests we serve? Hey all, I'm investigating a fundraising issue where it appears that banners that should be about the same size compressed, but which are differently sized upon decompression, show markedly different conversion rates (the only thing that's different about them is the name of the banner which affects content length). One of the angles I'm investigating is if perhaps we're serving a significant number of banners uncompressed; which would affect the amount of time it takes to appear on the site. If we have this data already, I can compare it to data that I'm going to take from the banner stream [1]. Alternate things I'm considering is if it takes the caching layer longer to retrieve serve certain banner content and/or cache keys. -- The Data -- For the truly curious; the two tests I've run so far that have led me down this path are: have two banners with the same content (cloned) but with different names. As names get substituted into the banners multiple times through keyword expansion the content lengths will be different. See how many clicks each banner gets. This is multivariate with the two variables being content length, and cache key. Cache key setup 1 (Long name has a worse spot in the cache): Short Name: 0.22% success rate (155300 samples) Long Name: 0.19% success rate (160800 samples) The 95% confidence interval has the long name performing from -31% to 3% worse than the short name with a power of 0.014. Cache key setup 2 (Long name has a better spot in the cache): Short Name: 0.20% success rate (294900 samples) Long Name: 0.19% success rate (309500 samples) The 95% CI here still has the long name performing worse; but with power that is effectively not useful. [1] https://gerrit.wikimedia.org/r/#/c/90667/ ~Matt Walker Wikimedia Foundation Fundraising Technology Team