Well, because Yottaa’s web monitoring service monitors tens of thousands of web sites and has accumulated a database of tens of millions of web performance samples, we have a treasure trove of data. So I set out to answer the following questions:
- Are there ones that have a particularly poor “service level agreement” (SLA)?
Looking at data across millions of samples, I looked at the following metrics:
- Average size of the download;
- Average Time to Last Byte (i.e., how long it takes to download);
Here are the results:
|File Name||% of Web Sites||Size (Bytes)||Time to Last Byte (msec)||Samples with > 1 sec. Time to Last Byte (%)|
|ga.js (Google Analytics)||66.7%||14,888||253||8.6%|
|plusone.js (Google +1)||9.8%||7,036||823||26.7%|
|conversion.js (Google AdWords)||4.3%||2,467||197||3.0%|
|show_ads.js (Google AdSense)||4.0%||6,272||196||1.8%|
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Knowing the size of the file, server IP address and the download timeline, we can compute the individual server’s bandwidth. And as it turns out, this varies widely – typically a couple hundred KB/sec, though (as illustrated in the histogram below) there’s a spike at the high end.
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- Consider leveraging a content delivery network such as Akamai's or Yottaa's CDN.
There’s several ways I can imagine improving on this analysis:
- Though I believe our sample set is fairly broad (tens of thousands of web sites, and millions of browser samples), repeating this for a larger set of sites might give an even more representative view of the web;
Thoughts / Suggestions?