PerfMon PerfOrmance

Hi everyone,

I thought I’d post some graphs on the performance of the PerfMon Blog over the last couple months.  There are a few reasons for doing this:

1. I want to see how consistent performance of a WordPress blog is.
2. The graphs added to the page will mean more objects being downloaded which will affect the weight of the page, which in turn will allow me to look at how adding images will affect the performance of a page.

This first graph shows the average load time of the PerfMon Blog over time.  We can see from this graph that the performance of the blog is pretty consistent over a 30 day period (around 1.84 seconds) and rarely do errors occur (the errors on the graph are timeout errors that occurred when the perfmon.wordpress.com page took longer than 3 seconds to download):

Average load time performance of the PerfMon Blog.

So far we see that the performance is pretty consistent from a high level.  The timeout errors when the page takes longer than 3 seconds to download does not concern me too much (it’s bound to happen) and a very consistent performance (that is a non-spikey graph) is always a good sign, especially when monitoring from geographically dispersed locations.  Now let’s drill down a bit and see what the performance of the page looks like from the object level (images, CSS, JavaScript files).  Here we have a waterfall style graph called a Full-Page Breakdown:

Full-Page breakdown for PerfMon Blog

The graph shows us the performance of the items on the page and breaks down that performance into three key values: DNS lookup time, latency time (i.e. 1st packet time), and transfer time.  Since monitoring is being performed from an IE browser we know that we’re seeing the actual performance of the page (JavaScript execution, rendering and layout, as well as any objects requested asynchronously…if any).  The object level performance looks pretty good the only thing I’d really like to comment on is the DNS lookup time (the yellow values of the graph).  It seems that because of a number of third party items (analytics and advertising code) there is a bit more DNS lookup time then I’d like.  The way IE works it will perform a DNS lookup for a domain only once and then cache that information for the remainder of the session.  So every time a new domain is introduced a DNS lookup needs to be performed.  We spent about 0.5 seconds doing DNS queries!

This final graph is here to show how the PerfMon Blog performs for viewers coming from different locations.  It looks fairly good:

Uptime and average load time for PerfMon Blog

This is fairly good performance.  The average load time (per monitoring location) is represented by the green line.  This line is rather straight meaning that the performance is consistent regardless of where in the US you are viewing the PerfMon Blog from.  That’s good news!  Often this line will start out low on the right (meaning the performance is good from those locations) and will increase as the line moves to the left of the graph indicating that users further from the server hosting the web-site see poor performance.  The background of the graph is broken down into 3 values:

1. Green – This is the percentage of successful samples taken from that location.
2. Yellow – This is the percentage of unvalidated errors.  An error is unvalidated if another monitoring location is unable to duplicate the error that was reported.
3. Red – This is the percentage of validated errors from the location.  An error is validated if a number of monitoring locations reported the same error.

We can see that certain regions generally see more errors (validated and unvalidated): Salt Lake City, Boston, San Jose, Newark, Scranton, and Los Angeles.  This coeincides with their higher load times as well.  Overall, the performance of the PerfMon Blog page is pretty good.  The question is; is that because it has minimal content, is hosted on a solid infrastructure, or has very few people viewing it .