Go Guerrill-R on Your Data

The Guerrilla Data Analysis Techniques training course (GDAT) will be held during the week of August 8-12 this year. As usual, the focus will be on applying R to your performance and capacity planning data, as well as how to use the PDQ-R modeling tool.


(Click on the image for details)
Classes are held at our Larkspur Landing location in Pleasanton, California; a 45-minute BART ride to downtown San Francisco. For those of you coming from international locations, here is a table of currency EXCHANGE rates. We look forward to seeing all of you in August!

Quantifying Scalability FTW (The Movie)

The video of my presentation at the Surge 2010 conference on scalability and performance has finally been posted. Since it doesn't seem to be a streaming server, it may take several minutes to download the video (depending on the speed of your pipe). Also, the audio is suboptimal because it seems to have been recorded from the ambient loudspeakers rather than a direct mic. I was too busy giving the talk to remember the setup they used.

Here's the abstract:

You probably already collect performance data, but data ain't information. Successfull scalability requires transforming your data so that you can quantify the cost-benefit of any architectural decisions. In other words:

measurement + models == information
So, measurement alone is only half the story; you need a method to transform your data. In this presentation I will show you a method that I have developed and applied successfully to large-scale web sites and stack applications to quantify the benefits of proposed scaling strategies. To the degree that you don't quantify your scalability, you run the risk of ending up with WTF rather than FTW.

May 2011 Guerrilla Classes: Light Bulb Moments

It's impossible to know what will constitute a light bulb moment for someone else. In the recent Guerrilla classes (GBoot and GCaP), we seemed to be having many more than our usual quota of such moments. So much so, that I decided to keep a list.

Applying PDQ in R to Load Testing

PDQ is a library of functions that helps you to express and solve performance questions about computer systems using the abstraction of queues. The queueing paradigm is a natural choice because, whether big (a web site) or small (a laptop), all computer systems can be represented as a network or circuit of buffers and a buffer is a type of queue.

Fundamental Performance Metrics

Baron Schwartz invited me to comment on his latest blog post entitled "The four fundamental performance metrics," which I did. Coincidentally, I happened to address this same topic in my presentation at CMG Atlanta last week. As the following slides shows, I claim there are really only 3 fundamental performance metrics (actually 2, if you want to get truly fundamental about it).