In this short article we talk about how to get Yape running in a docker container to avoid having to setup python on your machine.

It's been a while since the last article in this series, so let's recap quickly.

In last week's discussion we created a simple graph based on the data input from one file. Now, as we all know, sometimes we have multiple different datafiles to parse and correlate. So this week we are going to load additional perfmon data and learn how to plot that into the same graph.
Since we might want to use our generated graphs in reports or on a webpage, we'll also look into ways to export the generated graphs.

marking code snippets as python doesn't enable highlighting for python code

This is the first article of a series diving into visualization tools and analysis of time series data. Obviously we are most interested in looking at performance related data we can gather from the Caché family of products. However, as we'll see down the road, we are absolutely not limited to that. For now we are exploring python and the libraries/tools available within that ecosystem.

I was benchmarking the populate utils when I noticed something strange. Consider this simple benchmarking method: