Profile your workload and share the results in data-rich, interactive charts
Version 1.01
#Requires
- Linux
- dstat
- python
- (Optional) Some of the advanced monitors (like GPU) use R scripts to parse output data
Start here:
- example.sh Simple write to disk example
- example-sweep.sh Sweeping block size while writing to disk
- example-cluster.sh Run workload on 2 machines at once
- example-spark.sh Run the SparkPi example on your spark cluster
- example-amester.sh Collect measurements on Power8 systems using the AMESTER tool
- TODO example-gpu.sh Record GPU profiles on systems with nvidia GPUs
- TODO example-perf.sh Record perf data
- TODO example-oprofile.sh Record oprofile data
This repository also makes use of:
- Dygraphs for javascript charts (included).
- c3.js for javascript charts (included).
- jquery-csv for csv parsing (included).
- GNU-time /usr/bin/time
Try it out:
sudo apt-get install -y dstat
git clone https://github.com/jschaub30/pid_monitor
cd pid_monitor/
cp example.sh your_workload.sh
[ Edit your_workload.sh ]
./your_workload.sh
./pid_webserver.sh
[ (Optional) copy the run directory to your web server ]
When run, these examples will create the following directories:
- ./rundir/[WORKLOAD-NAME]/[DATETIME]/data/raw # All config and raw data files end up here
- ./rundir/[WORKLOAD-NAME]/[DATETIME]/scripts # Measurement and analysis scripts
- ./rundir/[WORKLOAD-NAME]/[DATETIME]/html # For interactive charts
To permanently share all the measurements on your server, you need to enable a web server. On Ubuntu, this is as simple as
sudo apt-get install apache2
cd /var/www/html
sudo ln -sf [location of rundir in pid_monitor directory]