In performancetest users can find all the resources to conduct benchmark and performance tests. Moreover, to process and present the results. In the docs folder users will find detailed test explanations, comprehensive instructions on how to execute these tests, and a comprehensive guide on how to effectively process the gathered data. In the tools folder the user can find the python3 notebooks and Python file with the basic functions needed for creating the reports.
In order to setup your environment, run
pip install -r requirements.txt
to install the necessary Python packages. Everytime you login, run
source setup.sh
or add this to env.sh in your dunedaq workspace.
To generate a performance report the tools collect_metrics.py and generate_performance_report.py are used. Both tools require a json file as input, which provides metrics about the test and necessary information requiret to retrieve the data. To generate a template json file, run
collect_metrics.py -g
which should produce a file called template_report.json in your current directory. In this configuration file lists all the information needed and a brief decsription describing each entry. Note that entries with None are optional. Once all the information is filled run
collect_metrics.py -f <name of your json file>
to collect the dashboard information and format the core utilisation output. The output of this script are csv files for each test and core utilisation file, which are automatically added to your json file under the entries grafana_data_files and core_utilisation_files, respectively.
Generate the performance report by running
generate_performance_report.py -f <name of your json file>