ccagency-load-simulation-experiments

This repository contains programs that can be used to execute an experiment on the RED execution engine CC-Agency and evaluate the results. These results can be used to estimate the performance of the agency installation.

These experiments start a docker container which executes echo hello.

The results of previously executed experiments are summarized in CSV files located under the results/ directory. The python programs to execute, fetch and plot experiments are located under the src/ directory. The directory experiment_templates/ contains a RED file that can be used as template for an experiment.

Dependencies

The required software dependencies to execute the experiments are listed in requirements.txt. To install them execute pip install -r requirements.txt, possibly in a virtual environment.

To execute the experiments a running CC-Agency installation is required. More information on how to setup CC-Agency can be found at the Curious Containers Documentation.

Execution

Execute experiments

To execute an experiment on your agency installation the program src/execute_experiment.py can be used.

python3 ./src/execute_experiment.py

In order to execute the experiments the agency-url of the agency on which the experiments are to be executed is asked, as well as the agency-username and corresponding agency-password. The agency-url should look similar to https://agency.example.de/cc. You can test the agency-url be accessing it with you browser. This should return a hello world json object.

This will start 10.000 docker containers on the agency cluster. To reduce the amount of docker containers you can specify the amount with the --num-batches argument.

# start 100 docker containers
python3 ./src/execute_experiment.py --num-batches 100

Results

After executing the experiments there will be a executed_experiments/ directory, that contains experiment meta information.

Make sure to remove this directory if you restart the experiment. Otherwise old experiments will be used for the following process.

Fetch batch information

To create a compact representation of the executed experiment run the following program.

python3 ./src/create_csv.py

To fetch the experiment information the agency authentication information is requested again. This can also take some minutes.

The result of this program is a the csv file results/processing_timestamps.csv. Before the program is executed, this csv file is already in the repository. It contains the results of a previously executed experiment and will be overwritten.

Plot the results

To create a plot showing the result execute the program

python3 ./src/plot_results.py

This will create the files state_changes.pdf and state_counts.pdf.