Clustinator is an incremental clustering service for ContinuITy, which is the open-source implementation of a research project on “Automated Performance Testing in Continuous Software Engineering”, launched by Novatec Consulting GmbH and the University of Stuttgart (Reliable Software Systems Group). ContinuITy started in September 2017 with a duration of 2.5 years. It is funded by the German Federal Ministry of Education and Research (BMBF). For details about the research project, please refer to our Web site.

Clustinator integrates with the application architecture of ContinuITy. Being triggered via RabbitMQ by the Cobra service, it retrieves sessions from an Elasticsearch, clusters them into user groups of similar behavior, stores the results into the Elasticsearch, and reports back to the remaining ContinuITy services. The user behavior representation relates to the WESSBAS-DSL.

We provide Clustinator as a Docker image, which can be easily executed as follows:

docker run continuityproject/clustinator

The following configuration options can be added as environment variable (using the -e flag). The default properties fit the default ContinuITy Docker setup.

• RABBITMQ: Host name of the RabbitMQ server. Defaults to rabbitmq.
• ELASTIC: Host name of Elasticsearch. Defaults to cobra-db.
• RABBITMQ_TIMEOUT: The timeout in seconds after which the RabbitMQ connection is treated to be dead. Defaults to 60.
• ELASTIC_TIMEOUT: The timeout in seconds to wait for an Elasticsearch request. Defaults to 10.
• SESSIONS_BUFFER: A file path to a session matrix buffer. None (the default) means not buffering the matrices. The path is inside the Docker container and can be mapped to a local folder as a volume.
• FAST_TEST: Set to true to do a fast test run without think time calculation. DO NOT USE IN PRODUCTION! Defaults to false.

Clustinator can also be executed locally, e.g., when developing the service. We recommend using Python 3.6.

Check out this Git repository and install the required packages:

pip install -r requirements.txt

Then, go to the folder clustinator and run the service using the following command:

python receiver.py [-h] [--rabbitmq [RABBITMQ]]
                   [--rabbitmq-port [RABBITMQ_PORT]] [--elastic [ELASTIC]]
                   [--timeout [TIMEOUT]] [--elastic-timeout [ELASTIC_TIMEOUT]]
                   [--sessions-buffer [SESSIONS_BUFFER]] [--fast-test]

Optional arguments are the following:

• -h, --help: Show a help message and exit.
• --rabbitmq [RABBITMQ]: The host name or IP of the RabbitMQ server. Defaults to localhost.
• --rabbitmq-port [RABBITMQ_PORT]: The port number of the RabbitMQ server. Defaults to 5672.
• --elastic [ELASTIC]: The host name or IP of the elasticsearch server. Defaults to localhost.
• --timeout [TIMEOUT]: The timeout in seconds after which the RabbitMQ connection is treated to be dead. Defaults to None, which accepts the server's proposal.
• --elastic-timeout [ELASTIC_TIMEOUT]: The timeout in seconds to wait for an Elasticsearch request. Defaults to 10.
• --sessions-buffer [SESSIONS_BUFFER]: A file path to a session matrix buffer. None (the default) means not buffering the matrices.
• --fast-test: Set to true to do a fast test run without think time calculation. DO NOT USE IN PRODUCTION!

Clustinator implements or is based on the work of several scientific publications, which we list in the following. Here, we only consider publications that directly influenced the implementation; further publications of the ContinuITy project are available on the project web site.

• Henning Schulz, Tobias Angerstein, and André van Hoorn: Towards Automating Representative Load Testing in Continuous Software Engineering (full paper), Companion of the International Conference on Performance Engineering (ICPE) 2018, Berlin, Germany
• Christian Vögele, André van Hoorn, Eike Schulz, Wilhelm Hasselbring, and Helmut Krcmar: WESSBAS: extraction of probabilistic workload specifications for load testing and performance prediction - a model-driven approach for session-based application systems, Software and Systems Modeling 17(2): 443-477 (2018)

This project is licensed under Apache v2 - see the LICENSE file for details.