vasim 0.1.3

Vertical Autoscaler Simulator Toolkit

VASIM

VASIM (Vertical Autoscaling SIMulator) is a tool designed to address the complexities involved in assessing autoscaling algorithms.

VASIM is designed for testing recommendation algorithms, with a particular focus on CPU usage in VMs and Kubernetes pods. The toolkit replicates common components found in autoscaler architectures, including the controller, metrics collector, recommender, and resource updater. It enables a comprehensive simulation of the entire autoscaling system’s behavior, with the flexibility to customize various parameters.

If you are writing an academic paper, you can cite this work as:

@inproceedings{pavlenko2024vasim,
  author = {Pavlenko, Anna and Saur, Karla and Zhu, Yiwen and Kroth, Brian and Cahoon, Joyce and Camacho-Rodríguez, Jesús},
  title = {VASIM: Vertical Autoscaling Simulator Toolkit},
  booktitle = {IEEE International Conference on Data Engineering (ICDE 2024)},
  year = {2024},
  month = {May},
}

Start here!

Our documentation and working example is in our notebook that shows how to get started simulating your data traces and tuning parameters. Our example provides the 3 things needed to run VASim: (1) a data csv file, (2) an autoscaling algorithm, and (3) a metadata.json file of parameters. Details of all of these can be found in the notebook.

Additionally:

• Within each folder, there is a README explaining the code.

  • simulator
  • recommender
  • forecasting
  • cluster state
  • tests

• For additional usage examples, see any test in the tests folder that starts with test_e2e.

• Please see our blog post or research paper for more details!

Authors

• Anna Pavlenko (@apavlen, primary implementation)
• Karla Saur (@ksaur, editing, maintaining)
• Yiwen Zhu (@zyw400)
• Brian Kroth (@bpkroth)
• Joyce Cahoon (@jyuu)
• Jesús Camacho Rodríguez (@jcamachor)

Contributing

Please see CONTRIBUTING.md for techinical details.

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [e-mail] with any additional questions or comments.

Trademarks

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