https://github.com/timonback/thesis-msc-simulator

Master project. Simulator to find the optimal deployment model of FaaS (serverless) and VM-based instances to reduce cost
https://github.com/timonback/thesis-msc-simulator

cloud faas nodejs pareto-optimality serverless vm

Last synced: 3 months ago
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Master project. Simulator to find the optimal deployment model of FaaS (serverless) and VM-based instances to reduce cost

• Host: GitHub
• URL: https://github.com/timonback/thesis-msc-simulator
• Owner: timonback
• Created: 2018-08-30T13:42:25.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T06:08:33.000Z (about 2 years ago)
• Last Synced: 2024-10-10T05:38:06.152Z (3 months ago)
• Topics: cloud, faas, nodejs, pareto-optimality, serverless, vm
• Language: JavaScript
• Homepage: https://fse.studenttheses.ub.rug.nl/18484/
• Size: 345 KB
• Stars: 6
• Watchers: 2
• Forks: 5
• Open Issues: 6
• Metadata Files:
  • Readme: README.md

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README

        
# Cloud Load Simulator

[![CircleCI](https://circleci.com/gh/timonback/thesis-msc-simulator.svg?style=svg&circle-token=9c777812c1ea59fd70f1eb8092675cfa4657c088)](https://circleci.com/gh/timonback/thesis-msc-simulator)

Demo at: [https://faas-simulator.herokuapp.com/index.html](https://faas-simulator.herokuapp.com/index.html)

It simulates various loads towards a cloud environment.

Based on the configuration, the cost for handling all requests is calculated.

In many cases (depending on the load characteristics), the cost can be reduced by moving certain requests to FaaS 

(Function as a Service).

This is a Python 3 project that requires the dependencies to be install via `python3 setup.py install` 

(virtualenv is recommended in general).

All of the configuration is done in the `simulator/configuration.py` file.

## Standalone

Run `python3 main.py`

## Server

Run `python3 serve.py`

Then open `http://localhost:8888/index.html`

![Screenshot](../master/README_screenshot.png?raw=true)

## Tests

Run the tests `python3 setup.py test`. A coverage report is generated in `./htmlcov`.

## Profiling

Run the tests `python3 setup.py test` to profile.

Convert the profiling file (`profiler.dmp`) into a readable file with `python3 util/analyze_dmp.py profiler.dmp 

profiler.log`.