https://github.com/farfetch/maestro
A load testing tool to make tests execution and analysis using JMeter.
https://github.com/farfetch/maestro
hacktoberfest jmeter performance
Last synced: 9 months ago
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A load testing tool to make tests execution and analysis using JMeter.
- Host: GitHub
- URL: https://github.com/farfetch/maestro
- Owner: Farfetch
- License: mit
- Created: 2021-11-25T09:12:55.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2024-02-21T14:40:55.000Z (over 2 years ago)
- Last Synced: 2025-04-13T09:12:42.231Z (about 1 year ago)
- Topics: hacktoberfest, jmeter, performance
- Language: Python
- Homepage: https://Farfetch.github.io/maestro
- Size: 4.98 MB
- Stars: 32
- Watchers: 5
- Forks: 4
- Open Issues: 73
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Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Codeowners: .github/CODEOWNERS
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README

**Maestro** is a load testing tool, building on our years of experience in the load and performance testing industry. It provides a clean, approachable way of running JMeter based tests.
> **NOTICE:** Maestro is under development and there might be some breaking changes over versions. We do have regular releases and are really welcome to get feedback.
## Features
#### WEB-based UI
Maestro provides a list of endpoints from where you can analyze your test execution in real-time. There is a full overview of all charts and use cases available in the [Introduction section](https://farfetch.github.io/maestro/docs/intro)

#### Distributed & Scalable
The core concept of having agents deployed inside your infrastructure gives a lot of flexibility to make the tests stable, secure, and able to **_support the simulation of thousands requests/second_**.
#### Collaborative environment
_Real-time monitoring_, _Collaboration over results_, _Programmability_ are core things that Maestro focused on to make sure you can collaborate with your teams and improve over time.
## Usage
See our documentation in the [https://farfetch.github.io/maestro](https://farfetch.github.io/maestro).
Explore already published [Docker images](https://farfetch.github.io/maestro/docs/docker_images)
Start application locally by following up [Setup Environment](https://farfetch.github.io/maestro/docs/getting_started/setup_environment) guide.
## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please read the [CONTRIBUTING](CONTRIBUTING.md) file to know what we expect from your contribution and the guidelines you should follow.
## Maintainers
- [Vitalii Melnychuk](https://github.com/vitaliimelnychuk)
- [Nuno Dionísio](https://github.com/nunodio)
- [Dyego Wermelinger](https://github.com/dyegowermelinger)
## License
[MIT](LICENSE)