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https://github.com/chaos-genius/chaos_genius

ML powered analytics engine for outlier detection and root cause analysis.
https://github.com/chaos-genius/chaos_genius

ai alert alert-messages analytics anomaly-detection business-intelligence data-visualization dataquality deep-learning hacktoberfest machine-learning ml monitoring monitoring-tool observability outlier-detection python rootcauseanalysis seasonality time-series

Last synced: 6 days ago
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ML powered analytics engine for outlier detection and root cause analysis.

Host: GitHub
URL: https://github.com/chaos-genius/chaos_genius
Owner: chaos-genius
License: mit
Created: 2021-05-27T08:13:03.000Z (over 3 years ago)
Default Branch: main
Last Pushed: 2024-05-07T05:24:30.000Z (6 months ago)
Last Synced: 2024-05-22T12:17:11.951Z (6 months ago)
Topics: ai, alert, alert-messages, analytics, anomaly-detection, business-intelligence, data-visualization, dataquality, deep-learning, hacktoberfest, machine-learning, ml, monitoring, monitoring-tool, observability, outlier-detection, python, rootcauseanalysis, seasonality, time-series
Language: Python
Homepage: https://www.chaosgenius.io
Size: 9.88 MB
Stars: 705
Watchers: 10
Forks: 81
Open Issues: 141
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
- Roadmap: roadmap.md

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README

![CG Header](https://raw.githubusercontent.com/chaos-genius/.github/main/images/CG-banner.png)

Website •
Docs •
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LinkedIn •
Community Slack

ML powered analytics engine for outlier detection and root cause analysis

## Repository Status: Archived

⚠️ **Notice:** This repository is no longer actively maintained or developed. It remains available for historical reference, but no further updates or support will be provided. Users are advised to consider more up-to-date alternatives.

## ✨ What is Chaos Genius?

Chaos Genius is an open source ML powered analytics engine for outlier detection and root cause analysis. Chaos Genius can be used to monitor and analyse high dimensionality business, data and system metrics at scale.

Using Chaos Genius, users can segment large datasets by key performance metrics (e.g. Daily Active Users, Cloud Costs, Failure Rates) and important dimensions (e.g., countryID, DeviceID, ProductID, DayofWeek) across which they want to monitor and analyse the key metrics.

### Use Chaos Genius if you want:
- Multidimensional Drill Downs & Insights
- Anomaly Detection
- Smart Alerting
- Seasonality Detection*
- Automated Root Cause Analysis*
- Forecasting*
- What-If Analysis*

**in Short and Medium-term Roadmap*

### Demo

[A small demo of Chaos Genius](https://chaosgenius-public.s3.amazonaws.com/test-cg-1-small.gif)

## ⚙️ Quick Start

```
git clone https://github.com/chaos-genius/chaos_genius

cd chaos_genius

docker-compose up
```

Visit [http://localhost:8080](http://localhost:8080/)

Follow this [Quick Start guide](https://docs.chaosgenius.io/docs/Quick_Start/prereqs) or read our [Documentation](https://docs.chaosgenius.io/docs/introduction) for more details.

## :dizzy: Key Features

### 1. Automated DeepDrills

Generate multidimensional drilldowns to identify the key drivers of change in defined metrics (e.g. Sales) across a large number of high cardinality dimensions (e.g. CountryID, ProductID, BrandID, Device_type).
- Techniques: Statistical Filtering, A* like path based search to deal with combinatorial explosion

![DD](https://raw.githubusercontent.com/chaos-genius/.github/main/images/DeepDrills.png)

### 2. Anomaly Detection

Modular anomaly detection toolkit for monitoring high-dimensional time series with ability to select from different models. Tackle variations caused by seasonality, trends and holidays in the time series data.
- Models: Prophet, EWMA, EWSTD, Neural Prophet, Greykite

![Anomaly](https://raw.githubusercontent.com/chaos-genius/.github/main/images/AnomalyDrillDowns.png)

### 3. Smart Alerts

Actionable alerts with self-learning thresholds. Configurations to setup alert frequency & reporting to combat alert fatigue.
- Channels: Email, Slack

![Alerting](https://raw.githubusercontent.com/chaos-genius/.github/main/images/Alerting-Dark.png)

## :octocat: Community

For any help, discussions and suggestions feel free to reach out to the Chaos Genius team and the community here:

- [GitHub](https://github.com/chaos-genius/.github) (report bugs, contribute, follow roadmap)

- [Slack](https://join.slack.com/t/chaosgenius/shared_invite/zt-140042uac-rrm~xbx9o_aydi6PTmp_Mg) (discuss with the community and Chaos Genius team)

- [Book Office Hours](https://calendly.com/chaosgenius/30min) (set up time with the Chaos Genius team for any questions or help with setup)

- [Blog](https://chaosgenius.io/blog/) (follow us on latest trends on Data, Machine Learning, Open Source and more)

## 🚦 Roadmap

Our goal is to make Chaos Genius production ready for all organisations irrespective of their data infrasturcture, data sources and scale requirements. With that in mind we have created a [roadmap](https://docs.chaosgenius.io/docs/roadmap/) for Chaos Genius. If you see something missing or wish to make suggestions, please drop us a line on our [Community Slack](https://join.slack.com/t/chaosgenius/shared_invite/zt-140042uac-rrm~xbx9o_aydi6PTmp_Mg) or raise an issue.

## :seedling: Contributing

Want to contribute? Get started with:

- Show us some love - Give us a :star2:!

- Submit an issue.

- Share a part of the documentation that you find difficult to follow.

- [Translate our Readme](https://github.com/chaos-genius/chaos_genius/blob/main/README.md).

- Create a pull request. Here's a [list of issues](https://github.com/chaos-genius/chaos_genius/issues) to start with. Please review our [contribution guidelines](https://github.com/chaos-genius/chaos_genius/blob/main/CONTRIBUTING.md) before opening a pull request. Thank you for contributing!

## :heart: Contributors

Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):

_pshrimal21
📆 📖 🤔 🎨

_{Harshit Surana}
💻 🔣 🔬 🐛

_{Manas Solanki}
💻 👀 🔧 🐛

_{Kartikay Bagla}
💻 🚧 🔬

_{Varun P}
💻 🚧 🔬

_{Keshav Pradeep}
💻 🔣 📖

_{Daj Katal}
🔌 📖

_{Amatullah Sethjiwala}
💻 🔣 ⚠️

_juzarbhori
💻 🎨

_{Amogh Dhar Diwan}
💻 🔣 🐛

_{Samyak Sarnayak}
💻 📦 🐛

_{Aayush Naik}
💻 🐛 📦

_{Kshitij Agarwal}
💻 🔧 🐛

_{Bhargav S. Kumar}
💻 📦 🐛

_{moghankumar06}
💻 🎨

_{Santhoshkumar1023}
💻 🎨

_{Mansi-Chauhan27}
🔌

_{davidhayter-karhoo}
🐛

_{Marijn van Aerle}
🐛

_gxu-kangaroo
🐛

_{RamneekKaur983}
💻

_arvind-27
🔣

_{Josh Taylor}
🐛

_ChartistDev
💻 🎨 🐛 👀

_{Rajdeep Sharma}
💻 👀

_{balakumar9493}
💻 🎨

_{Ikko Ashimine}
💻

_{rohit sohlot}
💻

_athul-osmo
🐛

_{Kumar Shivendu}
🐛 🤔

_{Pratham Sharma}
🐛

_{churchill1973}
🤔