CueObserve
luminol
Our great sponsors
| CueObserve | luminol | |
|---|---|---|
| 6 | 3 | |
| 205 | 1,157 | |
| 0.0% | 1.2% | |
| 0.0 | 1.6 | |
| about 2 years ago | 12 months ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
CueObserve
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[Project] Open-source Anomaly detection on SQL data
We are building CueObserve, an open source repo to run anomaly detection on data in your SQL data warehouses and databases. It currently supports BigQuery, RedShift, Snowflake, Postgres, MySQL and Druid. It is available at github.com/cuebook/cueobserve.
- CueObserve - Anomaly detection on SQL data warehouses and databases
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Show HN: CueObserve – Open-source Anomaly detection on SQL data
Hi HN, Sachin here with Ankit, Praveen, Vineet and Vikrant.
With CueObserve, you can run anomaly detection on business metric data in your SQL data warehouses and databases. CueObserve currently supports 6 data sources - BigQuery, RedShift, Snowflake, Postgres, MySQL and Druid.
CueObserve is open-source (https://github.com/cuebook/CueObserve). Docs are at https://cueobserve.cuebook.ai
Do give it a try and let us know. We’d love to hear your thoughts, feedback, and questions.
luminol
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How are SREs using AI?
We use something (developed in-house) similar to https://github.com/linkedin/luminol for anomaly and correlation.
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[P] anomaly detection in time series data
Hey, I solved this problem in my current job using Time Series Bitmap + Clustering. There's an implementation of this algorithm in this Linkedin's package called Luminol: https://github.com/linkedin/luminol
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How to make timer series correlations running faster?
I'm using the Luminol package to calculate correlations among normalized data.
What are some alternatives?
growthbook - Open Source Feature Flagging and A/B Testing Platform
luminaire - Luminaire is a python package that provides ML driven solutions for monitoring time series data.
ethereum-etl - Python scripts for ETL (extract, transform and load) jobs for Ethereum blocks, transactions, ERC20 / ERC721 tokens, transfers, receipts, logs, contracts, internal transactions. Data is available in Google BigQuery https://goo.gl/oY5BCQ
stumpy - STUMPY is a powerful and scalable Python library for modern time series analysis
bigquery_fdw - BigQuery Foreign Data Wrapper for PostgreSQL
loglizer - A machine learning toolkit for log-based anomaly detection [ISSRE'16]
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
opensnitch - OpenSnitch is a GNU/Linux application firewall
dbt-ml-preprocessing - A SQL port of python's scikit-learn preprocessing module, provided as cross-database dbt macros.
diepvries - The Picnic Data Vault framework.