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# Multivariate time series Anomaly Detection (preview)
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# What is Multivariate Anomaly Detector? (Public Preview)
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The new **multivariate anomaly detection** APIs further enable developers by easily integrating advanced AI for detecting anomalies from groups of metrics, without the need for machine learning knowledge or labeled data. Dependencies and inter-correlations between up to 300 different signals are now automatically counted as key factors. This new capability helps you to proactively protect your complex systems such as software applications, servers, factory machines, spacecraft, or even your business, from failures.
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@@ -35,7 +36,28 @@ To run the Notebook, you should get a valid Anomaly Detector API **subscription
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## Region support
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The preview of Multivariate Anomaly Detector is currently available in 26 Azure regions: Southeast Asia, Australia East, Canada Central, North Europe, West Europe, East US, East US 2, South Central US, West US, West US 2, West US 3, UK South, Japan East, Brazil South, Central US, Norway East, Korea Central, East Asia, Germany West Central, Central India, UAE North, France Central, North Central US, Switzerland North, South Africa North, Jio India West.
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The preview of Multivariate Anomaly Detector is currently available in 26 Azure regions.
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| Geography | Regions |
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| ------------- | ---------------- |
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| Africa | South Africa North |
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| Asia Pacific | Southeast Asia, East Asia|
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| Australia | Australia East |
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| Brazil |Brazil South|
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|Canada | Canada Central |
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| Europe | North Europe, West Europe, Switzerland North |
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|France |France Central |
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|Germany| Germany West Central |
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|India| Jio India West, Central India |
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|Japan | Japan East |
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|Korea | Korea Central |
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|Norway | Norway East|
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|United Arab Emirates| UAE North |
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| United Kingdom | UK South |
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| United States | East US, East US 2, South Central US, West US, West US 2, West US 3, Central US, North Central US|
The Anomaly Detector API enables you to monitor and detect abnormalities in your time series data without having to know machine learning. The Anomaly Detector API's algorithms adapt by automatically identifying and applying the best-fitting models to your data, regardless of industry, scenario, or data volume. Using your time series data, the API determines boundaries for anomaly detection, expected values, and which data points are anomalies.
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1. Send a request to the Anomaly Detector API with your data.
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1. Process the API response by parsing the returned JSON message.
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## Algorithms
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* See the following technical blogs for information about the algorithms used:
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