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Multivariate Time Series Anomaly Detection in Azure

Louise Han announces an update to the anomaly detection service:

We are excited to announce that we are adding more powerful capabilities in Microsoft Azure Multivariate Anomaly Detector (MVAD) today. In the latest version(v1.1-preview.1) of this API, we implemented a new , in a synchronous manner, which means you could get the anomaly detection results immediately once you call this API. This synchronous inference API is a substantial change compared with previous inference process and will be more intuitive and easier-to-use.

Also, we added a new field named ‘interpretation‘  to give more explanations on an anomaly, like which variables have huge correlation changes and cause the anomaly. These updates will support you to better leverage MVAD and get more useful information to analyze and take actions.

Click through for some more details.