Identifying problems with Anomaly Detector
Anomaly Detector helps you easily embed anomaly detection capabilities into your apps so users can quickly identify problems. No background in machine learning is required. This API ingests time-series data of all types and selects the best fitting anomaly detection model for your data to ensure high accuracy.
Ingests data from the various shops that contain raw data to be monitored by Anomaly Detector.
Aggregates, samples and computes the raw data to generate the time series, or calls the Anomaly Detector API directly if the time series are already prepared and gets a response with the detection results.
Queues the anomaly-related meta data.
Based on the anomaly-related meta data, calls the customised alerting service.
Stores the anomaly detection meta data.
Visualises the results of the time series anomaly detection.
- 1 Ingests data from the various shops that contain raw data to be monitored by Anomaly Detector.
- 2 Aggregates, samples and computes the raw data to generate the time series, or calls the Anomaly Detector API directly if the time series are already prepared and gets a response with the detection results.
- 3 Queues the anomaly-related meta data.
- 4 Based on the anomaly-related meta data, calls the customised alerting service.
- 5 Stores the anomaly detection meta data.
- 6 Visualises the results of the time series anomaly detection.
Implementation guidance
| Products/Description | Documentation | |
|---|---|---|
|
Service Bus |
Reliable cloud messaging as a service (MaaS) and simple hybrid integration | |
|
Azure Databricks |
Simplify on-premises database migration to the cloud | |
|
|
Improve business analytics | |
|
Storage Accounts |
Durable, highly available and massively scalable cloud storage |