Mock sample for your project: ApiManagementClient API

Load balancer admin operation endpoints and objects.

The Admin Backup Management Client.

The Admin Storage Management Client.

The Run Commands Client.

File share operation endpoints and objects.

Storage pool operation endpoints and objects.

Extracts information from forms and images into structured data.

Azure Application Insights client for work item configurations for a component.

The User Subscription Management Client.

Use these REST APIs for performing operations on who is going to receive notifications associated with your Azure API Management deployment.

The Admin Storage Management Client.

The Azure SQL Database management API provides a RESTful set of web APIs that interact with Azure SQL Database services to manage your databases. The API enables users to create, retrieve, update, and delete databases, servers, and other entities.

Creates an Azure Data Lake Analytics account management client.

Azure Event Hubs client

The Hybrid Compute Management Client.

The Managed Labs Client.

Specification for ManagedServices.

The Anomaly Detector API detects anomalies automatically in time series data. It supports two kinds of mode, one is for stateless using, another is for stateful using. In stateless mode, there are three functionalities. Entire Detect is for detecting the whole series with model trained by the time series, Last Detect is detecting last point with model trained by points before. ChangePoint Detect is for detecting trend changes in time series. In stateful mode, user can store time series, the stored time series will be used for detection anomalies. Under this mode, user can still use the above three functionalities by only giving a time range without preparing time series in client side. Besides the above three functionalities, stateful model also provide group based detection and labeling service. By leveraging labeling service user can provide labels for each detection result, these labels will be used for retuning or regenerating detection models. Inconsistency detection is a kind of group based detection, this detection will find inconsistency ones in a set of time series. By using anomaly detector service, business customers can discover incidents and establish a logic flow for root cause analysis.

The Container Service Client.