Mock sample for your project: StorageManagementClient API

Provides create, read, update and delete functionality for Azure SQL Database resources including servers, databases, elastic pools, recommendations, and operations.

The Container Service Client.

Azure Application Insights client for web test locations.

The Azure Analysis Services Web API provides a RESTful set of web services that enables users to create, retrieve, update, and delete Analysis Services servers

Storage pool operation endpoints and objects.

Use these REST APIs for performing operations on entities like API, Product, and Subscription associated with your Azure API Management deployment.

Deployment Admin Client.

Region health operation endpoints and objects.

AzureBridge Admin Client.

The Admin Storage Management Client.

Azure Bot Service is a platform for creating smart conversational agents.

Azure Alerts Management Service provides a single pane of glass of alerts across Azure Monitor.

AzureBridge Admin Client.

The HDInsight Management Client.

The Azure Serial Console allows you to access the serial console of a Virtual Machine or VM scale set instance

The Container Service Client.

The Container Service Client.

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 Anomaly Finder API detects anomalies automatically in time series data. It supports two functionalities, one is for detecting the whole series with model trained by the timeseries, another is detecting last point with model trained by points before. By using this service, business customers can discover incidents and establish a logic flow for root cause analysis.

The Container Service Client.

HyperDrive REST API

Virtual Machine Image Template