Mock sample for your project: SqlManagementClient API

File share operation endpoints and objects.

The Azure Management Groups API enables consolidation of multiple subscriptions/resources into an organizational hierarchy and centrally manage access control, policies, alerting and reporting for those resources.

The Admin Storage Management Client.

The Admin Storage Management Client.

Use these REST APIs for managing OAuth2 servers configuration in your Azure API Management deployment. OAuth 2.0 can be used to authorize developer accounts for Azure API Management. For more information refer to How to OAuth2.

Azure client for Workbook.

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

The Update Admin Management Client.

The HDInsight Management Client.

Creates an Azure Data Lake Analytics job client.

Azure IoT Central is a service that makes it easy to connect, monitor, and manage your IoT devices at scale.

Specification for ManagedServices.

The Azure Management Groups API enables consolidation of multiple subscriptions/resources into an organizational hierarchy and centrally manage access control, policies, alerting and reporting for those resources.

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.

These APIs allow end users to manage Azure Machine Learning Models, Images, Profiles, and Services.

The HDInsight Management Client.

Allows extension of ARM control plane with custom resource providers.

Azure Digital Twins Client for managing DigitalTwinsInstance