Mock sample for your project: DataLakeStoreFileSystemManagementClient API

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.

The Admin Backup 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 Application Insights workbook type.

The Microsoft Azure management API provides create, read, update, and delete functionality for Azure MariaDB resources including servers, databases, firewall rules, VNET rules, log files and configurations with new business model.

Role based access control provides you a way to apply granular level policy administration down to individual resources or resource groups. These operations enable you to manage role assignments. A role assignment grants access to Azure Active Directory users.

Use these REST APIs for performing retrieving a collection of policy snippets available in Azure API Management deployment.

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

REST API for Azure Blockchain Service

REST API for Azure Spring Cloud

Azure Digital Twins Client for managing DigitalTwinsInstance

The HDInsight Management Client.

Azure Maintenance Management Client

The SAP HANA on Azure Management Client.

The HDInsight Management Client.

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

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.

API spec for Microsoft.Security (Azure Security Center) resource provider