Mock sample for your project: SqlManagementClient API

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Microsoft Azure Quota Resource Provider.

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.

APIs to deploy and manage resources to SeaBreeze.

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.

Azure Service Bus 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.

REST API for Azure Server Management Service.

Mixed Reality Resource Provider Remote Rendering Resource API

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

The Turbine Labs API provides CRUD operations for core object types, and is
mostly RESTy. The easiest way to interact with the API is with
tbnctl.
If you want to make direct HTTP calls, however, you can obtain an access
token using tbnctl, and then pass it in the Authorization header,
prefixed by Token :

The Compute Management Client.

The Container Service Client.

This API describe ACE Provisioning ManagementPartner

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.

APIs to manage web application firewall rules for Azure CDN

The Run Commands Client.