Mock sample for your project: ComputeManagementClient API

Creates an Azure Data Lake Analytics job client.

Azure Application Insights client for favorites.

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.

The Azure Data Catalog Resource Provider Services API.

Azure Enterprise Knowledge Graph Service is a platform for creating knowledge graphs at scale.

Storage subsystem operation endpoints and objects.

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

Dev Spaces REST API

Use this API to manage the IoTSpaces service instances in your Azure subscription.

The Admin Storage Management Client.

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

These APIs allow end users to operate on Azure Machine Learning Workspace resources. They support CRUD operations for Azure Machine Learning Workspaces.

The Microsoft Azure ExpressRouteCrossConnection Resource Provider REST APIs describes the operations for the connectivity provider to provision ExpressRoute circuit, create and modify BGP peering entities and troubleshoot connectivity on customer's ExpressRoute circuit.

Azure NotificationHub client

Microsoft NetApp Azure Resource Provider specification

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

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 for using the Azure IoT Hub Device Provisioning Service features.

The HDInsight Management Client.