Mock sample for your project: Mixed Reality API

The Admin Infrastructure Insights Management Client.

Azure Maintenance Management Client

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

REST APIs for Azure Active Directory Connect Health

Use these REST APIs for performing operations to retrieve Products by Tags in Azure API Management deployment.

Azure Application Insights client for web test based alerting.

Azure Application Insights client for Components.

IP pool operation endpoints and objects.

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

Use these REST APIs for performing operations on User entity in Azure API Management deployment. The User entity in API Management represents the developers that call the APIs of the products to which they are subscribed.

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 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.

These are the Network Experiment APIs.

An API for QnAMaker Service

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.

Consumption management client provides access to consumption resources for Azure Enterprise Subscriptions.

The Run Commands Client.

The HDInsight Management 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 Compute Management Client.