Mock sample for your project: RunCommandsClient API

The DevTest Labs Client.

Use these REST APIs for performing operations on Email Templates associated with your Azure API Management deployment.

Creates an Azure Data Lake Analytics catalog 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.

The Admin Storage Management Client.

The HDInsight Management Client.

The Compute Management Client.

The Admin Subscriptions 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 HDInsight Management Client.

Fabric location operation endpoints and objects.

The Admin Storage Management Client.

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

The Azure Data Catalog Resource Provider Services API.

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.

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

Allows extension of ARM control plane with custom resource providers.

You use the API to scan your content as it is generated. Content Moderator then processes your content and sends the results along with relevant information either back to your systems or to the built-in review tool. You can use this information to take decisions e.g. take it down, send to human judge, etc.
When using the API, images need to have a minimum of 128 pixels and a maximum file size of 4MB.
Text can be at most 1024 characters long.
If the content passed to the text API or the image API exceeds the size limits, the API will return an error code that informs about the issue.

Azure Digital Twins Client for managing DigitalTwinsInstance

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.

Azure Cosmos DB Database Service Resource Provider REST API