Mock sample for your project: ServiceFabricManagementClient API

The Admin Fabric Management Client.

Azure Log Analytics API reference

Microsoft Azure Quota Resource Provider.

The Resource Health Client.

REST API for Azure VirtualWAN As a Service.

Provides operations for working with resources and resource groups.

This Swagger was generated by the API Framework.

AWS IoT Secure Tunneling AWS IoT Secure Tunnling enables you to create remote connections to devices deployed in the field. For more information about how AWS IoT Secure Tunneling works, see AWS IoT Secure Tunneling.

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.

API to Add/Remove/List Guest Diagnostics Settings Association for Azure Resources

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.

These APIs allow end users to operate on Azure Machine Learning Commitment Plans resources and their child Commitment Association resources. They support CRUD operations for commitment plans, get and list operations for commitment associations, moving commitment associations between commitment plans, and retrieving commitment plan usage history.

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

The Disk Resource Provider Client.

An API for face detection, verification, and identification.