Mock sample for your project: PolicyClient API

The Container Service Client.

The User Subscription Management Client.

Azure Log Analytics API reference for management of saved Queries within Query Packs.

REST APIs for Azure Advisor

Provides read and update functionality for Azure SQL Server backup long term retention vault

Subscription client provides an interface to create and manage Azure subscriptions programmatically.

Resource health operation endpoints and objects.

The Azure Serial Console allows you to access the serial console of a Virtual Machine or VM scale set instance

REST API for Azure Blockchain Service

The Admin Storage Management Client.

Azure Service Bus client

The Microsoft Azure management API provides create, read, update, and delete functionality for Azure MySQL resources including servers, databases, firewall rules, VNET rules, log files and configurations with new business model.

The Text Analytics API is a suite of text analytics web services built with best-in-class Microsoft machine learning algorithms. The API can be used to analyze unstructured text for tasks such as sentiment analysis, key phrase extraction and language detection. No training data is needed to use this API; just bring your text data. This API uses advanced natural language processing techniques to deliver best in class predictions. Further documentation can be found in https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview

The Managed Service Identity Client.

The HDInsight Management Client.

An API for QnAMaker runtime

This Swagger was generated by the API Framework.

PowerBI Dedicated Web API provides a RESTful set of web services that enables users to create, retrieve, update, and delete Power BI dedicated capacities

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.

Creates an Azure Data Lake Analytics account management client.

The Container Service Client.