Mock sample for your project: AutomationManagement API

Provides create, read, update and delete functionality for Azure SQL Database resources including servers, databases, elastic pools, recommendations, and operations.

Edge gateway pool operation endpoints and objects.

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

The HDInsight Job Client.

These APIs allow end users to operate on Azure Machine Learning Web Services resources. They support the following operations: Create or update a web service Get a web service Patch a web service Delete a web service Get All Web Services in a Resource Group Get All Web Services in a Subscription Get Web Services Keys

Azure Active Directory Client.

Shared Image Gallery Service Client.

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.

REST API for Azure Logic Apps.

This Swagger was generated by the API Framework.

Azure Application Insights client for Annotations for a component.

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

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.

The Container Service Client.

API for using the Azure IoT Hub Device Provisioning Service features.

The Container Service Client.

The Container Service Client.

Creates an Azure Data Lake Store filesystem client.