Mock sample for your project: Azure Stack Azure Bridge Client API

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The HDInsight Management Client.

Azure Cosmos DB Database Service Resource Provider REST API

The Admin Storage Management Client.

The Admin Storage Management Client.

Azure Blueprints Client provides access to blueprint definitions, assignments, and artifacts, and related blueprint operations.

REST API for Azure Blockchain Service

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Virtual Network admin operation endpoints and objects.

Update location operation endpoints and objects.

Microsoft.Intune Resource provider Api features in the swagger-2.0 specification

The Azure management API provides a RESTful set of web services that interact with Azure Key Vault.

The Container Service Client.

Microsoft.Intune Resource provider Api features in the swagger-2.0 specification

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.

APIs to manage web application firewall rules.

Allows creation and deletion of Azure Shared Dashboards.

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 Microsoft Azure management API provides create, read, update, and delete functionality for Azure MySQL resources including servers, databases, firewall rules, VNET rules, security alert policies, log files, encryption keys, active directory administrator and configurations.

Creates an Azure Data Lake Analytics job client.

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A client for issuing REST requests to the Azure metrics service.