Mock sample for your project: FrontDoorManagementClient API

API to manage VM Insights Onboarding

Describes the interface for the per-tenant enclave service.

The Admin Subscriptions Management Client.

Use these REST APIs for performing operations on Diagnostic entity associated with your Azure API Management deployment. Diagnostics are used to log requests/responses in the APIM proxy.

Use these REST APIs for performing operations on API entity and their Operations associated with your Azure API Management deployment.

The Admin Infrastructure Insights Management Client.

Azure Application Insights client for saved items.

Use these REST APIs for performing operations on Property entity associated with your Azure API Management deployment. API Management policies are a powerful capability of the system that allow the publisher to change the behavior of the API through configuration. Policies are a collection of statements that are executed sequentially on the request or response of an API. Policy statements can be constructed using literal text values, policy expressions, and properties. Each API Management service instance has a properties collection of key/value pairs that are global to the service instance. These properties can be used to manage constant string values across all API configuration and policies.

The Admin Subscriptions Management Client.

Azure Application Insights client for Components.

Deployment Admin Client.

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

Amazon Connect is a cloud-based contact center solution that you use to set up and manage a customer contact center and provide reliable customer engagement at any scale. Amazon Connect provides metrics and real-time reporting that enable you to optimize contact routing. You can also resolve customer issues more efficiently by getting customers in touch with the appropriate agents. There are limits to the number of Amazon Connect resources that you can create. There are also limits to the number of requests that you can make per second. For more information, see Amazon Connect Service Quotas in the Amazon Connect Administrator Guide. You can connect programmatically to an AWS service by using an endpoint. For a list of Amazon Connect endpoints, see Amazon Connect Endpoints. Working with contact flows? Check out the Amazon Connect Flow language.

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.

Use these APIs to manage Azure Front Door resources through the Azure Resource Manager. You must make sure that requests made to these resources are secure.

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 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.

Azure Log Analytics API reference for Solution.

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.

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.