Mock sample for your project: Engagement.ManagementClient API

The Managed Labs Client.

Use these REST APIs for performing operations on Quota entity associated with your Azure API Management deployment. To configure call rate limit and quota policies refer to how to configure call rate limit and quota.

Creates an Azure Data Lake Analytics catalog 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.

The DevTest Labs Client.

Use these REST APIs for performing operations on Identity Provider entity associated with your Azure API Management deployment. Setting up an external Identity Provider for authentication can help you manage the developer portal logins using the OAuth2 flow.

The HDInsight Management Client.

The Admin Commerce Management Client.

Azure EventGrid Management Client

The Admin Compute Disk Management Client.

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 Storage Management API.

These APIs allow end users to manage Azure Machine Learning Models, Images, Profiles, and Services.

Azure DevOps Resource Provider

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

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.

Azure Bot Service is a platform for creating smart conversational agents.

Azure Digital Twins Client for managing DigitalTwinsInstance

APIs to manage web application firewall rules.