Mock sample for your project: Azure Machine Learning Workspaces API

The HDInsight Management Client.

Use these REST APIs for performing operations on tenant entity associated with your Azure API Management deployment. Using this entity you can manage properties and configuration that apply to the entire API Management service instance.

The HDInsight Management Client.

The Admin Compute Disk Management Client.

Edge gateway operation endpoints and objects.

Azure Application Insights client for Components.

Storage pool operation endpoints and objects.

The HDInsight Management Client.

Azure Application Insights client for Annotations for a component.

Kinesis Video Streams Signaling Service is a intermediate service that establishes a communication channel for discovering peers, transmitting offers and answers in order to establish peer-to-peer connection in webRTC technology.

Use these REST APIs for performing operations to retrieve Products by Tags in Azure API Management deployment.

Role based access control provides you a way to apply granular level policy administration down to individual resources or resource groups. These operations enable you to manage role definitions and role assignments. A role definition describes the set of actions that can be performed on resources. A role assignment grants access to Azure Active Directory users.

Use these REST APIs for performing operations on NamedValue 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 NamedValues. Each API Management service instance has a NamedValues collection of key/value pairs that are global to the service instance. These NamedValues can be used to manage constant string values across all API configuration and policies.

Amazon Kinesis Data Analytics is a fully managed service that you can use to process and analyze streaming data using Java, SQL, or Scala. The service enables you to quickly author and run Java, SQL, or Scala code against streaming sources to perform time series analytics, feed real-time dashboards, and create real-time metrics.

Amazon Simple Workflow Service The Amazon Simple Workflow Service (Amazon SWF) makes it easy to build applications that use Amazon's cloud to coordinate work across distributed components. In Amazon SWF, a task represents a logical unit of work that is performed by a component of your workflow. Coordinating tasks in a workflow involves managing intertask dependencies, scheduling, and concurrency in accordance with the logical flow of the application. Amazon SWF gives you full control over implementing tasks and coordinating them without worrying about underlying complexities such as tracking their progress and maintaining their state. This documentation serves as reference only. For a broader overview of the Amazon SWF programming model, see the Amazon SWF Developer Guide .

Azure Digital Twins Client for managing DigitalTwinsInstance