Mock sample for your project: ApplicationInsightsManagementClient API

Use these REST APIs for performing retrieve a collection of Apis associated with a tag in Azure API Management deployment.

Resource Provider

Use these REST APIs for performing operations on User entity in Azure API Management deployment. The User entity in API Management represents the developers that call the APIs of the products to which they are subscribed.

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

Use these REST APIs for performing operations on Certificate entity in your Azure API Management deployment. Certificates can be used to setup mutual authentication with your Backend in API Management. For more information refer to How to secure backend using Mutual Auth Certificate.

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

The HDInsight Job Client.

Azure Application Insights workbook template type.

Public IP Address admin endpoints and objects.

Virtual Machine Image Template

This Swagger was generated by the API Framework.

The Container Service Client.

Amazon GameLift Service GameLift provides solutions for hosting session-based multiplayer game servers in the cloud, including tools for deploying, operating, and scaling game servers. Built on AWS global computing infrastructure, GameLift helps you deliver high-performance, high-reliability, low-cost game servers while dynamically scaling your resource usage to meet player demand. About GameLift solutions Get more information on these GameLift solutions in the GameLift Developer Guide. GameLift managed hosting -- GameLift offers a fully managed service to set up and maintain computing machines for hosting, manage game session and player session life cycle, and handle security, storage, and performance tracking. You can use automatic scaling tools to balance player demand and hosting costs, configure your game session management to minimize player latency, and add FlexMatch for matchmaking. Managed hosting with Realtime Servers -- With GameLift Realtime Servers, you can quickly configure and set up ready-to-go game servers for your game. Realtime Servers provides a game server framework with core GameLift infrastructure already built in. Then use the full range of GameLift managed hosting features, including FlexMatch, for your game. GameLift FleetIQ -- Use GameLift FleetIQ as a standalone service while hosting your games using EC2 instances and Auto Scaling groups. GameLift FleetIQ provides optimizations for game hosting, including boosting the viability of low-cost Spot Instances gaming. For a complete solution, pair the GameLift FleetIQ and FlexMatch standalone services. GameLift FlexMatch -- Add matchmaking to your game hosting solution. FlexMatch is a customizable matchmaking service for multiplayer games. Use FlexMatch as integrated with GameLift managed hosting or incorporate FlexMatch as a standalone service into your own hosting solution. About this API Reference This reference guide describes the low-level service API for Amazon GameLift. With each topic in this guide, you can find links to language-specific SDK guides and the AWS CLI reference. Useful links: GameLift API operations listed by tasks GameLift tools and resources

Amazon Managed Service for Prometheus

Amazon DocumentDB API documentation

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

Provides APIs for creating and managing Amazon Forecast resources.

Amazon CloudWatch Synthetics You can use Amazon CloudWatch Synthetics to continually monitor your services. You can create and manage canaries, which are modular, lightweight scripts that monitor your endpoints and APIs from the outside-in. You can set up your canaries to run 24 hours a day, once per minute. The canaries help you check the availability and latency of your web services and troubleshoot anomalies by investigating load time data, screenshots of the UI, logs, and metrics. The canaries seamlessly integrate with CloudWatch ServiceLens to help you trace the causes of impacted nodes in your applications. For more information, see Using ServiceLens to Monitor the Health of Your Applications in the Amazon CloudWatch User Guide. Before you create and manage canaries, be aware of the security considerations. For more information, see Security Considerations for Synthetics Canaries.

The Admin Subscriptions Management Client.

The Azure Analysis Services Web API provides a RESTful set of web services that enables users to create, retrieve, update, and delete Analysis Services servers

AWS Data Pipeline configures and manages a data-driven workflow called a pipeline. AWS Data Pipeline handles the details of scheduling and ensuring that data dependencies are met so that your application can focus on processing the data. AWS Data Pipeline provides a JAR implementation of a task runner called AWS Data Pipeline Task Runner. AWS Data Pipeline Task Runner provides logic for common data management scenarios, such as performing database queries and running data analysis using Amazon Elastic MapReduce (Amazon EMR). You can use AWS Data Pipeline Task Runner as your task runner, or you can write your own task runner to provide custom data management. AWS Data Pipeline implements two main sets of functionality. Use the first set to create a pipeline and define data sources, schedules, dependencies, and the transforms to be performed on the data. Use the second set in your task runner application to receive the next task ready for processing. The logic for performing the task, such as querying the data, running data analysis, or converting the data from one format to another, is contained within the task runner. The task runner performs the task assigned to it by the web service, reporting progress to the web service as it does so. When the task is done, the task runner reports the final success or failure of the task to the web service.

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 .