Mock sample for your project: GalleryManagementClient API

Update run operation endpoints and objects.

Provides read, delete, and failover functionality for Azure SQL Database replication links.

The Admin Storage Management Client.

Update location operation endpoints and objects.

The HDInsight Management Client.

The Azure Data Catalog Resource Provider Services API.

The Compute Management Client.

These APIs allow end users to operate on Azure Machine Learning Web Services resources. They support the following operations: Create or update a web service Get a web service Patch a web service Delete a web service Get All Web Services in a Resource Group Get All Web Services in a Subscription Get Web Services Keys

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 AWS IoT 1-Click Projects API Reference

The Amazon Braket API Reference provides information about the operations and structures supported in Amazon Braket.

Azure Log Analytics API reference for Query Packs management.

Use these REST APIs for performing operations on logger entity Azure API Management deployment.The Logger entity in API Management represents an event sink that you can use to log API Management events. Currently the Logger entity supports logging API Management events to Azure EventHub.

Use these REST APIs for performing operations on who is going to receive notifications associated with your Azure API Management deployment.

Amazon Honeycode is a fully managed service that allows you to quickly build mobile and web apps for teams—without programming. Build Honeycode apps for managing almost anything, like projects, customers, operations, approvals, resources, and even your team.

An AWS Elemental MediaStore container is a namespace that holds folders and objects. You use a container endpoint to create, read, and delete objects.

AWS Elemental MediaPackage VOD

Amazon Managed Service for Prometheus

Amazon Kinesis Analytics Overview This documentation is for version 1 of the Amazon Kinesis Data Analytics API, which only supports SQL applications. Version 2 of the API supports SQL and Java applications. For more information about version 2, see Amazon Kinesis Data Analytics API V2 Documentation. This is the Amazon Kinesis Analytics v1 API Reference. The Amazon Kinesis Analytics Developer Guide provides additional information.

Role based access control provides you a way to apply granular level policy administration down to individual resources or resource groups. These calls handle provider operations.

This section provides documentation for the Amazon CodeGuru Profiler API operations. Amazon CodeGuru Profiler collects runtime performance data from your live applications, and provides recommendations that can help you fine-tune your application performance. Using machine learning algorithms, CodeGuru Profiler can help you find your most expensive lines of code and suggest ways you can improve efficiency and remove CPU bottlenecks. Amazon CodeGuru Profiler provides different visualizations of profiling data to help you identify what code is running on the CPU, see how much time is consumed, and suggest ways to reduce CPU utilization. Amazon CodeGuru Profiler currently supports applications written in all Java virtual machine (JVM) languages and Python. While CodeGuru Profiler supports both visualizations and recommendations for applications written in Java, it can also generate visualizations and a subset of recommendations for applications written in other JVM languages and Python. For more information, see What is Amazon CodeGuru Profiler in the Amazon CodeGuru Profiler User Guide.