Mock sample for your project: SqlManagementClient API

The Azure management API provides a RESTful set of web services that interact with Azure Key Vault.

Fabric location operation endpoints and objects.

Microsoft Storage Sync Service API

The HDInsight Management Client.

Use these REST APIs for managing OAuth2 servers configuration in your Azure API Management deployment. OAuth 2.0 can be used to authorize developer accounts for Azure API Management. For more information refer to How to OAuth2.

Azure Log Analytics API reference for Query Packs management.

The HDInsight Management Client.

The service for managing third party addons.

Use these REST APIs for getting the network connectivity status of your Azure API Management deployment. When the API Management service is deployed inside a Virtual Network, it needs to have access to other Azure resources it depends on. This also gives details about the DNS Servers visible to Azure API Management deployment.

You can use the Amazon Redshift Data API to run queries on Amazon Redshift tables. You can run SQL statements, which are committed if the statement succeeds. For more information about the Amazon Redshift Data API, see Using the Amazon Redshift Data API in the Amazon Redshift Cluster Management Guide.

Contact Lens for Amazon Connect enables you to analyze conversations between customer and agents, by using speech transcription, natural language processing, and intelligent search capabilities. It performs sentiment analysis, detects issues, and enables you to automatically categorize contacts. Contact Lens for Amazon Connect provides both real-time and post-call analytics of customer-agent conversations. For more information, see Analyze conversations using Contact Lens in the Amazon Connect Administrator Guide.

Software load balancer multiplexer operation endpoints and objects.

Use this REST API to get all the issues across an Azure Api Management service.

Resource health operation endpoints and objects.

The Microsoft Azure management API provides create, read, update, and delete functionality for Azure MySQL resources including servers, databases, firewall rules, VNET rules, security alert policies, log files and configurations with new business model.

The Amazon AppIntegrations service enables you to configure and reuse connections to external applications. For information about how you can use external applications with Amazon Connect, see Set up pre-built integrations in the Amazon Connect Administrator Guide.

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.

The Admin Commerce Management Client.

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.

AWS Auto Scaling Use AWS Auto Scaling to create scaling plans for your applications to automatically scale your scalable AWS resources. API Summary You can use the AWS Auto Scaling service API to accomplish the following tasks: Create and manage scaling plans Define target tracking scaling policies to dynamically scale your resources based on utilization Scale Amazon EC2 Auto Scaling groups using predictive scaling and dynamic scaling to scale your Amazon EC2 capacity faster Set minimum and maximum capacity limits Retrieve information on existing scaling plans Access current forecast data and historical forecast data for up to 56 days previous To learn more about AWS Auto Scaling, including information about granting IAM users required permissions for AWS Auto Scaling actions, see the AWS Auto Scaling User Guide.

Deployment Admin Client.