Mock sample for your project: SqlManagementClient API

Assess your workloads for Azure.

Azure Blueprints Client provides access to blueprint definitions, assignments, and artifacts, and related blueprint operations.

Use these REST APIs for performing operations on Backend entity in Azure API Management deployment. The Backend entity in API Management represents a backend service that is configured to skip certification chain validation when using a self-signed certificate to test mutual certificate authentication.

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

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.

Use these REST APIs for performing operations on the ApiVersionSet entity associated with your Azure API Management deployment. Using this entity you create and manage API Version Sets that are used to group APIs for consistent versioning.

Azure Log Analytics API reference for management of saved Queries within Query Packs.

ARM Databricks

Dev Spaces REST API

Fabric location operation endpoints and objects.

Amazon WorkMail is a secure, managed business email and calendaring service with support for existing desktop and mobile email clients. You can access your email, contacts, and calendars using Microsoft Outlook, your browser, or other native iOS and Android email applications. You can integrate WorkMail with your existing corporate directory and control both the keys that encrypt your data and the location in which your data is stored. The WorkMail API is designed for the following scenarios: Listing and describing organizations Managing users Managing groups Managing resources All WorkMail API operations are Amazon-authenticated and certificate-signed. They not only require the use of the AWS SDK, but also allow for the exclusive use of AWS Identity and Access Management users and roles to help facilitate access, trust, and permission policies. By creating a role and allowing an IAM user to access the WorkMail site, the IAM user gains full administrative visibility into the entire WorkMail organization (or as set in the IAM policy). This includes, but is not limited to, the ability to create, update, and delete users, groups, and resources. This allows developers to perform the scenarios listed above, as well as give users the ability to grant access on a selective basis using the IAM model.

The Compute Management Client.

Definition of the public APIs exposed by Amazon Machine Learning

Provides APIs for creating and managing Amazon Forecast resources.

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.

The Amazon API Gateway Management API allows you to directly manage runtime aspects of your deployed APIs. To use it, you must explicitly set the SDK's endpoint to point to the endpoint of your deployed API. The endpoint will be of the form https://{api-id}.execute-api.{region}.amazonaws.com/{stage}, or will be the endpoint corresponding to your API's custom domain and base path, if applicable.

This is the Resource Access Manager API Reference. This documentation provides descriptions and syntax for each of the actions and data types in RAM. RAM is a service that helps you securely share your Amazon Web Services resources across Amazon Web Services accounts and within your organization or organizational units (OUs) in Organizations. For supported resource types, you can also share resources with IAM roles and IAM users. If you have multiple Amazon Web Services accounts, you can use RAM to share those resources with other accounts. To learn more about RAM, see the following resources: Resource Access Manager product page Resource Access Manager User Guide

IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight. Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources. IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.

The FinSpace management service provides the APIs for managing the FinSpace environments.

Amazon Athena is an interactive query service that lets you use standard SQL to analyze data directly in Amazon S3. You can point Athena at your data in Amazon S3 and run ad-hoc queries and get results in seconds. Athena is serverless, so there is no infrastructure to set up or manage. You pay only for the queries you run. Athena scales automatically—executing queries in parallel—so results are fast, even with large datasets and complex queries. For more information, see What is Amazon Athena in the Amazon Athena User Guide. If you connect to Athena using the JDBC driver, use version 1.1.0 of the driver or later with the Amazon Athena API. Earlier version drivers do not support the API. For more information and to download the driver, see Accessing Amazon Athena with JDBC. For code samples using the Amazon Web Services SDK for Java, see Examples and Code Samples in the Amazon Athena User Guide.

This is the Amazon Rekognition API reference.

Amazon Data Lifecycle Manager With Amazon Data Lifecycle Manager, you can manage the lifecycle of your Amazon Web Services resources. You create lifecycle policies, which are used to automate operations on the specified resources. Amazon DLM supports Amazon EBS volumes and snapshots. For information about using Amazon DLM with Amazon EBS, see Automating the Amazon EBS Snapshot Lifecycle in the Amazon EC2 User Guide.