Mock sample for your project: AWS WAF Regional API

Amazon EMR is a web service that makes it easier to process large amounts of data efficiently. Amazon EMR uses Hadoop processing combined with several Amazon Web Services services to do tasks such as web indexing, data mining, log file analysis, machine learning, scientific simulation, and data warehouse management.

Catalog API actions allow you to manage your entities through list, describe, and update capabilities. An entity can be a product or an offer on AWS Marketplace. You can automate your entity update process by integrating the AWS Marketplace Catalog API with your AWS Marketplace product build or deployment pipelines. You can also create your own applications on top of the Catalog API to manage your products on AWS Marketplace.

Amazon Web Services X-Ray provides APIs for managing debug traces and retrieving service maps and other data created by processing those traces.

Identity and Access Management Identity and Access Management (IAM) is a web service for securely controlling access to Amazon Web Services services. With IAM, you can centrally manage users, security credentials such as access keys, and permissions that control which Amazon Web Services resources users and applications can access. For more information about IAM, see Identity and Access Management (IAM) and the Identity and Access Management User Guide.

An AWS Elemental MediaStore asset is an object, similar to an object in the Amazon S3 service. Objects are the fundamental entities that are stored in AWS Elemental MediaStore.

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 Mobile Service provides mobile app and website developers with capabilities required to configure AWS resources and bootstrap their developer desktop projects with the necessary SDKs, constants, tools and samples to make use of those resources.

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

Describes all of the AWS IoT 1-Click device-related API operations for the service.
Also provides sample requests, responses, and errors for the supported web services
protocols.

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.

Amazon Mechanical Turk API Reference

These APIs allow end users to manage Azure Machine Learning Models, Images, Profiles, and Services.

These APIs allow end users to operate on Azure Machine Learning Workspace resources.

Microsoft NetApp Azure Resource Provider specification

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

The Microsoft Azure Network management API provides a RESTful set of web services that interact with Microsoft Azure Networks service to manage your network resources. The API has entities that capture the relationship between an end user and the Microsoft Azure Networks service.

Amazon S3 Glacier (Glacier) is a storage solution for "cold data." Glacier is an extremely low-cost storage service that provides secure, durable, and easy-to-use storage for data backup and archival. With Glacier, customers can store their data cost effectively for months, years, or decades. Glacier also enables customers to offload the administrative burdens of operating and scaling storage to AWS, so they don't have to worry about capacity planning, hardware provisioning, data replication, hardware failure and recovery, or time-consuming hardware migrations. Glacier is a great storage choice when low storage cost is paramount and your data is rarely retrieved. If your application requires fast or frequent access to your data, consider using Amazon S3. For more information, see Amazon Simple Storage Service (Amazon S3). You can store any kind of data in any format. There is no maximum limit on the total amount of data you can store in Glacier. If you are a first-time user of Glacier, we recommend that you begin by reading the following sections in the Amazon S3 Glacier Developer Guide : What is Amazon S3 Glacier - This section of the Developer Guide describes the underlying data model, the operations it supports, and the AWS SDKs that you can use to interact with the service. Getting Started with Amazon S3 Glacier - The Getting Started section walks you through the process of creating a vault, uploading archives, creating jobs to download archives, retrieving the job output, and deleting archives.

The HDInsight Management Client.

Welcome to the Audit Manager API reference. This guide is for developers who need detailed information about the Audit Manager API operations, data types, and errors. Audit Manager is a service that provides automated evidence collection so that you can continuously audit your Amazon Web Services usage, and assess the effectiveness of your controls to better manage risk and simplify compliance. Audit Manager provides pre-built frameworks that structure and automate assessments for a given compliance standard. Frameworks include a pre-built collection of controls with descriptions and testing procedures, which are grouped according to the requirements of the specified compliance standard or regulation. You can also customize frameworks and controls to support internal audits with unique requirements. Use the following links to get started with the Audit Manager API: Actions : An alphabetical list of all Audit Manager API operations. Data types : An alphabetical list of all Audit Manager data types. Common parameters : Parameters that all Query operations can use. Common errors : Client and server errors that all operations can return. If you're new to Audit Manager, we recommend that you review the Audit Manager User Guide.