Mock sample for your project: AWS IoT Data Plane API

Doc Engage API - Amazon Pinpoint API

The AWS Migration Hub API methods help to obtain server and application migration status and integrate your resource-specific migration tool by providing a programmatic interface to Migration Hub. Remember that you must set your AWS Migration Hub home region before you call any of these APIs, or a HomeRegionNotSetException error will be returned. Also, you must make the API calls while in your home region.

AWS Fault Injection Simulator is a managed service that enables you to perform fault injection experiments on your AWS workloads. For more information, see the AWS Fault Injection Simulator User Guide.

Amazon Comprehend is an AWS service for gaining insight into the content of documents. Use these actions to determine the topics contained in your documents, the topics they discuss, the predominant sentiment expressed in them, the predominant language used, and more.

The Amazon Chime API (application programming interface) is designed for developers to perform key tasks, such as creating and managing Amazon Chime accounts, users, and Voice Connectors. This guide provides detailed information about the Amazon Chime API, including operations, types, inputs and outputs, and error codes. It also includes some server-side API actions to use with the Amazon Chime SDK. For more information about the Amazon Chime SDK, see Using the Amazon Chime SDK in the Amazon Chime Developer Guide. You can use an AWS SDK, the AWS Command Line Interface (AWS CLI), or the REST API to make API calls. We recommend using an AWS SDK or the AWS CLI. Each API operation includes links to information about using it with a language-specific AWS SDK or the AWS CLI. Using an AWS SDK You don't need to write code to calculate a signature for request authentication. The SDK clients authenticate your requests by using access keys that you provide. For more information about AWS SDKs, see the AWS Developer Center. Using the AWS CLI Use your access keys with the AWS CLI to make API calls. For information about setting up the AWS CLI, see Installing the AWS Command Line Interface in the AWS Command Line Interface User Guide. For a list of available Amazon Chime commands, see the Amazon Chime commands in the AWS CLI Command Reference. Using REST APIs If you use REST to make API calls, you must authenticate your request by providing a signature. Amazon Chime supports signature version 4. For more information, see Signature Version 4 Signing Process in the Amazon Web Services General Reference. When making REST API calls, use the service name chime and REST endpoint https://service.chime.aws.amazon.com. Administrative permissions are controlled using AWS Identity and Access Management (IAM). For more information, see Identity and Access Management for Amazon Chime in the Amazon Chime Administration Guide.

Batch Using Batch, you can run batch computing workloads on the Cloud. Batch computing is a common means for developers, scientists, and engineers to access large amounts of compute resources. Batch uses the advantages of this computing workload to remove the undifferentiated heavy lifting of configuring and managing required infrastructure. At the same time, it also adopts a familiar batch computing software approach. Given these advantages, Batch can help you to efficiently provision resources in response to jobs submitted, thus effectively helping you to eliminate capacity constraints, reduce compute costs, and deliver your results more quickly. As a fully managed service, Batch can run batch computing workloads of any scale. Batch automatically provisions compute resources and optimizes workload distribution based on the quantity and scale of your specific workloads. With Batch, there's no need to install or manage batch computing software. This means that you can focus your time and energy on analyzing results and solving your specific problems.

App Mesh is a service mesh based on the Envoy proxy that makes it easy to monitor and control microservices. App Mesh standardizes how your microservices communicate, giving you end-to-end visibility and helping to ensure high availability for your applications. App Mesh gives you consistent visibility and network traffic controls for every microservice in an application. You can use App Mesh with Amazon Web Services Fargate, Amazon ECS, Amazon EKS, Kubernetes on Amazon Web Services, and Amazon EC2. App Mesh supports microservice applications that use service discovery naming for their components. For more information about service discovery on Amazon ECS, see Service Discovery in the Amazon Elastic Container Service Developer Guide. Kubernetes kube-dns and coredns are supported. For more information, see DNS for Services and Pods in the Kubernetes documentation.

You can use the Cost Explorer API to programmatically query your cost and usage data. You can query for aggregated data such as total monthly costs or total daily usage. You can also query for granular data. This might include the number of daily write operations for Amazon DynamoDB database tables in your production environment. Service Endpoint The Cost Explorer API provides the following endpoint: https://ce.us-east-1.amazonaws.com For information about the costs that are associated with the Cost Explorer API, see Amazon Web Services Cost Management Pricing.

Alexa for Business helps you use Alexa in your organization. Alexa for Business provides you with the tools to manage Alexa devices, enroll your users, and assign skills, at scale. You can build your own context-aware voice skills using the Alexa Skills Kit and the Alexa for Business API operations. You can also make these available as private skills for your organization. Alexa for Business makes it efficient to voice-enable your products and services, thus providing context-aware voice experiences for your customers. Device makers building with the Alexa Voice Service (AVS) can create fully integrated solutions, register their products with Alexa for Business, and manage them as shared devices in their organization.

Amazon Cloud Directory Amazon Cloud Directory is a component of the AWS Directory Service that simplifies the development and management of cloud-scale web, mobile, and IoT applications. This guide describes the Cloud Directory operations that you can call programmatically and includes detailed information on data types and errors. For information about Cloud Directory features, see AWS Directory Service and the Amazon Cloud Directory Developer Guide.

AWS CodeStar This is the API reference for AWS CodeStar. This reference provides descriptions of the operations and data types for the AWS CodeStar API along with usage examples. You can use the AWS CodeStar API to work with: Projects and their resources, by calling the following: DeleteProject, which deletes a project. DescribeProject, which lists the attributes of a project. ListProjects, which lists all projects associated with your AWS account. ListResources, which lists the resources associated with a project. ListTagsForProject, which lists the tags associated with a project. TagProject, which adds tags to a project. UntagProject, which removes tags from a project. UpdateProject, which updates the attributes of a project. Teams and team members, by calling the following: AssociateTeamMember, which adds an IAM user to the team for a project. DisassociateTeamMember, which removes an IAM user from the team for a project. ListTeamMembers, which lists all the IAM users in the team for a project, including their roles and attributes. UpdateTeamMember, which updates a team member's attributes in a project. Users, by calling the following: CreateUserProfile, which creates a user profile that contains data associated with the user across all projects. DeleteUserProfile, which deletes all user profile information across all projects. DescribeUserProfile, which describes the profile of a user. ListUserProfiles, which lists all user profiles. UpdateUserProfile, which updates the profile for a user.

This section provides documentation for the Amazon CodeGuru Reviewer API operations. CodeGuru Reviewer is a service that uses program analysis and machine learning to detect potential defects that are difficult for developers to find and recommends fixes in your Java and Python code. By proactively detecting and providing recommendations for addressing code defects and implementing best practices, CodeGuru Reviewer improves the overall quality and maintainability of your code base during the code review stage. For more information about CodeGuru Reviewer, see the Amazon CodeGuru Reviewer User Guide. To improve the security of your CodeGuru Reviewer API calls, you can establish a private connection between your VPC and CodeGuru Reviewer by creating an interface VPC endpoint. For more information, see CodeGuru Reviewer and interface VPC endpoints (Amazon Web Services PrivateLink) in the Amazon CodeGuru Reviewer User Guide.

Amazon EMR on EKS provides a deployment option for Amazon EMR that allows you to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). With this deployment option, you can focus on running analytics workloads while Amazon EMR on EKS builds, configures, and manages containers for open-source applications. For more information about Amazon EMR on EKS concepts and tasks, see What is Amazon EMR on EKS. Amazon EMR containers is the API name for Amazon EMR on EKS. The emr-containers prefix is used in the following scenarios: It is the prefix in the CLI commands for Amazon EMR on EKS. For example, aws emr-containers start-job-run. It is the prefix before IAM policy actions for Amazon EMR on EKS. For example,"Action": [ "emr-containers:StartJobRun"]. For more information, see Policy actions for Amazon EMR on EKS. It is the prefix used in Amazon EMR on EKS service endpoints. For example, emr-containers.us-east-2.amazonaws.com. For more information, see Amazon EMR on EKS Service Endpoints.

A client for issuing REST requests to the Azure Batch service.

Amazon Comprehend is an AWS service for gaining insight into the content of documents. Use these actions to determine the topics contained in your documents, the topics they discuss, the predominant sentiment expressed in them, the predominant language used, and more.

The AWS IoT 1-Click Projects API Reference

REST APIs for Azure Advisor

Recovery Control Configuration API Reference for Amazon Route 53 Application Recovery Controller

Amazon Augmented AI (Amazon A2I) adds the benefit of human judgment to any machine learning application. When an AI application can't evaluate data with a high degree of confidence, human reviewers can take over. This human review is called a human review workflow. To create and start a human review workflow, you need three resources: a worker task template, a flow definition, and a human loop. For information about these resources and prerequisites for using Amazon A2I, see Get Started with Amazon Augmented AI in the Amazon SageMaker Developer Guide. This API reference includes information about API actions and data types that you can use to interact with Amazon A2I programmatically. Use this guide to: Start a human loop with the StartHumanLoop operation when using Amazon A2I with a custom task type. To learn more about the difference between custom and built-in task types, see Use Task Types. To learn how to start a human loop using this API, see Create and Start a Human Loop for a Custom Task Type in the Amazon SageMaker Developer Guide. Manage your human loops. You can list all human loops that you have created, describe individual human loops, and stop and delete human loops. To learn more, see Monitor and Manage Your Human Loop in the Amazon SageMaker Developer Guide. Amazon A2I integrates APIs from various AWS services to create and start human review workflows for those services. To learn how Amazon A2I uses these APIs, see Use APIs in Amazon A2I in the Amazon SageMaker Developer Guide.

Amazon Lightsail is the easiest way to get started with Amazon Web Services (AWS) for developers who need to build websites or web applications. It includes everything you need to launch your project quickly - instances (virtual private servers), container services, storage buckets, managed databases, SSD-based block storage, static IP addresses, load balancers, content delivery network (CDN) distributions, DNS management of registered domains, and resource snapshots (backups) - for a low, predictable monthly price. You can manage your Lightsail resources using the Lightsail console, Lightsail API, AWS Command Line Interface (AWS CLI), or SDKs. For more information about Lightsail concepts and tasks, see the Amazon Lightsail Developer Guide. This API Reference provides detailed information about the actions, data types, parameters, and errors of the Lightsail service. For more information about the supported AWS Regions, endpoints, and service quotas of the Lightsail service, see Amazon Lightsail Endpoints and Quotas in the AWS General Reference.

Amazon Textract detects and analyzes text in documents and converts it into machine-readable text. This is the API reference documentation for Amazon Textract.

Operations and objects for transcribing speech to text.

AWS Amplify Admin API

Cloud Map With Cloud Map, you can configure public DNS, private DNS, or HTTP namespaces that your microservice applications run in. When an instance becomes available, you can call the Cloud Map API to register the instance with Cloud Map. For public or private DNS namespaces, Cloud Map automatically creates DNS records and an optional health check. Clients that submit public or private DNS queries, or HTTP requests, for the service receive an answer that contains up to eight healthy records.