Mock sample for your project: Amazon Kinesis Video Streams API

The AWS Single Sign-On (SSO) Identity Store service provides a single place to retrieve all of your identities (users and groups). For more information about AWS, see the AWS Single Sign-On User Guide.

AWS Marketplace Metering Service This reference provides descriptions of the low-level AWS Marketplace Metering Service API. AWS Marketplace sellers can use this API to submit usage data for custom usage dimensions. For information on the permissions you need to use this API, see AWS Marketing metering and entitlement API permissions in the AWS Marketplace Seller Guide. Submitting Metering Records MeterUsage - Submits the metering record for a Marketplace product. MeterUsage is called from an EC2 instance or a container running on EKS or ECS. BatchMeterUsage - Submits the metering record for a set of customers. BatchMeterUsage is called from a software-as-a-service (SaaS) application. Accepting New Customers ResolveCustomer - Called by a SaaS application during the registration process. When a buyer visits your website during the registration process, the buyer submits a Registration Token through the browser. The Registration Token is resolved through this API to obtain a CustomerIdentifier and Product Code. Entitlement and Metering for Paid Container Products Paid container software products sold through AWS Marketplace must integrate with the AWS Marketplace Metering Service and call the RegisterUsage operation for software entitlement and metering. Free and BYOL products for Amazon ECS or Amazon EKS aren't required to call RegisterUsage, but you can do so if you want to receive usage data in your seller reports. For more information on using the RegisterUsage operation, see Container-Based Products. BatchMeterUsage API calls are captured by AWS CloudTrail. You can use Cloudtrail to verify that the SaaS metering records that you sent are accurate by searching for records with the eventName of BatchMeterUsage. You can also use CloudTrail to audit records over time. For more information, see the AWS CloudTrail User Guide .

AWS OpsWorks CM AWS OpsWorks for configuration management (CM) is a service that runs and manages configuration management servers. You can use AWS OpsWorks CM to create and manage AWS OpsWorks for Chef Automate and AWS OpsWorks for Puppet Enterprise servers, and add or remove nodes for the servers to manage. Glossary of terms Server : A configuration management server that can be highly-available. The configuration management server runs on an Amazon Elastic Compute Cloud (EC2) instance, and may use various other AWS services, such as Amazon Relational Database Service (RDS) and Elastic Load Balancing. A server is a generic abstraction over the configuration manager that you want to use, much like Amazon RDS. In AWS OpsWorks CM, you do not start or stop servers. After you create servers, they continue to run until they are deleted. Engine : The engine is the specific configuration manager that you want to use. Valid values in this release include ChefAutomate and Puppet. Backup : This is an application-level backup of the data that the configuration manager stores. AWS OpsWorks CM creates an S3 bucket for backups when you launch the first server. A backup maintains a snapshot of a server's configuration-related attributes at the time the backup starts. Events : Events are always related to a server. Events are written during server creation, when health checks run, when backups are created, when system maintenance is performed, etc. When you delete a server, the server's events are also deleted. Account attributes : Every account has attributes that are assigned in the AWS OpsWorks CM database. These attributes store information about configuration limits (servers, backups, etc.) and your customer account. Endpoints AWS OpsWorks CM supports the following endpoints, all HTTPS. You must connect to one of the following endpoints. Your servers can only be accessed or managed within the endpoint in which they are created. opsworks-cm.us-east-1.amazonaws.com opsworks-cm.us-east-2.amazonaws.com opsworks-cm.us-west-1.amazonaws.com opsworks-cm.us-west-2.amazonaws.com opsworks-cm.ap-northeast-1.amazonaws.com opsworks-cm.ap-southeast-1.amazonaws.com opsworks-cm.ap-southeast-2.amazonaws.com opsworks-cm.eu-central-1.amazonaws.com opsworks-cm.eu-west-1.amazonaws.com For more information, see AWS OpsWorks endpoints and quotas in the AWS General Reference. Throttling limits All API operations allow for five requests per second with a burst of 10 requests per second.

Amazon MQ is a managed message broker service for Apache ActiveMQ and RabbitMQ that makes it easy to set up and operate message brokers in the cloud. A message broker allows software applications and components to communicate using various programming languages, operating systems, and formal messaging protocols.

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.

This section provides documentation for the AWS RoboMaker API operations.

AWS Application Discovery Service AWS Application Discovery Service helps you plan application migration projects. It automatically identifies servers, virtual machines (VMs), and network dependencies in your on-premises data centers. For more information, see the AWS Application Discovery Service FAQ. Application Discovery Service offers three ways of performing discovery and collecting data about your on-premises servers: Agentless discovery is recommended for environments that use VMware vCenter Server. This mode doesn't require you to install an agent on each host. It does not work in non-VMware environments. Agentless discovery gathers server information regardless of the operating systems, which minimizes the time required for initial on-premises infrastructure assessment. Agentless discovery doesn't collect information about network dependencies, only agent-based discovery collects that information. Agent-based discovery collects a richer set of data than agentless discovery by using the AWS Application Discovery Agent, which you install on one or more hosts in your data center. The agent captures infrastructure and application information, including an inventory of running processes, system performance information, resource utilization, and network dependencies. The information collected by agents is secured at rest and in transit to the Application Discovery Service database in the cloud. AWS Partner Network (APN) solutions integrate with Application Discovery Service, enabling you to import details of your on-premises environment directly into Migration Hub without using the discovery connector or discovery agent. Third-party application discovery tools can query AWS Application Discovery Service, and they can write to the Application Discovery Service database using the public API. In this way, you can import data into Migration Hub and view it, so that you can associate applications with servers and track migrations. Recommendations We recommend that you use agent-based discovery for non-VMware environments, and whenever you want to collect information about network dependencies. You can run agent-based and agentless discovery simultaneously. Use agentless discovery to complete the initial infrastructure assessment quickly, and then install agents on select hosts to collect additional information. Working With This Guide This API reference provides descriptions, syntax, and usage examples for each of the actions and data types for Application Discovery Service. The topic for each action shows the API request parameters and the response. Alternatively, you can use one of the AWS SDKs to access an API that is tailored to the programming language or platform that you're using. For more information, see AWS SDKs. Remember that you must set your Migration Hub home region before you call any of these APIs. You must make API calls for write actions (create, notify, associate, disassociate, import, or put) while in your home region, or a HomeRegionNotSetException error is returned. API calls for read actions (list, describe, stop, and delete) are permitted outside of your home region. Although it is unlikely, the Migration Hub home region could change. If you call APIs outside the home region, an InvalidInputException is returned. You must call GetHomeRegion to obtain the latest Migration Hub home region. This guide is intended for use with the AWS Application Discovery Service User Guide. All data is handled according to the AWS Privacy Policy. You can operate Application Discovery Service offline to inspect collected data before it is shared with the service.

IoT Greengrass brings local compute, messaging, data management, sync, and ML inference capabilities to edge devices. This enables devices to collect and analyze data closer to the source of information, react autonomously to local events, and communicate securely with each other on local networks. Local devices can also communicate securely with Amazon Web Services IoT Core and export IoT data to the Amazon Web Services Cloud. IoT Greengrass developers can use Lambda functions and components to create and deploy applications to fleets of edge devices for local operation. IoT Greengrass Version 2 provides a new major version of the IoT Greengrass Core software, new APIs, and a new console. Use this API reference to learn how to use the IoT Greengrass V2 API operations to manage components, manage deployments, and core devices. For more information, see What is IoT Greengrass? in the IoT Greengrass V2 Developer Guide.

AWS Outposts is a fully managed service that extends AWS infrastructure, APIs, and tools to customer premises. By providing local access to AWS managed infrastructure, AWS Outposts enables customers to build and run applications on premises using the same programming interfaces as in AWS Regions, while using local compute and storage resources for lower latency and local data processing needs.

Doc Engage API - Amazon Pinpoint API

Amazon CloudSearch Configuration Service You use the Amazon CloudSearch configuration service to create, configure, and manage search domains. Configuration service requests are submitted using the AWS Query protocol. AWS Query requests are HTTP or HTTPS requests submitted via HTTP GET or POST with a query parameter named Action. The endpoint for configuration service requests is region-specific: cloudsearch. region.amazonaws.com. For example, cloudsearch.us-east-1.amazonaws.com. For a current list of supported regions and endpoints, see Regions and Endpoints.

Consumption management client provides access to consumption resources for Azure Enterprise Subscriptions.

The Azure Data Catalog Resource Provider Services API.

The Microsoft Azure management API provides create, read, update, and delete functionality for Azure MariaDB resources including servers, databases, firewall rules, VNET rules, security alert policies, log files, encryption keys, active directory administrator and configurations.

Allows extension of ARM control plane with custom resource providers.

Microsoft Customer Engagement Fabric

These APIs allow end users to operate on Azure Machine Learning Commitment Plans resources and their child Commitment Association resources. They support CRUD operations for commitment plans, get and list operations for commitment associations, moving commitment associations between commitment plans, and retrieving commitment plan usage history.

The HDInsight Management Client.

Subscription client provides an interface to create and manage Azure subscriptions programmatically.

Provides create, read, update and delete functionality Azure SQL server communication links.

The Web Search API lets you send a search query to Bing and get back search results that include links to webpages, images, and more.

Provides create, read, update and delete functionality for Azure SQL Database resources including recommendations and operations.