Mock sample for your project: Amazon Kinesis API

AWS Well-Architected Tool This is the AWS Well-Architected Tool API Reference. The AWS Well-Architected Tool API provides programmatic access to the AWS Well-Architected Tool in the AWS Management Console. For information about the AWS Well-Architected Tool, see the AWS Well-Architected Tool User Guide.

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.

This is the AWS Proton Service API Reference. It provides descriptions, syntax and usage examples for each of the actions and data types for the AWS Proton service. The documentation for each action shows the Query API request parameters and the XML response. Alternatively, you can use the AWS CLI to access an API. For more information, see the AWS Command Line Interface User Guide. The AWS Proton service is a two-pronged automation framework. Administrators create service templates to provide standardized infrastructure and deployment tooling for serverless and container based applications. Developers, in turn, select from the available service templates to automate their application or service deployments. Because administrators define the infrastructure and tooling that AWS Proton deploys and manages, they need permissions to use all of the listed API operations. When developers select a specific infrastructure and tooling set, AWS Proton deploys their applications. To monitor their applications that are running on AWS Proton, developers need permissions to the service create, list, update and delete API operations and the service instance list and update API operations. To learn more about AWS Proton administration, see the AWS Proton Administrator Guide. To learn more about deploying serverless and containerized applications on AWS Proton, see the AWS Proton User Guide. Ensuring Idempotency When you make a mutating API request, the request typically returns a result before the asynchronous workflows of the operation are complete. Operations might also time out or encounter other server issues before they're complete, even if the request already returned a result. This might make it difficult to determine whether the request succeeded. Moreover, you might need to retry the request multiple times to ensure that the operation completes successfully. However, if the original request and the subsequent retries are successful, the operation occurs multiple times. This means that you might create more resources than you intended. Idempotency ensures that an API request action completes no more than one time. With an idempotent request, if the original request action completes successfully, any subsequent retries complete successfully without performing any further actions. However, the result might contain updated information, such as the current creation status. The following lists of APIs are grouped according to methods that ensure idempotency. Idempotent create APIs with a client token The API actions in this list support idempotency with the use of a client token. The corresponding AWS CLI commands also support idempotency using a client token. A client token is a unique, case-sensitive string of up to 64 ASCII characters. To make an idempotent API request using one of these actions, specify a client token in the request. We recommend that you don't reuse the same client token for other API requests. If you don’t provide a client token for these APIs, a default client token is automatically provided by SDKs. Given a request action that has succeeded: If you retry the request using the same client token and the same parameters, the retry succeeds without performing any further actions other than returning the original resource detail data in the response. If you retry the request using the same client token, but one or more of the parameters are different, the retry throws a ValidationException with an IdempotentParameterMismatch error. Client tokens expire eight hours after a request is made. If you retry the request with the expired token, a new resource is created. If the original resource is deleted and you retry the request, a new resource is created. Idempotent create APIs with a client token: CreateEnvironmentTemplateVersion CreateServiceTemplateVersion CreateEnvironmentAccountConnection Idempotent create APIs Given a request action that has succeeded: If you retry the request with an API from this group, and the original resource hasn't been modified, the retry succeeds without performing any further actions other than returning the original resource detail data in the response. If the original resource has been modified, the retry throws a ConflictException. If you retry with different input parameters, the retry throws a ValidationException with an IdempotentParameterMismatch error. Idempotent create APIs: CreateEnvironmentTemplate CreateServiceTemplate CreateEnvironment CreateService Idempotent delete APIs Given a request action that has succeeded: When you retry the request with an API from this group and the resource was deleted, its metadata is returned in the response. If you retry and the resource doesn't exist, the response is empty. In both cases, the retry succeeds. Idempotent delete APIs: DeleteEnvironmentTemplate DeleteEnvironmentTemplateVersion DeleteServiceTemplate DeleteServiceTemplateVersion DeleteEnvironmentAccountConnection Asynchronous idempotent delete APIs Given a request action that has succeeded: If you retry the request with an API from this group, if the original request delete operation status is DELETEINPROGRESS, the retry returns the resource detail data in the response without performing any further actions. If the original request delete operation is complete, a retry returns an empty response. Asynchronous idempotent delete APIs: DeleteEnvironment DeleteService

Amazon Personalize can consume real-time user event data, such as stream or click data, and use it for model training either alone or combined with historical data. For more information see Recording Events.

Amazon Mechanical Turk API Reference

Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide. Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).

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

Amazon Neptune Amazon Neptune is a fast, reliable, fully-managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. This interface reference for Amazon Neptune contains documentation for a programming or command line interface you can use to manage Amazon Neptune. Note that Amazon Neptune is asynchronous, which means that some interfaces might require techniques such as polling or callback functions to determine when a command has been applied. In this reference, the parameter descriptions indicate whether a command is applied immediately, on the next instance reboot, or during the maintenance window. The reference structure is as follows, and we list following some related topics from the user guide.

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.

Amazon Macie Classic Amazon Macie Classic is a security service that uses machine learning to automatically discover, classify, and protect sensitive data in AWS. Macie Classic recognizes sensitive data such as personally identifiable information (PII) or intellectual property, and provides you with dashboards and alerts that give visibility into how this data is being accessed or moved. For more information, see the Amazon Macie Classic User Guide.

Amazon Kinesis Analytics Overview This documentation is for version 1 of the Amazon Kinesis Data Analytics API, which only supports SQL applications. Version 2 of the API supports SQL and Java applications. For more information about version 2, see Amazon Kinesis Data Analytics API V2 Documentation. This is the Amazon Kinesis Analytics v1 API Reference. The Amazon Kinesis Analytics Developer Guide provides additional information.

Use these REST APIs for performing operations on OpenId Connect Provider entity associated with your Azure API Management deployment. API Management allows you to access APIs secured with token from OpenID Connect Provider to be accessed from the Developer Console.

These APIs allow end users to operate on Azure Machine Learning Team Account resources. They support CRUD operations for Azure Machine Learning Team Accounts.

Provides create, read and update functionality for database Threat Detection policies.

Azure Digital Twins Client for managing DigitalTwinsInstance

Use these APIs to manage Azure CDN resources through the Azure Resource Manager. You must make sure that requests made to these resources are secure.

The DevTest Labs Client.

Specification for ManagedServices.

The Azure Instance Metadata Client

Microsoft Customer Engagement Fabric

The HDInsight Management Client.