Mock sample for your project: Amazon Elastic Container Registry Public API

Amazon ElastiCache Amazon ElastiCache is a web service that makes it easier to set up, operate, and scale a distributed cache in the cloud. With ElastiCache, customers get all of the benefits of a high-performance, in-memory cache with less of the administrative burden involved in launching and managing a distributed cache. The service makes setup, scaling, and cluster failure handling much simpler than in a self-managed cache deployment. In addition, through integration with Amazon CloudWatch, customers get enhanced visibility into the key performance statistics associated with their cache and can receive alarms if a part of their cache runs hot.

AWS CodeStar Connections This AWS CodeStar Connections API Reference provides descriptions and usage examples of the operations and data types for the AWS CodeStar Connections API. You can use the connections API to work with connections and installations. Connections are configurations that you use to connect AWS resources to external code repositories. Each connection is a resource that can be given to services such as CodePipeline to connect to a third-party repository such as Bitbucket. For example, you can add the connection in CodePipeline so that it triggers your pipeline when a code change is made to your third-party code repository. Each connection is named and associated with a unique ARN that is used to reference the connection. When you create a connection, the console initiates a third-party connection handshake. Installations are the apps that are used to conduct this handshake. For example, the installation for the Bitbucket provider type is the Bitbucket app. When you create a connection, you can choose an existing installation or create one. When you want to create a connection to an installed provider type such as GitHub Enterprise Server, you create a host for your connections. You can work with connections by calling: CreateConnection, which creates a uniquely named connection that can be referenced by services such as CodePipeline. DeleteConnection, which deletes the specified connection. GetConnection, which returns information about the connection, including the connection status. ListConnections, which lists the connections associated with your account. You can work with hosts by calling: CreateHost, which creates a host that represents the infrastructure where your provider is installed. DeleteHost, which deletes the specified host. GetHost, which returns information about the host, including the setup status. ListHosts, which lists the hosts associated with your account. You can work with tags in AWS CodeStar Connections by calling the following: ListTagsForResource, which gets information about AWS tags for a specified Amazon Resource Name (ARN) in AWS CodeStar Connections. TagResource, which adds or updates tags for a resource in AWS CodeStar Connections. UntagResource, which removes tags for a resource in AWS CodeStar Connections. For information about how to use AWS CodeStar Connections, see the Developer Tools User Guide.

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 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.

AWS Import/Export Service AWS Import/Export accelerates transferring large amounts of data between the AWS cloud and portable storage devices that you mail to us. AWS Import/Export transfers data directly onto and off of your storage devices using Amazon's high-speed internal network and bypassing the Internet. For large data sets, AWS Import/Export is often faster than Internet transfer and more cost effective than upgrading your connectivity.

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.

AWS IoT Greengrass seamlessly extends AWS onto physical devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage. AWS IoT Greengrass ensures your devices can respond quickly to local events and operate with intermittent connectivity. AWS IoT Greengrass minimizes the cost of transmitting data to the cloud by allowing you to author AWS Lambda functions that execute locally.

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.

Provides APIs for creating and managing Amazon Forecast resources.

AWS Elemental MediaConvert

Amazon Kinesis Data Streams Service API Reference Amazon Kinesis Data Streams is a managed service that scales elastically for real-time processing of streaming big data.

Kinesis Video Streams Signaling Service is a intermediate service that establishes a communication channel for discovering peers, transmitting offers and answers in order to establish peer-to-peer connection in webRTC technology.

Amazon WorkLink is a cloud-based service that provides secure access to internal websites and web apps from iOS and Android phones. In a single step, your users, such as employees, can access internal websites as efficiently as they access any other public website. They enter a URL in their web browser, or choose a link to an internal website in an email. Amazon WorkLink authenticates the user's access and securely renders authorized internal web content in a secure rendering service in the AWS cloud. Amazon WorkLink doesn't download or store any internal web content on mobile devices.

Resource provider health operation endpoints and objects.

REST API for Azure Spring Cloud

The Admin Commerce Management Client.

The Admin Subscriptions Management Client.

This is AWS WAF Classic documentation. For more information, see AWS WAF Classic in the developer guide. For the latest version of AWS WAF, use the AWS WAFV2 API and see the AWS WAF Developer Guide. With the latest version, AWS WAF has a single set of endpoints for regional and global use. This is the AWS WAF Classic API Reference for using AWS WAF Classic with Amazon CloudFront. The AWS WAF Classic actions and data types listed in the reference are available for protecting Amazon CloudFront distributions. You can use these actions and data types via the endpoint waf.amazonaws.com. This guide is for developers who need detailed information about the AWS WAF Classic API actions, data types, and errors. For detailed information about AWS WAF Classic features and an overview of how to use the AWS WAF Classic API, see the AWS WAF Classic in the developer guide.

Deployment Admin Client.

Deployment Admin Client.

Azure Application Insights client for selecting pricing plans and options.