This is the API Reference for Amazon Rekognition Image, Amazon Rekognition Custom Labels, Amazon Rekognition Stored Video, Amazon Rekognition Streaming Video. It provides descriptions of actions, data types, common parameters, and common errors.
Amazon Rekognition Image
Amazon Rekognition Custom Labels
Amazon Rekognition Video Stored Video
Amazon Rekognition Video Streaming Video
Resource Groups lets you organize Amazon Web Services resources such as Amazon Elastic Compute Cloud instances, Amazon Relational Database Service databases, and Amazon Simple Storage Service buckets into groups using criteria that you define as tags. A resource group is a collection of resources that match the resource types specified in a query, and share one or more tags or portions of tags. You can create a group of resources based on their roles in your cloud infrastructure, lifecycle stages, regions, application layers, or virtually any criteria. Resource Groups enable you to automate management tasks, such as those in Amazon Web Services Systems Manager Automation documents, on tag-related resources in Amazon Web Services Systems Manager. Groups of tagged resources also let you quickly view a custom console in Amazon Web Services Systems Manager that shows Config compliance and other monitoring data about member resources.
To create a resource group, build a resource query, and specify tags that identify the criteria that members of the group have in common. Tags are key-value pairs.
For more information about Resource Groups, see the Resource Groups User Guide.
Resource Groups uses a REST-compliant API that you can use to perform the following types of operations.
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Create, Read, Update, and Delete (CRUD) operations on resource groups and resource query entities
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Applying, editing, and removing tags from resource groups
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Resolving resource group member ARNs so they can be returned as search results
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Getting data about resources that are members of a group
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Searching Amazon Web Services resources based on a resource query
This section provides documentation for the AWS RoboMaker API operations.
Amazon Route 53 is a highly available and scalable Domain Name System (DNS) web service.
You can use Route 53 to:
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Register domain names.
For more information, see How domain registration works.
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Route internet traffic to the resources for your domain
For more information, see How internet traffic is routed to your website or web application.
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Check the health of your resources.
For more information, see How Route 53 checks the health of your resources.
Amazon Route 53 API actions let you register domain names and perform related operations.
When you create a VPC using Amazon VPC, you automatically get DNS resolution within the VPC from Route 53 Resolver. By default, Resolver answers DNS queries for VPC domain names such as domain names for EC2 instances or Elastic Load Balancing load balancers. Resolver performs recursive lookups against public name servers for all other domain names.
You can also configure DNS resolution between your VPC and your network over a Direct Connect or VPN connection:
Forward DNS queries from resolvers on your network to Route 53 Resolver
DNS resolvers on your network can forward DNS queries to Resolver in a specified VPC. This allows your DNS resolvers to easily resolve domain names for Amazon Web Services resources such as EC2 instances or records in a Route 53 private hosted zone. For more information, see How DNS Resolvers on Your Network Forward DNS Queries to Route 53 Resolver in the Amazon Route 53 Developer Guide.
Conditionally forward queries from a VPC to resolvers on your network
You can configure Resolver to forward queries that it receives from EC2 instances in your VPCs to DNS resolvers on your network. To forward selected queries, you create Resolver rules that specify the domain names for the DNS queries that you want to forward (such as example.com), and the IP addresses of the DNS resolvers on your network that you want to forward the queries to. If a query matches multiple rules (example.com, acme.example.com), Resolver chooses the rule with the most specific match (acme.example.com) and forwards the query to the IP addresses that you specified in that rule. For more information, see How Route 53 Resolver Forwards DNS Queries from Your VPCs to Your Network in the Amazon Route 53 Developer Guide.
Like Amazon VPC, Resolver is Regional. In each Region where you have VPCs, you can choose whether to forward queries from your VPCs to your network (outbound queries), from your network to your VPCs (inbound queries), or both.
Amazon Lex provides both build and runtime endpoints. Each endpoint provides a set of operations (API). Your conversational bot uses the runtime API to understand user utterances (user input text or voice). For example, suppose a user says "I want pizza", your bot sends this input to Amazon Lex using the runtime API. Amazon Lex recognizes that the user request is for the OrderPizza intent (one of the intents defined in the bot). Then Amazon Lex engages in user conversation on behalf of the bot to elicit required information (slot values, such as pizza size and crust type), and then performs fulfillment activity (that you configured when you created the bot). You use the build-time API to create and manage your Amazon Lex bot. For a list of build-time operations, see the build-time API, .
This section contains documentation for the Amazon Lex V2 Runtime V2 API operations.
The Amazon SageMaker runtime API.
Amazon Web Services S3 Control provides access to Amazon S3 control plane actions.
Amazon S3 on Outposts provides access to S3 on Outposts operations.
Provides APIs for creating and managing SageMaker resources.
Other Resources:
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:
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Start a human loop with the
StartHumanLoopoperation 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.
SageMaker Edge Manager dataplane service for communicating with active agents.
Contains all data plane API operations and data types for the Amazon SageMaker Feature Store. Use this API to put, delete, and retrieve (get) features from a feature store.
Use the following operations to configure your OnlineStore and OfflineStore features, and to create and manage feature groups:
Savings Plans are a pricing model that offer significant savings on AWS usage (for example, on Amazon EC2 instances). You commit to a consistent amount of usage, in USD per hour, for a term of 1 or 3 years, and receive a lower price for that usage. For more information, see the AWS Savings Plans User Guide.
Amazon EventBridge Schema Registry
Amazon SimpleDB is a web service providing the core database functions of data indexing and querying in the cloud. By offloading the time and effort associated with building and operating a web-scale database, SimpleDB provides developers the freedom to focus on application development.
A traditional, clustered relational database requires a sizable upfront capital outlay, is complex to design, and often requires extensive and repetitive database administration. Amazon SimpleDB is dramatically simpler, requiring no schema, automatically indexing your data and providing a simple API for storage and access. This approach eliminates the administrative burden of data modeling, index maintenance, and performance tuning. Developers gain access to this functionality within Amazon's proven computing environment, are able to scale instantly, and pay only for what they use.
Visit http://aws.amazon.com/simpledb/ for more information.