Mock sample for your project: Amazon Athena API

Amazon Managed Blockchain is a fully managed service for creating and managing blockchain networks using open-source frameworks. Blockchain allows you to build applications where multiple parties can securely and transparently run transactions and share data without the need for a trusted, central authority. Managed Blockchain supports the Hyperledger Fabric and Ethereum open-source frameworks. Because of fundamental differences between the frameworks, some API actions or data types may only apply in the context of one framework and not the other. For example, actions related to Hyperledger Fabric network members such as CreateMember and DeleteMember do not apply to Ethereum. The description for each action indicates the framework or frameworks to which it applies. Data types and properties that apply only in the context of a particular framework are similarly indicated.

Storage Gateway Service Storage Gateway is the service that connects an on-premises software appliance with cloud-based storage to provide seamless and secure integration between an organization's on-premises IT environment and the Amazon Web Services storage infrastructure. The service enables you to securely upload data to the Cloud for cost effective backup and rapid disaster recovery. Use the following links to get started using the Storage Gateway Service API Reference : Storage Gateway required request headers : Describes the required headers that you must send with every POST request to Storage Gateway. Signing requests : Storage Gateway requires that you authenticate every request you send; this topic describes how sign such a request. Error responses : Provides reference information about Storage Gateway errors. Operations in Storage Gateway : Contains detailed descriptions of all Storage Gateway operations, their request parameters, response elements, possible errors, and examples of requests and responses. Storage Gateway endpoints and quotas : Provides a list of each Region and the endpoints available for use with Storage Gateway. Storage Gateway resource IDs are in uppercase. When you use these resource IDs with the Amazon EC2 API, EC2 expects resource IDs in lowercase. You must change your resource ID to lowercase to use it with the EC2 API. For example, in Storage Gateway the ID for a volume might be vol-AA22BB012345DAF670. When you use this ID with the EC2 API, you must change it to vol-aa22bb012345daf670. Otherwise, the EC2 API might not behave as expected. IDs for Storage Gateway volumes and Amazon EBS snapshots created from gateway volumes are changing to a longer format. Starting in December 2016, all new volumes and snapshots will be created with a 17-character string. Starting in April 2016, you will be able to use these longer IDs so you can test your systems with the new format. For more information, see Longer EC2 and EBS resource IDs. For example, a volume Amazon Resource Name (ARN) with the longer volume ID format looks like the following: arn:aws:storagegateway:us-west-2:111122223333:gateway/sgw-12A3456B/volume/vol-1122AABBCCDDEEFFG. A snapshot ID with the longer ID format looks like the following: snap-78e226633445566ee. For more information, see Announcement: Heads-up – Longer Storage Gateway volume and snapshot IDs coming in 2016.

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, .

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 Web Services S3 Control provides access to Amazon S3 control plane actions.

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 Kinesis Data Analytics is a fully managed service that you can use to process and analyze streaming data using Java, SQL, or Scala. The service enables you to quickly author and run Java, SQL, or Scala code against streaming sources to perform time series analytics, feed real-time dashboards, and create real-time metrics.

Amazon Lex Build-Time Actions Amazon Lex is an AWS service for building conversational voice and text interfaces. Use these actions to create, update, and delete conversational bots for new and existing client applications.

API for AWS Elemental MediaConnect

AWS Step Functions AWS Step Functions is a service that lets you coordinate the components of distributed applications and microservices using visual workflows. You can use Step Functions to build applications from individual components, each of which performs a discrete function, or task, allowing you to scale and change applications quickly. Step Functions provides a console that helps visualize the components of your application as a series of steps. Step Functions automatically triggers and tracks each step, and retries steps when there are errors, so your application executes predictably and in the right order every time. Step Functions logs the state of each step, so you can quickly diagnose and debug any issues. Step Functions manages operations and underlying infrastructure to ensure your application is available at any scale. You can run tasks on AWS, your own servers, or any system that has access to AWS. You can access and use Step Functions using the console, the AWS SDKs, or an HTTP API. For more information about Step Functions, see the AWS Step Functions Developer Guide .

Amazon Kinesis Data Firehose API Reference Amazon Kinesis Data Firehose is a fully managed service that delivers real-time streaming data to destinations such as Amazon Simple Storage Service (Amazon S3), Amazon Elasticsearch Service (Amazon ES), Amazon Redshift, and Splunk.

Amazon Web Services Snow Device Management documentation.

You use the API to scan your content as it is generated. Content Moderator then processes your content and sends the results along with relevant information either back to your systems or to the built-in review tool. You can use this information to take decisions e.g. take it down, send to human judge, etc.
When using the API, images need to have a minimum of 128 pixels and a maximum file size of 4MB.
Text can be at most 1024 characters long.
If the content passed to the text API or the image API exceeds the size limits, the API will return an error code that informs about the issue.

AWS Global Accelerator This is the AWS Global Accelerator API Reference. This guide is for developers who need detailed information about AWS Global Accelerator API actions, data types, and errors. For more information about Global Accelerator features, see the AWS Global Accelerator Developer Guide. AWS Global Accelerator is a service in which you create accelerators to improve the performance of your applications for local and global users. Depending on the type of accelerator you choose, you can gain additional benefits. By using a standard accelerator, you can improve availability of your internet applications that are used by a global audience. With a standard accelerator, Global Accelerator directs traffic to optimal endpoints over the AWS global network. For other scenarios, you might choose a custom routing accelerator. With a custom routing accelerator, you can use application logic to directly map one or more users to a specific endpoint among many endpoints. Global Accelerator is a global service that supports endpoints in multiple AWS Regions but you must specify the US West (Oregon) Region to create or update accelerators. By default, Global Accelerator provides you with two static IP addresses that you associate with your accelerator. With a standard accelerator, instead of using the IP addresses that Global Accelerator provides, you can configure these entry points to be IPv4 addresses from your own IP address ranges that you bring to Global Accelerator. The static IP addresses are anycast from the AWS edge network. For a standard accelerator, they distribute incoming application traffic across multiple endpoint resources in multiple AWS Regions, which increases the availability of your applications. Endpoints for standard accelerators can be Network Load Balancers, Application Load Balancers, Amazon EC2 instances, or Elastic IP addresses that are located in one AWS Region or multiple Regions. For custom routing accelerators, you map traffic that arrives to the static IP addresses to specific Amazon EC2 servers in endpoints that are virtual private cloud (VPC) subnets. The static IP addresses remain assigned to your accelerator for as long as it exists, even if you disable the accelerator and it no longer accepts or routes traffic. However, when you delete an accelerator, you lose the static IP addresses that are assigned to it, so you can no longer route traffic by using them. You can use IAM policies like tag-based permissions with Global Accelerator to limit the users who have permissions to delete an accelerator. For more information, see Tag-based policies. For standard accelerators, Global Accelerator uses the AWS global network to route traffic to the optimal regional endpoint based on health, client location, and policies that you configure. The service reacts instantly to changes in health or configuration to ensure that internet traffic from clients is always directed to healthy endpoints. For a list of the AWS Regions where Global Accelerator and other services are currently supported, see the AWS Region Table. AWS Global Accelerator includes the following components: Static IP addresses Global Accelerator provides you with a set of two static IP addresses that are anycast from the AWS edge network. If you bring your own IP address range to AWS (BYOIP) to use with a standard accelerator, you can instead assign IP addresses from your own pool to use with your accelerator. For more information, see Bring your own IP addresses (BYOIP) in AWS Global Accelerator. The IP addresses serve as single fixed entry points for your clients. If you already have Elastic Load Balancing load balancers, Amazon EC2 instances, or Elastic IP address resources set up for your applications, you can easily add those to a standard accelerator in Global Accelerator. This allows Global Accelerator to use static IP addresses to access the resources. The static IP addresses remain assigned to your accelerator for as long as it exists, even if you disable the accelerator and it no longer accepts or routes traffic. However, when you delete an accelerator, you lose the static IP addresses that are assigned to it, so you can no longer route traffic by using them. You can use IAM policies like tag-based permissions with Global Accelerator to delete an accelerator. For more information, see Tag-based policies. Accelerator An accelerator directs traffic to endpoints over the AWS global network to improve the performance of your internet applications. Each accelerator includes one or more listeners. There are two types of accelerators: A standard accelerator directs traffic to the optimal AWS endpoint based on several factors, including the user’s location, the health of the endpoint, and the endpoint weights that you configure. This improves the availability and performance of your applications. Endpoints can be Network Load Balancers, Application Load Balancers, Amazon EC2 instances, or Elastic IP addresses. A custom routing accelerator directs traffic to one of possibly thousands of Amazon EC2 instances running in a single or multiple virtual private clouds (VPCs). With custom routing, listener ports are mapped to statically associate port ranges with VPC subnets, which allows Global Accelerator to determine an EC2 instance IP address at the time of connection. By default, all port mapping destinations in a VPC subnet can't receive traffic. You can choose to configure all destinations in the subnet to receive traffic, or to specify individual port mappings that can receive traffic. For more information, see Types of accelerators. DNS name Global Accelerator assigns each accelerator a default Domain Name System (DNS) name, similar to a1234567890abcdef.awsglobalaccelerator.com, that points to the static IP addresses that Global Accelerator assigns to you or that you choose from your own IP address range. Depending on the use case, you can use your accelerator's static IP addresses or DNS name to route traffic to your accelerator, or set up DNS records to route traffic using your own custom domain name. Network zone A network zone services the static IP addresses for your accelerator from a unique IP subnet. Similar to an AWS Availability Zone, a network zone is an isolated unit with its own set of physical infrastructure. When you configure an accelerator, by default, Global Accelerator allocates two IPv4 addresses for it. If one IP address from a network zone becomes unavailable due to IP address blocking by certain client networks, or network disruptions, then client applications can retry on the healthy static IP address from the other isolated network zone. Listener A listener processes inbound connections from clients to Global Accelerator, based on the port (or port range) and protocol (or protocols) that you configure. A listener can be configured for TCP, UDP, or both TCP and UDP protocols. Each listener has one or more endpoint groups associated with it, and traffic is forwarded to endpoints in one of the groups. You associate endpoint groups with listeners by specifying the Regions that you want to distribute traffic to. With a standard accelerator, traffic is distributed to optimal endpoints within the endpoint groups associated with a listener. Endpoint group Each endpoint group is associated with a specific AWS Region. Endpoint groups include one or more endpoints in the Region. With a standard accelerator, you can increase or reduce the percentage of traffic that would be otherwise directed to an endpoint group by adjusting a setting called a traffic dial. The traffic dial lets you easily do performance testing or blue/green deployment testing, for example, for new releases across different AWS Regions. Endpoint An endpoint is a resource that Global Accelerator directs traffic to. Endpoints for standard accelerators can be Network Load Balancers, Application Load Balancers, Amazon EC2 instances, or Elastic IP addresses. An Application Load Balancer endpoint can be internet-facing or internal. Traffic for standard accelerators is routed to endpoints based on the health of the endpoint along with configuration options that you choose, such as endpoint weights. For each endpoint, you can configure weights, which are numbers that you can use to specify the proportion of traffic to route to each one. This can be useful, for example, to do performance testing within a Region. Endpoints for custom routing accelerators are virtual private cloud (VPC) subnets with one or many EC2 instances.

Use these REST APIs for performing operations on User entity in Azure API Management deployment. The User entity in API Management represents the developers that call the APIs of the products to which they are subscribed.

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.

Edge gateway operation endpoints and objects.

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.

Resource health operation endpoints and objects.

Azure Application Insights workbook template type.

The Azure BatchAI Management API.

AWS CloudFormation CloudFormation allows you to create and manage Amazon Web Services infrastructure deployments predictably and repeatedly. You can use CloudFormation to leverage Amazon Web Services products, such as Amazon Elastic Compute Cloud, Amazon Elastic Block Store, Amazon Simple Notification Service, Elastic Load Balancing, and Auto Scaling to build highly-reliable, highly scalable, cost-effective applications without creating or configuring the underlying Amazon Web Services infrastructure. With CloudFormation, you declare all of your resources and dependencies in a template file. The template defines a collection of resources as a single unit called a stack. CloudFormation creates and deletes all member resources of the stack together and manages all dependencies between the resources for you. For more information about CloudFormation, see the CloudFormation Product Page. CloudFormation makes use of other Amazon Web Services products. If you need additional technical information about a specific Amazon Web Services product, you can find the product's technical documentation at docs.aws.amazon.com .

Amazon Inspector Amazon Inspector enables you to analyze the behavior of your AWS resources and to identify potential security issues. For more information, see Amazon Inspector User Guide.