Mock sample for your project: Amazon Cognito Identity API

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Amazon Cognito Identity

amazonaws.com

Version: 2014-06-30


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Description

Amazon Cognito Federated Identities Amazon Cognito Federated Identities is a web service that delivers scoped temporary credentials to mobile devices and other untrusted environments. It uniquely identifies a device and supplies the user with a consistent identity over the lifetime of an application. Using Amazon Cognito Federated Identities, you can enable authentication with one or more third-party identity providers (Facebook, Google, or Login with Amazon) or an Amazon Cognito user pool, and you can also choose to support unauthenticated access from your app. Cognito delivers a unique identifier for each user and acts as an OpenID token provider trusted by AWS Security Token Service (STS) to access temporary, limited-privilege AWS credentials. For a description of the authentication flow from the Amazon Cognito Developer Guide see Authentication Flow. For more information see Amazon Cognito Federated Identities.

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AWS CodeDeploy

AWS CodeDeploy AWS CodeDeploy is a deployment service that automates application deployments to Amazon EC2 instances, on-premises instances running in your own facility, serverless AWS Lambda functions, or applications in an Amazon ECS service. You can deploy a nearly unlimited variety of application content, such as an updated Lambda function, updated applications in an Amazon ECS service, code, web and configuration files, executables, packages, scripts, multimedia files, and so on. AWS CodeDeploy can deploy application content stored in Amazon S3 buckets, GitHub repositories, or Bitbucket repositories. You do not need to make changes to your existing code before you can use AWS CodeDeploy. AWS CodeDeploy makes it easier for you to rapidly release new features, helps you avoid downtime during application deployment, and handles the complexity of updating your applications, without many of the risks associated with error-prone manual deployments. AWS CodeDeploy Components Use the information in this guide to help you work with the following AWS CodeDeploy components: Application : A name that uniquely identifies the application you want to deploy. AWS CodeDeploy uses this name, which functions as a container, to ensure the correct combination of revision, deployment configuration, and deployment group are referenced during a deployment. Deployment group : A set of individual instances, CodeDeploy Lambda deployment configuration settings, or an Amazon ECS service and network details. A Lambda deployment group specifies how to route traffic to a new version of a Lambda function. An Amazon ECS deployment group specifies the service created in Amazon ECS to deploy, a load balancer, and a listener to reroute production traffic to an updated containerized application. An EC2/On-premises deployment group contains individually tagged instances, Amazon EC2 instances in Amazon EC2 Auto Scaling groups, or both. All deployment groups can specify optional trigger, alarm, and rollback settings. Deployment configuration : A set of deployment rules and deployment success and failure conditions used by AWS CodeDeploy during a deployment. Deployment : The process and the components used when updating a Lambda function, a containerized application in an Amazon ECS service, or of installing content on one or more instances. Application revisions : For an AWS Lambda deployment, this is an AppSpec file that specifies the Lambda function to be updated and one or more functions to validate deployment lifecycle events. For an Amazon ECS deployment, this is an AppSpec file that specifies the Amazon ECS task definition, container, and port where production traffic is rerouted. For an EC2/On-premises deployment, this is an archive file that contains source content—source code, webpages, executable files, and deployment scripts—along with an AppSpec file. Revisions are stored in Amazon S3 buckets or GitHub repositories. For Amazon S3, a revision is uniquely identified by its Amazon S3 object key and its ETag, version, or both. For GitHub, a revision is uniquely identified by its commit ID. This guide also contains information to help you get details about the instances in your deployments, to make on-premises instances available for AWS CodeDeploy deployments, to get details about a Lambda function deployment, and to get details about Amazon ECS service deployments. AWS CodeDeploy Information Resources AWS CodeDeploy User Guide AWS CodeDeploy API Reference Guide AWS CLI Reference for AWS CodeDeploy AWS CodeDeploy Developer Forum

Amazon Elastic Block Store

You can use the Amazon Elastic Block Store (Amazon EBS) direct APIs to create Amazon EBS snapshots, write data directly to your snapshots, read data on your snapshots, and identify the differences or changes between two snapshots. If you’re an independent software vendor (ISV) who offers backup services for Amazon EBS, the EBS direct APIs make it more efficient and cost-effective to track incremental changes on your Amazon EBS volumes through snapshots. This can be done without having to create new volumes from snapshots, and then use Amazon Elastic Compute Cloud (Amazon EC2) instances to compare the differences. You can create incremental snapshots directly from data on-premises into volumes and the cloud to use for quick disaster recovery. With the ability to write and read snapshots, you can write your on-premises data to an snapshot during a disaster. Then after recovery, you can restore it back to Amazon Web Services or on-premises from the snapshot. You no longer need to build and maintain complex mechanisms to copy data to and from Amazon EBS. This API reference provides detailed information about the actions, data types, parameters, and errors of the EBS direct APIs. For more information about the elements that make up the EBS direct APIs, and examples of how to use them effectively, see Accessing the Contents of an Amazon EBS Snapshot in the Amazon Elastic Compute Cloud User Guide. For more information about the supported Amazon Web Services Regions, endpoints, and service quotas for the EBS direct APIs, see Amazon Elastic Block Store Endpoints and Quotas in the Amazon Web Services General Reference.

Amazon Location Service

Suite of geospatial services including Maps, Places, Routes, Tracking, and Geofencing

Amazon Lookout for Vision

This is the Amazon Lookout for Vision API Reference. It provides descriptions of actions, data types, common parameters, and common errors. Amazon Lookout for Vision enables you to find visual defects in industrial products, accurately and at scale. It uses computer vision to identify missing components in an industrial product, damage to vehicles or structures, irregularities in production lines, and even minuscule defects in silicon wafers — or any other physical item where quality is important such as a missing capacitor on printed circuit boards.

AWS App Runner

AWS App Runner AWS App Runner is an application service that provides a fast, simple, and cost-effective way to go directly from an existing container image or source code to a running service in the AWS cloud in seconds. You don't need to learn new technologies, decide which compute service to use, or understand how to provision and configure AWS resources. App Runner connects directly to your container registry or source code repository. It provides an automatic delivery pipeline with fully managed operations, high performance, scalability, and security. For more information about App Runner, see the AWS App Runner Developer Guide. For release information, see the AWS App Runner Release Notes. To install the Software Development Kits (SDKs), Integrated Development Environment (IDE) Toolkits, and command line tools that you can use to access the API, see Tools for Amazon Web Services. Endpoints For a list of Region-specific endpoints that App Runner supports, see AWS App Runner endpoints and quotas in the AWS General Reference.

Amazon Athena

Amazon Athena is an interactive query service that lets you use standard SQL to analyze data directly in Amazon S3. You can point Athena at your data in Amazon S3 and run ad-hoc queries and get results in seconds. Athena is serverless, so there is no infrastructure to set up or manage. You pay only for the queries you run. Athena scales automatically—executing queries in parallel—so results are fast, even with large datasets and complex queries. For more information, see What is Amazon Athena in the Amazon Athena User Guide. If you connect to Athena using the JDBC driver, use version 1.1.0 of the driver or later with the Amazon Athena API. Earlier version drivers do not support the API. For more information and to download the driver, see Accessing Amazon Athena with JDBC. For code samples using the Amazon Web Services SDK for Java, see Examples and Code Samples in the Amazon Athena User Guide.

Amazon Augmented AI Runtime

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.

AWS Migration Hub

The AWS Migration Hub API methods help to obtain server and application migration status and integrate your resource-specific migration tool by providing a programmatic interface to Migration Hub. Remember that you must set your AWS Migration Hub home region before you call any of these APIs, or a HomeRegionNotSetException error will be returned. Also, you must make the API calls while in your home region.

Amazon SageMaker Service

Provides APIs for creating and managing Amazon SageMaker resources. Other Resources: Amazon SageMaker Developer Guide Amazon Augmented AI Runtime API Reference

Amazon Kinesis Video Streams

AWS Cloud Map

Cloud Map With Cloud Map, you can configure public DNS, private DNS, or HTTP namespaces that your microservice applications run in. When an instance becomes available, you can call the Cloud Map API to register the instance with Cloud Map. For public or private DNS namespaces, Cloud Map automatically creates DNS records and an optional health check. Clients that submit public or private DNS queries, or HTTP requests, for the service receive an answer that contains up to eight healthy records.

Other APIs in the same category

AWS Global Accelerator

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.

Text Analytics Client

The Text Analytics API is a suite of text analytics web services built with best-in-class Microsoft machine learning algorithms. The API can be used to analyze unstructured text for tasks such as sentiment analysis, key phrase extraction and language detection. No training data is needed to use this API; just bring your text data. This API uses advanced natural language processing techniques to deliver best in class predictions. Further documentation can be found in https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview

Linode API

Introduction
The Linode API provides the ability to programmatically manage the full
range of Linode products and services.
This reference is designed to assist application developers and system
administrators. Each endpoint includes descriptions, request syntax, and
examples using standard HTTP requests. Response data is returned in JSON
format.
This document was generated from our OpenAPI Specification. See the
OpenAPI website for more information.
Download the Linode OpenAPI Specification.
Changelog
View our Changelog to see release
notes on all changes made to our API.
Access and Authentication
Some endpoints are publicly accessible without requiring authentication.
All endpoints affecting your Account, however, require either a Personal
Access Token or OAuth authentication (when using third-party
applications).
Personal Access Token
The easiest way to access the API is with a Personal Access Token (PAT)
generated from the
Linode Cloud Manager or
the Create Personal Access Token endpoint.
All scopes for the OAuth security model (defined below) apply to this
security model as well.
Authentication
| Security Scheme Type: | HTTP |
|-----------------------|------|
| HTTP Authorization Scheme | bearer |
OAuth
If you only need to access the Linode API for personal use,
we recommend that you create a personal access token.
If you're designing an application that can authenticate with an arbitrary Linode user, then
you should use the OAuth 2.0 workflows presented in this section.
For a more detailed example of an OAuth 2.0 implementation, see our guide on How to Create an OAuth App with the Linode Python API Library.
Before you implement OAuth in your application, you first need to create an OAuth client. You can do this with the Linode API or via the Cloud Manager:
When creating the client, you'll supply a label and a redirect_uri (referred to as the Callback URL in the Cloud Manager).
The response from this endpoint will give you a client_id and a secret.
Clients can be public or private, and are private by default. You can choose to make the client public when it is created.
A private client is used with applications which can securely store the client secret (that is, the secret returned to you when you first created the client). For example, an application running on a secured server that only the developer has access to would use a private OAuth client. This is also called a confidential client in some OAuth documentation.
A public client is used with applications where the client secret is not guaranteed to be secure. For example, a native app running on a user's computer may not be able to keep the client secret safe, as a user could potentially inspect the source of the application. So, native apps or apps that run in a user's browser should use a public client.
Public and private clients follow different workflows, as described below.
OAuth Workflow
The OAuth workflow is a series of exchanges between your third-party app and Linode. The workflow is used
to authenticate a user before an application can start making API calls on the user's behalf.
Notes:
With respect to the diagram in section 1.2 of RFC 6749, login.linode.com (referred to in this section as the login server)
is the Resource Owner and the Authorization Server; api.linode.com (referred to here as the api server) is the Resource Server.
The OAuth spec refers to the private and public workflows listed below as the authorization code flow and implicit flow.
| PRIVATE WORKFLOW | PUBLIC WORKFLOW |
|------------------|------------------|
| 1. The user visits the application's website and is directed to login with Linode. | 1. The user visits the application's website and is directed to login with Linode. |
| 2. Your application then redirects the user to Linode's login server with the client application's clientid and requested OAuth scope, which should appear in the URL of the login page. | 2. Your application then redirects the user to Linode's login server with the client application's clientid and requested OAuth scope, which should appear in the URL of the login page. |
| 3. The user logs into the login server with their username and password. | 3. The user logs into the login server with their username and password. |
| 4. The login server redirects the user to the specificed redirect URL with a temporary authorization code (exchange code) in the URL. | 4. The login server redirects the user back to your application with an OAuth accesstoken embedded in the redirect URL's hash. This is temporary and expires in two hours. No refreshtoken is issued. Therefore, once the access_token expires, a new one will need to be issued by having the user log in again. |
| 5. The application issues a POST request (see below) to the login server with the exchange code, clientid, and the client application's clientsecret. | |
| 6. The login server responds to the client application with a new OAuth accesstoken and refreshtoken. The access_token is set to expire in two hours. | |
| 7. The refreshtoken can be used by contacting the login server with the clientid, clientsecret, granttype, and refreshtoken to get a new OAuth accesstoken and refreshtoken. The new accesstoken is good for another two hours, and the new refresh_token, can be used to extend the session again by this same method. | |
OAuth Private Workflow - Additional Details
The following information expands on steps 5 through 7 of the private workflow:
Once the user has logged into Linode and you have received an exchange code,
you will need to trade that exchange code for an accesstoken and refreshtoken. You
do this by making an HTTP POST request to the following address:
Rate Limiting
With the Linode API, you can make up to 1,600 general API requests every two minutes per user as
determined by IP adddress or by OAuth token. Additionally, there are endpoint specfic limits defined below.
Note: There may be rate limiting applied at other levels outside of the API, for example, at the load balancer.
/stats endpoints have their own dedicated limits of 100 requests per minute per user.
These endpoints are:
View Linode Statistics
View Linode Statistics (year/month)
View NodeBalancer Statistics
List Managed Stats
Object Storage endpoints have a dedicated limit of 750 requests per second per user.
The Object Storage endpoints are:
Object Storage Endpoints
Opening Support Tickets has a dedicated limit of 2 requests per minute per user.
That endpoint is:
Open Support Ticket
Accepting Service Transfers has a dedicated limit of 2 requests per minute per user.
That endpoint is:
Service Transfer Accept
CLI (Command Line Interface)
The Linode CLI allows you to easily
work with the API using intuitive and simple syntax. It requires a
Personal Access Token
for authentication, and gives you access to all of the features and functionality
of the Linode API that are documented here with CLI examples.
Endpoints that do not have CLI examples are currently unavailable through the CLI, but
can be accessed via other methods such as Shell commands and other third-party applications.

Diagnostics API Client

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Computer Vision Client

microsoft.com
The Computer Vision API provides state-of-the-art algorithms to process images and return information. For example, it can be used to determine if an image contains mature content, or it can be used to find all the faces in an image. It also has other features like estimating dominant and accent colors, categorizing the content of images, and describing an image with complete English sentences. Additionally, it can also intelligently generate images thumbnails for displaying large images effectively.

Clever-Cloud API

clever-cloud.com
Public API for managing Clever-Cloud data and products

Computer Vision

azure.com
The Computer Vision API provides state-of-the-art algorithms to process images and return information. For example, it can be used to determine if an image contains mature content, or it can be used to find all the faces in an image. It also has other features like estimating dominant and accent colors, categorizing the content of images, and describing an image with complete English sentences. Additionally, it can also intelligently generate images thumbnails for displaying large images effectively.

MonitorManagementClient

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Cosmos DB

azure.com
Azure Cosmos DB Database Service Resource Provider REST API

Entity Search Client

microsoft.com
The Entity Search API lets you send a search query to Bing and get back search results that include entities and places. Place results include restaurants, hotel, or other local businesses. For places, the query can specify the name of the local business or it can ask for a list (for example, restaurants near me). Entity results include persons, places, or things. Place in this context is tourist attractions, states, countries, etc.

DeploymentScriptsClient

azure.com
The APIs listed in this specification can be used to manage Deployment Scripts resource through the Azure Resource Manager.

ContainerInstanceManagementClient

azure.com