Mock sample for your project: AWS Amplify API

Amazon Elastic Container Registry Amazon Elastic Container Registry (Amazon ECR) is a managed container image registry service. Customers can use the familiar Docker CLI, or their preferred client, to push, pull, and manage images. Amazon ECR provides a secure, scalable, and reliable registry for your Docker or Open Container Initiative (OCI) images. Amazon ECR supports private repositories with resource-based permissions using IAM so that specific users or Amazon EC2 instances can access repositories and images. Amazon ECR has service endpoints in each supported Region. For more information, see Amazon ECR endpoints in the Amazon Web Services General Reference.

Amazon CloudFront This is the Amazon CloudFront API Reference. This guide is for developers who need detailed information about CloudFront API actions, data types, and errors. For detailed information about CloudFront features, see the Amazon CloudFront Developer Guide.

Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.

Backup Backup is a unified backup service designed to protect Amazon Web Services services and their associated data. Backup simplifies the creation, migration, restoration, and deletion of backups, while also providing reporting and auditing.

AWS CloudHSM Service This is documentation for AWS CloudHSM Classic. For more information, see AWS CloudHSM Classic FAQs, the AWS CloudHSM Classic User Guide, and the AWS CloudHSM Classic API Reference. For information about the current version of AWS CloudHSM, see AWS CloudHSM, the AWS CloudHSM User Guide, and the AWS CloudHSM API Reference.

Amazon FSx is a fully managed service that makes it easy for storage and application administrators to launch and use shared file storage.

Amazon API Gateway Amazon API Gateway helps developers deliver robust, secure, and scalable mobile and web application back ends. API Gateway allows developers to securely connect mobile and web applications to APIs that run on AWS Lambda, Amazon EC2, or other publicly addressable web services that are hosted outside of AWS.

Amazon GameLift Service GameLift provides solutions for hosting session-based multiplayer game servers in the cloud, including tools for deploying, operating, and scaling game servers. Built on AWS global computing infrastructure, GameLift helps you deliver high-performance, high-reliability, low-cost game servers while dynamically scaling your resource usage to meet player demand. About GameLift solutions Get more information on these GameLift solutions in the GameLift Developer Guide. GameLift managed hosting -- GameLift offers a fully managed service to set up and maintain computing machines for hosting, manage game session and player session life cycle, and handle security, storage, and performance tracking. You can use automatic scaling tools to balance player demand and hosting costs, configure your game session management to minimize player latency, and add FlexMatch for matchmaking. Managed hosting with Realtime Servers -- With GameLift Realtime Servers, you can quickly configure and set up ready-to-go game servers for your game. Realtime Servers provides a game server framework with core GameLift infrastructure already built in. Then use the full range of GameLift managed hosting features, including FlexMatch, for your game. GameLift FleetIQ -- Use GameLift FleetIQ as a standalone service while hosting your games using EC2 instances and Auto Scaling groups. GameLift FleetIQ provides optimizations for game hosting, including boosting the viability of low-cost Spot Instances gaming. For a complete solution, pair the GameLift FleetIQ and FlexMatch standalone services. GameLift FlexMatch -- Add matchmaking to your game hosting solution. FlexMatch is a customizable matchmaking service for multiplayer games. Use FlexMatch as integrated with GameLift managed hosting or incorporate FlexMatch as a standalone service into your own hosting solution. About this API Reference This reference guide describes the low-level service API for Amazon GameLift. With each topic in this guide, you can find links to language-specific SDK guides and the AWS CLI reference. Useful links: GameLift API operations listed by tasks GameLift tools and resources

Batch Using Batch, you can run batch computing workloads on the Cloud. Batch computing is a common means for developers, scientists, and engineers to access large amounts of compute resources. Batch uses the advantages of this computing workload to remove the undifferentiated heavy lifting of configuring and managing required infrastructure. At the same time, it also adopts a familiar batch computing software approach. Given these advantages, Batch can help you to efficiently provision resources in response to jobs submitted, thus effectively helping you to eliminate capacity constraints, reduce compute costs, and deliver your results more quickly. As a fully managed service, Batch can run batch computing workloads of any scale. Batch automatically provisions compute resources and optimizes workload distribution based on the quantity and scale of your specific workloads. With Batch, there's no need to install or manage batch computing software. This means that you can focus your time and energy on analyzing results and solving your specific problems.

IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight. Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources. IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.

Amazon EC2 Auto Scaling Amazon EC2 Auto Scaling is designed to automatically launch or terminate EC2 instances based on user-defined scaling policies, scheduled actions, and health checks. For more information about Amazon EC2 Auto Scaling, see the Amazon EC2 Auto Scaling User Guide. For information about granting IAM users required permissions for calls to Amazon EC2 Auto Scaling, see Granting IAM users required permissions for Amazon EC2 Auto Scaling resources in the Amazon EC2 Auto Scaling API Reference.

Amazon Kendra is a service for indexing large document sets.

The Admin Compute Disk Management Client.

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 EMR on EKS provides a deployment option for Amazon EMR that allows you to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). With this deployment option, you can focus on running analytics workloads while Amazon EMR on EKS builds, configures, and manages containers for open-source applications. For more information about Amazon EMR on EKS concepts and tasks, see What is Amazon EMR on EKS. Amazon EMR containers is the API name for Amazon EMR on EKS. The emr-containers prefix is used in the following scenarios: It is the prefix in the CLI commands for Amazon EMR on EKS. For example, aws emr-containers start-job-run. It is the prefix before IAM policy actions for Amazon EMR on EKS. For example,"Action": [ "emr-containers:StartJobRun"]. For more information, see Policy actions for Amazon EMR on EKS. It is the prefix used in Amazon EMR on EKS service endpoints. For example, emr-containers.us-east-2.amazonaws.com. For more information, see Amazon EMR on EKS Service Endpoints.

For more information about AWS CloudHSM, see AWS CloudHSM and the AWS CloudHSM User Guide.

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.

The REST API specification for Ably.

Welcome to the Audit Manager API reference. This guide is for developers who need detailed information about the Audit Manager API operations, data types, and errors. Audit Manager is a service that provides automated evidence collection so that you can continuously audit your Amazon Web Services usage, and assess the effectiveness of your controls to better manage risk and simplify compliance. Audit Manager provides pre-built frameworks that structure and automate assessments for a given compliance standard. Frameworks include a pre-built collection of controls with descriptions and testing procedures, which are grouped according to the requirements of the specified compliance standard or regulation. You can also customize frameworks and controls to support internal audits with unique requirements. Use the following links to get started with the Audit Manager API: Actions : An alphabetical list of all Audit Manager API operations. Data types : An alphabetical list of all Audit Manager data types. Common parameters : Parameters that all Query operations can use. Common errors : Client and server errors that all operations can return. If you're new to Audit Manager, we recommend that you review the Audit Manager User Guide.

Time Series Insights environment data plane client for PAYG (Preview L1 SKU) environments.

The News Search API lets you send a search query to Bing and get back a list of news that are relevant to the search query. This section provides technical details about the query parameters and headers that you use to request news and the JSON response objects that contain them. For examples that show how to make requests, see Searching the web for news.

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.

This is the public REST API for elmah.io. All of the integrations communicates with elmah.io through this API. For additional help getting started with the API, visit the following help articles: Using the REST API Where is my API key? Where is my log ID? How to configure API key permissions