Mock sample for your project: Amazon Translate API

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.

You can use the Amazon Redshift Data API to run queries on Amazon Redshift tables. You can run SQL statements, which are committed if the statement succeeds. For more information about the Amazon Redshift Data API, see Using the Amazon Redshift Data API in the Amazon Redshift Cluster Management Guide.

Directory Service Directory Service is a web service that makes it easy for you to setup and run directories in the Amazon Web Services cloud, or connect your Amazon Web Services resources with an existing self-managed Microsoft Active Directory. This guide provides detailed information about Directory Service operations, data types, parameters, and errors. For information about Directory Services features, see Directory Service and the Directory Service Administration Guide. Amazon Web Services provides SDKs that consist of libraries and sample code for various programming languages and platforms (Java, Ruby, .Net, iOS, Android, etc.). The SDKs provide a convenient way to create programmatic access to Directory Service and other Amazon Web Services services. For more information about the Amazon Web Services SDKs, including how to download and install them, see Tools for Amazon Web Services.

You use the AmazonCloudSearch2013 API to upload documents to a search domain and search those documents. The endpoints for submitting UploadDocuments, Search, and Suggest requests are domain-specific. To get the endpoints for your domain, use the Amazon CloudSearch configuration service DescribeDomains action. The domain endpoints are also displayed on the domain dashboard in the Amazon CloudSearch console. You submit suggest requests to the search endpoint. For more information, see the Amazon CloudSearch Developer Guide.

The Amazon API Gateway Management API allows you to directly manage runtime aspects of your deployed APIs. To use it, you must explicitly set the SDK's endpoint to point to the endpoint of your deployed API. The endpoint will be of the form https://{api-id}.execute-api.{region}.amazonaws.com/{stage}, or will be the endpoint corresponding to your API's custom domain and base path, if applicable.

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.

Amazon Web Services Transfer Family is a fully managed service that enables the transfer of files over the File Transfer Protocol (FTP), File Transfer Protocol over SSL (FTPS), or Secure Shell (SSH) File Transfer Protocol (SFTP) directly into and out of Amazon Simple Storage Service (Amazon S3). Amazon Web Services helps you seamlessly migrate your file transfer workflows to Amazon Web Services Transfer Family by integrating with existing authentication systems, and providing DNS routing with Amazon Route 53 so nothing changes for your customers and partners, or their applications. With your data in Amazon S3, you can use it with Amazon Web Services services for processing, analytics, machine learning, and archiving. Getting started with Amazon Web Services Transfer Family is easy since there is no infrastructure to buy and set up.

The Amazon Chime API (application programming interface) is designed for developers to perform key tasks, such as creating and managing Amazon Chime accounts, users, and Voice Connectors. This guide provides detailed information about the Amazon Chime API, including operations, types, inputs and outputs, and error codes. It also includes some server-side API actions to use with the Amazon Chime SDK. For more information about the Amazon Chime SDK, see Using the Amazon Chime SDK in the Amazon Chime Developer Guide. You can use an AWS SDK, the AWS Command Line Interface (AWS CLI), or the REST API to make API calls. We recommend using an AWS SDK or the AWS CLI. Each API operation includes links to information about using it with a language-specific AWS SDK or the AWS CLI. Using an AWS SDK You don't need to write code to calculate a signature for request authentication. The SDK clients authenticate your requests by using access keys that you provide. For more information about AWS SDKs, see the AWS Developer Center. Using the AWS CLI Use your access keys with the AWS CLI to make API calls. For information about setting up the AWS CLI, see Installing the AWS Command Line Interface in the AWS Command Line Interface User Guide. For a list of available Amazon Chime commands, see the Amazon Chime commands in the AWS CLI Command Reference. Using REST APIs If you use REST to make API calls, you must authenticate your request by providing a signature. Amazon Chime supports signature version 4. For more information, see Signature Version 4 Signing Process in the Amazon Web Services General Reference. When making REST API calls, use the service name chime and REST endpoint https://service.chime.aws.amazon.com. Administrative permissions are controlled using AWS Identity and Access Management (IAM). For more information, see Identity and Access Management for Amazon Chime in the Amazon Chime Administration Guide.

Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect your sensitive data in AWS. Macie automates the discovery of sensitive data, such as PII and intellectual property, to provide you with insight into the data that your organization stores in AWS. Macie also provides an inventory of your Amazon S3 buckets, which it continually monitors for you. If Macie detects sensitive data or potential data access issues, it generates detailed findings for you to review and act upon as necessary.

Amazon Web Services Service Catalog AppRegistry enables organizations to understand the application context of their Amazon Web Services resources. AppRegistry provides a repository of your applications, their resources, and the application metadata that you use within your enterprise.

Amazon Lookout for Equipment is a machine learning service that uses advanced analytics to identify anomalies in machines from sensor data for use in predictive maintenance.

Welcome to the Amazon SQS API Reference. Amazon SQS is a reliable, highly-scalable hosted queue for storing messages as they travel between applications or microservices. Amazon SQS moves data between distributed application components and helps you decouple these components. For information on the permissions you need to use this API, see Identity and access management in the Amazon SQS Developer Guide. You can use Amazon Web Services SDKs to access Amazon SQS using your favorite programming language. The SDKs perform tasks such as the following automatically: Cryptographically sign your service requests Retry requests Handle error responses Additional information Amazon SQS Product Page Amazon SQS Developer Guide Making API Requests Amazon SQS Message Attributes Amazon SQS Dead-Letter Queues Amazon SQS in the Command Line Interface Amazon Web Services General Reference Regions and Endpoints

The HDInsight Management Client.

The Anomaly Finder API detects anomalies automatically in time series data. It supports two functionalities, one is for detecting the whole series with model trained by the timeseries, another is detecting last point with model trained by points before. By using this service, business customers can discover incidents and establish a logic flow for root cause analysis.

Azure Log Analytics API reference for Solution.

This Swagger was generated by the API Framework.

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.

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.

Allows extension of ARM control plane with custom resource providers.

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