Mock sample for your project: AWSMarketplace Metering API

Welcome to the IoT SiteWise API Reference. IoT SiteWise is an Amazon Web Services service that connects Industrial Internet of Things (IIoT) devices to the power of the Amazon Web Services Cloud. For more information, see the IoT SiteWise User Guide. For information about IoT SiteWise quotas, see Quotas in the IoT SiteWise User Guide.

IoT IoT provides secure, bi-directional communication between Internet-connected devices (such as sensors, actuators, embedded devices, or smart appliances) and the Amazon Web Services cloud. You can discover your custom IoT-Data endpoint to communicate with, configure rules for data processing and integration with other services, organize resources associated with each device (Registry), configure logging, and create and manage policies and credentials to authenticate devices. The service endpoints that expose this API are listed in Amazon Web Services IoT Core Endpoints and Quotas. You must use the endpoint for the region that has the resources you want to access. The service name used by Amazon Web Services Signature Version 4 to sign the request is: execute-api. For more information about how IoT works, see the Developer Guide. For information about how to use the credentials provider for IoT, see Authorizing Direct Calls to Amazon Web Services Services.

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.

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.

Amazon DevOps Guru is a fully managed service that helps you identify anomalous behavior in business critical operational applications. You specify the AWS resources that you want DevOps Guru to cover, then the Amazon CloudWatch metrics and AWS CloudTrail events related to those resources are analyzed. When anomalous behavior is detected, DevOps Guru creates an insight that includes recommendations, related events, and related metrics that can help you improve your operational applications. For more information, see What is Amazon DevOps Guru. You can specify 1 or 2 Amazon Simple Notification Service topics so you are notified every time a new insight is created. You can also enable DevOps Guru to generate an OpsItem in AWS Systems Manager for each insight to help you manage and track your work addressing insights. To learn about the DevOps Guru workflow, see How DevOps Guru works. To learn about DevOps Guru concepts, see Concepts in DevOps Guru.

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 Elastic Container Service Amazon Elastic Container Service (Amazon ECS) is a highly scalable, fast, container management service that makes it easy to run, stop, and manage Docker containers on a cluster. You can host your cluster on a serverless infrastructure that is managed by Amazon ECS by launching your services or tasks on Fargate. For more control, you can host your tasks on a cluster of Amazon Elastic Compute Cloud (Amazon EC2) instances that you manage. Amazon ECS makes it easy to launch and stop container-based applications with simple API calls, allows you to get the state of your cluster from a centralized service, and gives you access to many familiar Amazon EC2 features. You can use Amazon ECS to schedule the placement of containers across your cluster based on your resource needs, isolation policies, and availability requirements. Amazon ECS eliminates the need for you to operate your own cluster management and configuration management systems or worry about scaling your management infrastructure.

Describes all of the AWS IoT 1-Click device-related API operations for the service.
Also provides sample requests, responses, and errors for the supported web services
protocols.

Amazon Route 53 is a highly available and scalable Domain Name System (DNS) web service.

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.

AWS IoT Wireless API documentation

AWS AppConfig Use AWS AppConfig, a capability of AWS Systems Manager, to create, manage, and quickly deploy application configurations. AppConfig supports controlled deployments to applications of any size and includes built-in validation checks and monitoring. You can use AppConfig with applications hosted on Amazon EC2 instances, AWS Lambda, containers, mobile applications, or IoT devices. To prevent errors when deploying application configurations, especially for production systems where a simple typo could cause an unexpected outage, AppConfig includes validators. A validator provides a syntactic or semantic check to ensure that the configuration you want to deploy works as intended. To validate your application configuration data, you provide a schema or a Lambda function that runs against the configuration. The configuration deployment or update can only proceed when the configuration data is valid. During a configuration deployment, AppConfig monitors the application to ensure that the deployment is successful. If the system encounters an error, AppConfig rolls back the change to minimize impact for your application users. You can configure a deployment strategy for each application or environment that includes deployment criteria, including velocity, bake time, and alarms to monitor. Similar to error monitoring, if a deployment triggers an alarm, AppConfig automatically rolls back to the previous version. AppConfig supports multiple use cases. Here are some examples. Application tuning : Use AppConfig to carefully introduce changes to your application that can only be tested with production traffic. Feature toggle : Use AppConfig to turn on new features that require a timely deployment, such as a product launch or announcement. Allow list : Use AppConfig to allow premium subscribers to access paid content. Operational issues : Use AppConfig to reduce stress on your application when a dependency or other external factor impacts the system. This reference is intended to be used with the AWS AppConfig User Guide.

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.

Detective uses machine learning and purpose-built visualizations to help you analyze and investigate security issues across your Amazon Web Services (AWS) workloads. Detective automatically extracts time-based events such as login attempts, API calls, and network traffic from AWS CloudTrail and Amazon Virtual Private Cloud (Amazon VPC) flow logs. It also extracts findings detected by Amazon GuardDuty. The Detective API primarily supports the creation and management of behavior graphs. A behavior graph contains the extracted data from a set of member accounts, and is created and managed by an administrator account. Every behavior graph is specific to a Region. You can only use the API to manage graphs that belong to the Region that is associated with the currently selected endpoint. A Detective administrator account can use the Detective API to do the following: Enable and disable Detective. Enabling Detective creates a new behavior graph. View the list of member accounts in a behavior graph. Add member accounts to a behavior graph. Remove member accounts from a behavior graph. A member account can use the Detective API to do the following: View the list of behavior graphs that they are invited to. Accept an invitation to contribute to a behavior graph. Decline an invitation to contribute to a behavior graph. Remove their account from a behavior graph. All API actions are logged as CloudTrail events. See Logging Detective API Calls with CloudTrail. We replaced the term "master account" with the term "administrator account." An administrator account is used to centrally manage multiple accounts. In the case of Detective, the administrator account manages the accounts in their behavior graph.

The AWS Serverless Application Repository makes it easy for developers and enterprises to quickly find
and deploy serverless applications in the AWS Cloud. For more information about serverless applications,
see Serverless Computing and Applications on the AWS website. The AWS Serverless Application Repository is deeply integrated with the AWS Lambda console, so that developers of
all levels can get started with serverless computing without needing to learn anything new. You can use category
keywords to browse for applications such as web and mobile backends, data processing applications, or chatbots.
You can also search for applications by name, publisher, or event source. To use an application, you simply choose it,
configure any required fields, and deploy it with a few clicks. You can also easily publish applications, sharing them publicly with the community at large, or privately
within your team or across your organization. To publish a serverless application (or app), you can use the
AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDKs to upload the code. Along with the
code, you upload a simple manifest file, also known as the AWS Serverless Application Model (AWS SAM) template.
For more information about AWS SAM, see AWS Serverless Application Model (AWS SAM) on the AWS Labs
GitHub repository. The AWS Serverless Application Repository Developer Guide contains more information about the two developer
experiences available:
Consuming Applications – Browse for applications and view information about them, including
source code and readme files. Also install, configure, and deploy applications of your choosing.
Publishing Applications – Configure and upload applications to make them available to other
developers, and publish new versions of applications.

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.

The Container Service Client.

These APIs allow end users to operate on Azure Machine Learning Commitment Plans resources and their child Commitment Association resources. They support CRUD operations for commitment plans, get and list operations for commitment associations, moving commitment associations between commitment plans, and retrieving commitment plan usage history.

Virtual Machine Image Template

The service is used to perform ink layout and recognition of written words and shapes. Ink strokes passed to the service are recognized and organized into recognition results in the response

Azure Log Analytics API reference