Mock sample for your project: AWS Resource Groups Tagging API

Amazon Simple Workflow Service The Amazon Simple Workflow Service (Amazon SWF) makes it easy to build applications that use Amazon's cloud to coordinate work across distributed components. In Amazon SWF, a task represents a logical unit of work that is performed by a component of your workflow. Coordinating tasks in a workflow involves managing intertask dependencies, scheduling, and concurrency in accordance with the logical flow of the application. Amazon SWF gives you full control over implementing tasks and coordinating them without worrying about underlying complexities such as tracking their progress and maintaining their state. This documentation serves as reference only. For a broader overview of the Amazon SWF programming model, see the Amazon SWF Developer Guide .

AWS Data Exchange is a service that makes it easy for AWS customers to exchange data in the cloud. You can use the AWS Data Exchange APIs to create, update, manage, and access file-based data set in the AWS Cloud. As a subscriber, you can view and access the data sets that you have an entitlement to through a subscription. You can use the APIS to download or copy your entitled data sets to Amazon S3 for use across a variety of AWS analytics and machine learning services. As a provider, you can create and manage your data sets that you would like to publish to a product. Being able to package and provide your data sets into products requires a few steps to determine eligibility. For more information, visit the AWS Data Exchange User Guide. A data set is a collection of data that can be changed or updated over time. Data sets can be updated using revisions, which represent a new version or incremental change to a data set. A revision contains one or more assets. An asset in AWS Data Exchange is a piece of data that can be stored as an Amazon S3 object. The asset can be a structured data file, an image file, or some other data file. Jobs are asynchronous import or export operations used to create or copy assets.

DAX is a managed caching service engineered for Amazon DynamoDB. DAX dramatically speeds up database reads by caching frequently-accessed data from DynamoDB, so applications can access that data with sub-millisecond latency. You can create a DAX cluster easily, using the AWS Management Console. With a few simple modifications to your code, your application can begin taking advantage of the DAX cluster and realize significant improvements in read performance.

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.

With Application Auto Scaling, you can configure automatic scaling for the following resources: Amazon AppStream 2.0 fleets Amazon Aurora Replicas Amazon Comprehend document classification and entity recognizer endpoints Amazon DynamoDB tables and global secondary indexes throughput capacity Amazon ECS services Amazon ElastiCache for Redis clusters (replication groups) Amazon EMR clusters Amazon Keyspaces (for Apache Cassandra) tables Lambda function provisioned concurrency Amazon Managed Streaming for Apache Kafka broker storage Amazon SageMaker endpoint variants Spot Fleet (Amazon EC2) requests Custom resources provided by your own applications or services API Summary The Application Auto Scaling service API includes three key sets of actions: Register and manage scalable targets - Register Amazon Web Services or custom resources as scalable targets (a resource that Application Auto Scaling can scale), set minimum and maximum capacity limits, and retrieve information on existing scalable targets. Configure and manage automatic scaling - Define scaling policies to dynamically scale your resources in response to CloudWatch alarms, schedule one-time or recurring scaling actions, and retrieve your recent scaling activity history. Suspend and resume scaling - Temporarily suspend and later resume automatic scaling by calling the RegisterScalableTarget API action for any Application Auto Scaling scalable target. You can suspend and resume (individually or in combination) scale-out activities that are triggered by a scaling policy, scale-in activities that are triggered by a scaling policy, and scheduled scaling. To learn more about Application Auto Scaling, including information about granting IAM users required permissions for Application Auto Scaling actions, see the Application Auto Scaling User Guide.

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.

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 Elastic Kubernetes Service (Amazon EKS) is a managed service that makes it easy for you to run Kubernetes on Amazon Web Services without needing to stand up or maintain your own Kubernetes control plane. Kubernetes is an open-source system for automating the deployment, scaling, and management of containerized applications. Amazon EKS runs up-to-date versions of the open-source Kubernetes software, so you can use all the existing plugins and tooling from the Kubernetes community. Applications running on Amazon EKS are fully compatible with applications running on any standard Kubernetes environment, whether running in on-premises data centers or public clouds. This means that you can easily migrate any standard Kubernetes application to Amazon EKS without any code modification required.

Direct Connect links your internal network to an Direct Connect location over a standard Ethernet fiber-optic cable. One end of the cable is connected to your router, the other to an Direct Connect router. With this connection in place, you can create virtual interfaces directly to the Cloud (for example, to Amazon EC2 and Amazon S3) and to Amazon VPC, bypassing Internet service providers in your network path. A connection provides access to all Regions except the China (Beijing) and (China) Ningxia Regions. Amazon Web Services resources in the China Regions can only be accessed through locations associated with those Regions.

AWS CodeStar This is the API reference for AWS CodeStar. This reference provides descriptions of the operations and data types for the AWS CodeStar API along with usage examples. You can use the AWS CodeStar API to work with: Projects and their resources, by calling the following: DeleteProject, which deletes a project. DescribeProject, which lists the attributes of a project. ListProjects, which lists all projects associated with your AWS account. ListResources, which lists the resources associated with a project. ListTagsForProject, which lists the tags associated with a project. TagProject, which adds tags to a project. UntagProject, which removes tags from a project. UpdateProject, which updates the attributes of a project. Teams and team members, by calling the following: AssociateTeamMember, which adds an IAM user to the team for a project. DisassociateTeamMember, which removes an IAM user from the team for a project. ListTeamMembers, which lists all the IAM users in the team for a project, including their roles and attributes. UpdateTeamMember, which updates a team member's attributes in a project. Users, by calling the following: CreateUserProfile, which creates a user profile that contains data associated with the user across all projects. DeleteUserProfile, which deletes all user profile information across all projects. DescribeUserProfile, which describes the profile of a user. ListUserProfiles, which lists all user profiles. UpdateUserProfile, which updates the profile for a user.

AWS Application Discovery Service AWS Application Discovery Service helps you plan application migration projects. It automatically identifies servers, virtual machines (VMs), and network dependencies in your on-premises data centers. For more information, see the AWS Application Discovery Service FAQ. Application Discovery Service offers three ways of performing discovery and collecting data about your on-premises servers: Agentless discovery is recommended for environments that use VMware vCenter Server. This mode doesn't require you to install an agent on each host. It does not work in non-VMware environments. Agentless discovery gathers server information regardless of the operating systems, which minimizes the time required for initial on-premises infrastructure assessment. Agentless discovery doesn't collect information about network dependencies, only agent-based discovery collects that information. Agent-based discovery collects a richer set of data than agentless discovery by using the AWS Application Discovery Agent, which you install on one or more hosts in your data center. The agent captures infrastructure and application information, including an inventory of running processes, system performance information, resource utilization, and network dependencies. The information collected by agents is secured at rest and in transit to the Application Discovery Service database in the cloud. AWS Partner Network (APN) solutions integrate with Application Discovery Service, enabling you to import details of your on-premises environment directly into Migration Hub without using the discovery connector or discovery agent. Third-party application discovery tools can query AWS Application Discovery Service, and they can write to the Application Discovery Service database using the public API. In this way, you can import data into Migration Hub and view it, so that you can associate applications with servers and track migrations. Recommendations We recommend that you use agent-based discovery for non-VMware environments, and whenever you want to collect information about network dependencies. You can run agent-based and agentless discovery simultaneously. Use agentless discovery to complete the initial infrastructure assessment quickly, and then install agents on select hosts to collect additional information. Working With This Guide This API reference provides descriptions, syntax, and usage examples for each of the actions and data types for Application Discovery Service. The topic for each action shows the API request parameters and the response. Alternatively, you can use one of the AWS SDKs to access an API that is tailored to the programming language or platform that you're using. For more information, see AWS SDKs. Remember that you must set your Migration Hub home region before you call any of these APIs. You must make API calls for write actions (create, notify, associate, disassociate, import, or put) while in your home region, or a HomeRegionNotSetException error is returned. API calls for read actions (list, describe, stop, and delete) are permitted outside of your home region. Although it is unlikely, the Migration Hub home region could change. If you call APIs outside the home region, an InvalidInputException is returned. You must call GetHomeRegion to obtain the latest Migration Hub home region. This guide is intended for use with the AWS Application Discovery Service User Guide. All data is handled according to the AWS Privacy Policy. You can operate Application Discovery Service offline to inspect collected data before it is shared with the service.

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.

API spec for Microsoft.Security (Azure Security Center) resource provider

Use these APIs to manage Visual Studio Team Services resources through the Azure Resource Manager. All task operations conform to the HTTP/1.1 protocol specification and each operation returns an x-ms-request-id header that can be used to obtain information about the request. You must make sure that requests made to these resources are secure. For more information, see https://docs.microsoft.com/en-us/rest/api/index.

Use these REST APIs for performing operations on logger entity Azure API Management deployment.The Logger entity in API Management represents an event sink that you can use to log API Management events. Currently the Logger entity supports logging API Management events to Azure EventHub.

Amazon API Gateway V2

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 Spell Check API - V7 lets you check a text string for spelling and grammar errors.

The Azure SQL Database management API provides a RESTful set of web APIs that interact with Azure SQL Database services to manage your databases. The API enables users to create, retrieve, update, and delete databases, servers, and other entities.

The Azure SQL Database management API provides a RESTful set of web APIs that interact with Azure SQL Database services to manage your databases. The API enables users to create, retrieve, update, and delete databases, servers, and other entities.

The Azure SQL Database management API provides a RESTful set of web APIs that interact with Azure SQL Database services to manage your databases. The API enables users to create, retrieve, update, and delete databases, servers, and other entities.

AWS Data Pipeline configures and manages a data-driven workflow called a pipeline. AWS Data Pipeline handles the details of scheduling and ensuring that data dependencies are met so that your application can focus on processing the data. AWS Data Pipeline provides a JAR implementation of a task runner called AWS Data Pipeline Task Runner. AWS Data Pipeline Task Runner provides logic for common data management scenarios, such as performing database queries and running data analysis using Amazon Elastic MapReduce (Amazon EMR). You can use AWS Data Pipeline Task Runner as your task runner, or you can write your own task runner to provide custom data management. AWS Data Pipeline implements two main sets of functionality. Use the first set to create a pipeline and define data sources, schedules, dependencies, and the transforms to be performed on the data. Use the second set in your task runner application to receive the next task ready for processing. The logic for performing the task, such as querying the data, running data analysis, or converting the data from one format to another, is contained within the task runner. The task runner performs the task assigned to it by the web service, reporting progress to the web service as it does so. When the task is done, the task runner reports the final success or failure of the task to the web service.

Amazon Elastic Container Registry Public Amazon Elastic Container Registry (Amazon ECR) is a managed container image registry service. Amazon ECR provides both public and private registries to host your container images. You 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 public repositories with this API. For information about the Amazon ECR API for private repositories, see Amazon Elastic Container Registry API Reference.

Provides APIs for creating and managing Amazon Forecast resources.