Mock sample for your project: AWS RDS DataService API

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.

An AWS Elemental MediaStore asset is an object, similar to an object in the Amazon S3 service. Objects are the fundamental entities that are stored in AWS Elemental MediaStore.

Cloud9 Cloud9 is a collection of tools that you can use to code, build, run, test, debug, and release software in the cloud. For more information about Cloud9, see the Cloud9 User Guide. Cloud9 supports these operations: CreateEnvironmentEC2 : Creates an Cloud9 development environment, launches an Amazon EC2 instance, and then connects from the instance to the environment. CreateEnvironmentMembership : Adds an environment member to an environment. DeleteEnvironment : Deletes an environment. If an Amazon EC2 instance is connected to the environment, also terminates the instance. DeleteEnvironmentMembership : Deletes an environment member from an environment. DescribeEnvironmentMemberships : Gets information about environment members for an environment. DescribeEnvironments : Gets information about environments. DescribeEnvironmentStatus : Gets status information for an environment. ListEnvironments : Gets a list of environment identifiers. ListTagsForResource : Gets the tags for an environment. TagResource : Adds tags to an environment. UntagResource : Removes tags from an environment. UpdateEnvironment : Changes the settings of an existing environment. UpdateEnvironmentMembership : Changes the settings of an existing environment member for an environment.

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.

AWS CloudFormation CloudFormation allows you to create and manage Amazon Web Services infrastructure deployments predictably and repeatedly. You can use CloudFormation to leverage Amazon Web Services products, such as Amazon Elastic Compute Cloud, Amazon Elastic Block Store, Amazon Simple Notification Service, Elastic Load Balancing, and Auto Scaling to build highly-reliable, highly scalable, cost-effective applications without creating or configuring the underlying Amazon Web Services infrastructure. With CloudFormation, you declare all of your resources and dependencies in a template file. The template defines a collection of resources as a single unit called a stack. CloudFormation creates and deletes all member resources of the stack together and manages all dependencies between the resources for you. For more information about CloudFormation, see the CloudFormation Product Page. CloudFormation makes use of other Amazon Web Services products. If you need additional technical information about a specific Amazon Web Services product, you can find the product's technical documentation at docs.aws.amazon.com .

The Amazon Braket API Reference provides information about the operations and structures supported in Amazon Braket.

AWS CodePipeline Overview This is the AWS CodePipeline API Reference. This guide provides descriptions of the actions and data types for AWS CodePipeline. Some functionality for your pipeline can only be configured through the API. For more information, see the AWS CodePipeline User Guide. You can use the AWS CodePipeline API to work with pipelines, stages, actions, and transitions. Pipelines are models of automated release processes. Each pipeline is uniquely named, and consists of stages, actions, and transitions. You can work with pipelines by calling: CreatePipeline, which creates a uniquely named pipeline. DeletePipeline, which deletes the specified pipeline. GetPipeline, which returns information about the pipeline structure and pipeline metadata, including the pipeline Amazon Resource Name (ARN). GetPipelineExecution, which returns information about a specific execution of a pipeline. GetPipelineState, which returns information about the current state of the stages and actions of a pipeline. ListActionExecutions, which returns action-level details for past executions. The details include full stage and action-level details, including individual action duration, status, any errors that occurred during the execution, and input and output artifact location details. ListPipelines, which gets a summary of all of the pipelines associated with your account. ListPipelineExecutions, which gets a summary of the most recent executions for a pipeline. StartPipelineExecution, which runs the most recent revision of an artifact through the pipeline. StopPipelineExecution, which stops the specified pipeline execution from continuing through the pipeline. UpdatePipeline, which updates a pipeline with edits or changes to the structure of the pipeline. Pipelines include stages. Each stage contains one or more actions that must complete before the next stage begins. A stage results in success or failure. If a stage fails, the pipeline stops at that stage and remains stopped until either a new version of an artifact appears in the source location, or a user takes action to rerun the most recent artifact through the pipeline. You can call GetPipelineState, which displays the status of a pipeline, including the status of stages in the pipeline, or GetPipeline, which returns the entire structure of the pipeline, including the stages of that pipeline. For more information about the structure of stages and actions, see AWS CodePipeline Pipeline Structure Reference. Pipeline stages include actions that are categorized into categories such as source or build actions performed in a stage of a pipeline. For example, you can use a source action to import artifacts into a pipeline from a source such as Amazon S3. Like stages, you do not work with actions directly in most cases, but you do define and interact with actions when working with pipeline operations such as CreatePipeline and GetPipelineState. Valid action categories are: Source Build Test Deploy Approval Invoke Pipelines also include transitions, which allow the transition of artifacts from one stage to the next in a pipeline after the actions in one stage complete. You can work with transitions by calling: DisableStageTransition, which prevents artifacts from transitioning to the next stage in a pipeline. EnableStageTransition, which enables transition of artifacts between stages in a pipeline. Using the API to integrate with AWS CodePipeline For third-party integrators or developers who want to create their own integrations with AWS CodePipeline, the expected sequence varies from the standard API user. To integrate with AWS CodePipeline, developers need to work with the following items: Jobs, which are instances of an action. For example, a job for a source action might import a revision of an artifact from a source. You can work with jobs by calling: AcknowledgeJob, which confirms whether a job worker has received the specified job. GetJobDetails, which returns the details of a job. PollForJobs, which determines whether there are any jobs to act on. PutJobFailureResult, which provides details of a job failure. PutJobSuccessResult, which provides details of a job success. Third party jobs, which are instances of an action created by a partner action and integrated into AWS CodePipeline. Partner actions are created by members of the AWS Partner Network. You can work with third party jobs by calling: AcknowledgeThirdPartyJob, which confirms whether a job worker has received the specified job. GetThirdPartyJobDetails, which requests the details of a job for a partner action. PollForThirdPartyJobs, which determines whether there are any jobs to act on. PutThirdPartyJobFailureResult, which provides details of a job failure. PutThirdPartyJobSuccessResult, which provides details of a job success.

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

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.

Amazon ElastiCache Amazon ElastiCache is a web service that makes it easier to set up, operate, and scale a distributed cache in the cloud. With ElastiCache, customers get all of the benefits of a high-performance, in-memory cache with less of the administrative burden involved in launching and managing a distributed cache. The service makes setup, scaling, and cluster failure handling much simpler than in a self-managed cache deployment. In addition, through integration with Amazon CloudWatch, customers get enhanced visibility into the key performance statistics associated with their cache and can receive alarms if a part of their cache runs hot.

Amazon WorkMail is a secure, managed business email and calendaring service with support for existing desktop and mobile email clients. You can access your email, contacts, and calendars using Microsoft Outlook, your browser, or other native iOS and Android email applications. You can integrate WorkMail with your existing corporate directory and control both the keys that encrypt your data and the location in which your data is stored. The WorkMail API is designed for the following scenarios: Listing and describing organizations Managing users Managing groups Managing resources All WorkMail API operations are Amazon-authenticated and certificate-signed. They not only require the use of the AWS SDK, but also allow for the exclusive use of AWS Identity and Access Management users and roles to help facilitate access, trust, and permission policies. By creating a role and allowing an IAM user to access the WorkMail site, the IAM user gains full administrative visibility into the entire WorkMail organization (or as set in the IAM policy). This includes, but is not limited to, the ability to create, update, and delete users, groups, and resources. This allows developers to perform the scenarios listed above, as well as give users the ability to grant access on a selective basis using the IAM model.

This is the Resource Access Manager API Reference. This documentation provides descriptions and syntax for each of the actions and data types in RAM. RAM is a service that helps you securely share your Amazon Web Services resources across Amazon Web Services accounts and within your organization or organizational units (OUs) in Organizations. For supported resource types, you can also share resources with IAM roles and IAM users. If you have multiple Amazon Web Services accounts, you can use RAM to share those resources with other accounts. To learn more about RAM, see the following resources: Resource Access Manager product page Resource Access Manager User Guide

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.

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 Elastic Compute Cloud Amazon Elastic Compute Cloud (Amazon EC2) provides secure and resizable computing capacity in the AWS Cloud. Using Amazon EC2 eliminates the need to invest in hardware up front, so you can develop and deploy applications faster. Amazon Virtual Private Cloud (Amazon VPC) enables you to provision a logically isolated section of the AWS Cloud where you can launch AWS resources in a virtual network that you've defined. Amazon Elastic Block Store (Amazon EBS) provides block level storage volumes for use with EC2 instances. EBS volumes are highly available and reliable storage volumes that can be attached to any running instance and used like a hard drive. To learn more, see the following resources: Amazon EC2: AmazonEC2 product page, Amazon EC2 documentation Amazon EBS: Amazon EBS product page, Amazon EBS documentation Amazon VPC: Amazon VPC product page, Amazon VPC documentation AWS VPN: AWS VPN product page, AWS VPN documentation

The Admin Subscriptions Management Client.

Amazon Mechanical Turk API Reference

Drive operation endpoints and objects.

AWS Marketplace Metering Service This reference provides descriptions of the low-level AWS Marketplace Metering Service API. AWS Marketplace sellers can use this API to submit usage data for custom usage dimensions. For information on the permissions you need to use this API, see AWS Marketing metering and entitlement API permissions in the AWS Marketplace Seller Guide. Submitting Metering Records MeterUsage - Submits the metering record for a Marketplace product. MeterUsage is called from an EC2 instance or a container running on EKS or ECS. BatchMeterUsage - Submits the metering record for a set of customers. BatchMeterUsage is called from a software-as-a-service (SaaS) application. Accepting New Customers ResolveCustomer - Called by a SaaS application during the registration process. When a buyer visits your website during the registration process, the buyer submits a Registration Token through the browser. The Registration Token is resolved through this API to obtain a CustomerIdentifier and Product Code. Entitlement and Metering for Paid Container Products Paid container software products sold through AWS Marketplace must integrate with the AWS Marketplace Metering Service and call the RegisterUsage operation for software entitlement and metering. Free and BYOL products for Amazon ECS or Amazon EKS aren't required to call RegisterUsage, but you can do so if you want to receive usage data in your seller reports. For more information on using the RegisterUsage operation, see Container-Based Products. BatchMeterUsage API calls are captured by AWS CloudTrail. You can use Cloudtrail to verify that the SaaS metering records that you sent are accurate by searching for records with the eventName of BatchMeterUsage. You can also use CloudTrail to audit records over time. For more information, see the AWS CloudTrail User Guide .

The WorkDocs API is designed for the following use cases: File Migration: File migration applications are supported for users who want to migrate their files from an on-premises or off-premises file system or service. Users can insert files into a user directory structure, as well as allow for basic metadata changes, such as modifications to the permissions of files. Security: Support security applications are supported for users who have additional security needs, such as antivirus or data loss prevention. The API actions, along with AWS CloudTrail, allow these applications to detect when changes occur in Amazon WorkDocs. Then, the application can take the necessary actions and replace the target file. If the target file violates the policy, the application can also choose to email the user. eDiscovery/Analytics: General administrative applications are supported, such as eDiscovery and analytics. These applications can choose to mimic or record the actions in an Amazon WorkDocs site, along with AWS CloudTrail, to replicate data for eDiscovery, backup, or analytical applications. All Amazon WorkDocs API actions are Amazon authenticated and certificate-signed. They not only require the use of the AWS SDK, but also allow for the exclusive use of IAM users and roles to help facilitate access, trust, and permission policies. By creating a role and allowing an IAM user to access the Amazon WorkDocs site, the IAM user gains full administrative visibility into the entire Amazon WorkDocs site (or as set in the IAM policy). This includes, but is not limited to, the ability to modify file permissions and upload any file to any user. This allows developers to perform the three use cases above, as well as give users the ability to grant access on a selective basis using the IAM model.

Logical network operation endpoints and objects.

Use these REST APIs for performing operations on Email Templates associated with your Azure API Management deployment.

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 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.