Mock sample for your project: Amazon QLDB Session API

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Amazon QLDB Session

amazonaws.com

Version: 2019-07-11


Use this API in your project

Speed up your application development by using "Amazon QLDB Session API" ready-to-use mock sample. Mocking this API will allow you to start working in no time. No more accounts to create, API keys to provision, accesses to configure, unplanned downtime, just work.
It also improves your integration tests' quality and reliability by accounting for random failures, slow response time, etc.

Description

The transactional data APIs for Amazon QLDB Instead of interacting directly with this API, we recommend using the QLDB driver or the QLDB shell to execute data transactions on a ledger. If you are working with an AWS SDK, use the QLDB driver. The driver provides a high-level abstraction layer above this QLDB Session data plane and manages SendCommand API calls for you. For information and a list of supported programming languages, see Getting started with the driver in the Amazon QLDB Developer Guide. If you are working with the AWS Command Line Interface (AWS CLI), use the QLDB shell. The shell is a command line interface that uses the QLDB driver to interact with a ledger. For information, see Accessing Amazon QLDB using the QLDB shell.

Other APIs by amazonaws.com

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Amazon Augmented AI Runtime

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.

AWS CodeDeploy

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 Cost Explorer Service

You can use the Cost Explorer API to programmatically query your cost and usage data. You can query for aggregated data such as total monthly costs or total daily usage. You can also query for granular data. This might include the number of daily write operations for Amazon DynamoDB database tables in your production environment. Service Endpoint The Cost Explorer API provides the following endpoint: https://ce.us-east-1.amazonaws.com For information about the costs that are associated with the Cost Explorer API, see Amazon Web Services Cost Management Pricing.

AWS Device Farm

Welcome to the AWS Device Farm API documentation, which contains APIs for: Testing on desktop browsers Device Farm makes it possible for you to test your web applications on desktop browsers using Selenium. The APIs for desktop browser testing contain TestGrid in their names. For more information, see Testing Web Applications on Selenium with Device Farm. Testing on real mobile devices Device Farm makes it possible for you to test apps on physical phones, tablets, and other devices in the cloud. For more information, see the Device Farm Developer Guide.

Amazon CloudWatch

Amazon CloudWatch monitors your Amazon Web Services (Amazon Web Services) resources and the applications you run on Amazon Web Services in real time. You can use CloudWatch to collect and track metrics, which are the variables you want to measure for your resources and applications. CloudWatch alarms send notifications or automatically change the resources you are monitoring based on rules that you define. For example, you can monitor the CPU usage and disk reads and writes of your Amazon EC2 instances. Then, use this data to determine whether you should launch additional instances to handle increased load. You can also use this data to stop under-used instances to save money. In addition to monitoring the built-in metrics that come with Amazon Web Services, you can monitor your own custom metrics. With CloudWatch, you gain system-wide visibility into resource utilization, application performance, and operational health.

AWS OpsWorks

AWS OpsWorks Welcome to the AWS OpsWorks Stacks API Reference. This guide provides descriptions, syntax, and usage examples for AWS OpsWorks Stacks actions and data types, including common parameters and error codes. AWS OpsWorks Stacks is an application management service that provides an integrated experience for overseeing the complete application lifecycle. For information about this product, go to the AWS OpsWorks details page. SDKs and CLI The most common way to use the AWS OpsWorks Stacks API is by using the AWS Command Line Interface (CLI) or by using one of the AWS SDKs to implement applications in your preferred language. For more information, see: AWS CLI AWS SDK for Java AWS SDK for .NET AWS SDK for PHP 2 AWS SDK for Ruby AWS SDK for Node.js AWS SDK for Python(Boto) Endpoints AWS OpsWorks Stacks supports the following endpoints, all HTTPS. You must connect to one of the following endpoints. Stacks can only be accessed or managed within the endpoint in which they are created. opsworks.us-east-1.amazonaws.com opsworks.us-east-2.amazonaws.com opsworks.us-west-1.amazonaws.com opsworks.us-west-2.amazonaws.com opsworks.ca-central-1.amazonaws.com (API only; not available in the AWS console) opsworks.eu-west-1.amazonaws.com opsworks.eu-west-2.amazonaws.com opsworks.eu-west-3.amazonaws.com opsworks.eu-central-1.amazonaws.com opsworks.ap-northeast-1.amazonaws.com opsworks.ap-northeast-2.amazonaws.com opsworks.ap-south-1.amazonaws.com opsworks.ap-southeast-1.amazonaws.com opsworks.ap-southeast-2.amazonaws.com opsworks.sa-east-1.amazonaws.com Chef Versions When you call CreateStack, CloneStack, or UpdateStack we recommend you use the ConfigurationManager parameter to specify the Chef version. The recommended and default value for Linux stacks is currently 12. Windows stacks use Chef 12.2. For more information, see Chef Versions. You can specify Chef 12, 11.10, or 11.4 for your Linux stack. We recommend migrating your existing Linux stacks to Chef 12 as soon as possible.

Amazon Personalize Events

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AWS CodeStar Notifications

This AWS CodeStar Notifications API Reference provides descriptions and usage examples of the operations and data types for the AWS CodeStar Notifications API. You can use the AWS CodeStar Notifications API to work with the following objects: Notification rules, by calling the following: CreateNotificationRule, which creates a notification rule for a resource in your account. DeleteNotificationRule, which deletes a notification rule. DescribeNotificationRule, which provides information about a notification rule. ListNotificationRules, which lists the notification rules associated with your account. UpdateNotificationRule, which changes the name, events, or targets associated with a notification rule. Subscribe, which subscribes a target to a notification rule. Unsubscribe, which removes a target from a notification rule. Targets, by calling the following: DeleteTarget, which removes a notification rule target (SNS topic) from a notification rule. ListTargets, which lists the targets associated with a notification rule. Events, by calling the following: ListEventTypes, which lists the event types you can include in a notification rule. Tags, by calling the following: ListTagsForResource, which lists the tags already associated with a notification rule in your account. TagResource, which associates a tag you provide with a notification rule in your account. UntagResource, which removes a tag from a notification rule in your account. For information about how to use AWS CodeStar Notifications, see link in the CodeStarNotifications User Guide.

Amazon Detective

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Amazon CodeGuru Reviewer

This section provides documentation for the Amazon CodeGuru Reviewer API operations. CodeGuru Reviewer is a service that uses program analysis and machine learning to detect potential defects that are difficult for developers to find and recommends fixes in your Java and Python code. By proactively detecting and providing recommendations for addressing code defects and implementing best practices, CodeGuru Reviewer improves the overall quality and maintainability of your code base during the code review stage. For more information about CodeGuru Reviewer, see the Amazon CodeGuru Reviewer User Guide. To improve the security of your CodeGuru Reviewer API calls, you can establish a private connection between your VPC and CodeGuru Reviewer by creating an interface VPC endpoint. For more information, see CodeGuru Reviewer and interface VPC endpoints (Amazon Web Services PrivateLink) in the Amazon CodeGuru Reviewer User Guide.

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Other APIs in the same category

AWS Database Migration Service

Database Migration Service Database Migration Service (DMS) can migrate your data to and from the most widely used commercial and open-source databases such as Oracle, PostgreSQL, Microsoft SQL Server, Amazon Redshift, MariaDB, Amazon Aurora, MySQL, and SAP Adaptive Server Enterprise (ASE). The service supports homogeneous migrations such as Oracle to Oracle, as well as heterogeneous migrations between different database platforms, such as Oracle to MySQL or SQL Server to PostgreSQL. For more information about DMS, see What Is Database Migration Service? in the Database Migration Service User Guide.

ApiManagementClient

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AzureDigitalTwinsManagementClient

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NetworkManagementClient

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AuthorizationManagementClient

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AWSMarketplace Metering

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Amazon WorkMail

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.