Mock sample for your project: Amazon Kinesis Video Streams API

AppSync provides API actions for creating and interacting with data sources using GraphQL from your application.

AWS IoT Greengrass seamlessly extends AWS onto physical devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage. AWS IoT Greengrass ensures your devices can respond quickly to local events and operate with intermittent connectivity. AWS IoT Greengrass minimizes the cost of transmitting data to the cloud by allowing you to author AWS Lambda functions that execute locally.

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.

Amazon Web Services Certificate Manager You can use Amazon Web Services Certificate Manager (ACM) to manage SSL/TLS certificates for your Amazon Web Services-based websites and applications. For more information about using ACM, see the Amazon Web Services Certificate Manager User 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 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.

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.

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.

DataSync DataSync is a managed data transfer service that makes it simpler for you to automate moving data between on-premises storage and Amazon Simple Storage Service (Amazon S3) or Amazon Elastic File System (Amazon EFS). This API interface reference for DataSync contains documentation for a programming interface that you can use to manage DataSync.

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

This section provides documentation for the Amazon CodeGuru Profiler API operations. Amazon CodeGuru Profiler collects runtime performance data from your live applications, and provides recommendations that can help you fine-tune your application performance. Using machine learning algorithms, CodeGuru Profiler can help you find your most expensive lines of code and suggest ways you can improve efficiency and remove CPU bottlenecks. Amazon CodeGuru Profiler provides different visualizations of profiling data to help you identify what code is running on the CPU, see how much time is consumed, and suggest ways to reduce CPU utilization. Amazon CodeGuru Profiler currently supports applications written in all Java virtual machine (JVM) languages and Python. While CodeGuru Profiler supports both visualizations and recommendations for applications written in Java, it can also generate visualizations and a subset of recommendations for applications written in other JVM languages and Python. For more information, see What is Amazon CodeGuru Profiler in the Amazon CodeGuru Profiler User Guide.

Alexa for Business helps you use Alexa in your organization. Alexa for Business provides you with the tools to manage Alexa devices, enroll your users, and assign skills, at scale. You can build your own context-aware voice skills using the Alexa Skills Kit and the Alexa for Business API operations. You can also make these available as private skills for your organization. Alexa for Business makes it efficient to voice-enable your products and services, thus providing context-aware voice experiences for your customers. Device makers building with the Alexa Voice Service (AVS) can create fully integrated solutions, register their products with Alexa for Business, and manage them as shared devices in their organization.

Identity and Access Management Access Analyzer helps identify potential resource-access risks by enabling you to identify any policies that grant access to an external principal. It does this by using logic-based reasoning to analyze resource-based policies in your Amazon Web Services environment. An external principal can be another Amazon Web Services account, a root user, an IAM user or role, a federated user, an Amazon Web Services service, or an anonymous user. You can also use IAM Access Analyzer to preview and validate public and cross-account access to your resources before deploying permissions changes. This guide describes the Identity and Access Management Access Analyzer operations that you can call programmatically. For general information about IAM Access Analyzer, see Identity and Access Management Access Analyzer in the IAM User Guide. To start using IAM Access Analyzer, you first need to create an analyzer.

The APIs listed in this specification can be used to manage Deployment Scripts resource through the Azure Resource Manager.

Use these REST APIs to get the analytics reports associated with your Azure API Management deployment.

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

The Admin Subscriptions Management Client.

Use these REST APIs for performing operations on NamedValue entity associated with your Azure API Management deployment. API Management policies are a powerful capability of the system that allow the publisher to change the behavior of the API through configuration. Policies are a collection of statements that are executed sequentially on the request or response of an API. Policy statements can be constructed using literal text values, policy expressions, and NamedValues. Each API Management service instance has a NamedValues collection of key/value pairs that are global to the service instance. These NamedValues can be used to manage constant string values across all API configuration and policies.

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

Alexa for Business helps you use Alexa in your organization. Alexa for Business provides you with the tools to manage Alexa devices, enroll your users, and assign skills, at scale. You can build your own context-aware voice skills using the Alexa Skills Kit and the Alexa for Business API operations. You can also make these available as private skills for your organization. Alexa for Business makes it efficient to voice-enable your products and services, thus providing context-aware voice experiences for your customers. Device makers building with the Alexa Voice Service (AVS) can create fully integrated solutions, register their products with Alexa for Business, and manage them as shared devices in their organization.

Use these REST APIs for performing operations on Global Policies in Azure API Management deployment.

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.