Mock sample for your project: Amazon AppIntegrations Service API

Amazon Web Services S3 Control provides access to Amazon S3 control plane actions.

Elastic Inference public APIs.

Welcome to the AWS Ground Station API Reference. AWS Ground Station is a fully managed service that enables you to control satellite communications, downlink and process satellite data, and scale your satellite operations efficiently and cost-effectively without having to build or manage your own ground station infrastructure.

Amazon FSx is a fully managed service that makes it easy for storage and application administrators to launch and use shared file storage.

AWS App Runner AWS App Runner is an application service that provides a fast, simple, and cost-effective way to go directly from an existing container image or source code to a running service in the AWS cloud in seconds. You don't need to learn new technologies, decide which compute service to use, or understand how to provision and configure AWS resources. App Runner connects directly to your container registry or source code repository. It provides an automatic delivery pipeline with fully managed operations, high performance, scalability, and security. For more information about App Runner, see the AWS App Runner Developer Guide. For release information, see the AWS App Runner Release Notes. To install the Software Development Kits (SDKs), Integrated Development Environment (IDE) Toolkits, and command line tools that you can use to access the API, see Tools for Amazon Web Services. Endpoints For a list of Region-specific endpoints that App Runner supports, see AWS App Runner endpoints and quotas in the AWS General Reference.

Welcome to the Amazon AppFlow API reference. This guide is for developers who need detailed information about the Amazon AppFlow API operations, data types, and errors. Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between software as a service (SaaS) applications like Salesforce, Marketo, Slack, and ServiceNow, and Amazon Web Services like Amazon S3 and Amazon Redshift. Use the following links to get started on the Amazon AppFlow API: Actions : An alphabetical list of all Amazon AppFlow API operations. Data types : An alphabetical list of all Amazon AppFlow data types. Common parameters : Parameters that all Query operations can use. Common errors : Client and server errors that all operations can return. If you're new to Amazon AppFlow, we recommend that you review the Amazon AppFlow User Guide. Amazon AppFlow API users can use vendor-specific mechanisms for OAuth, and include applicable OAuth attributes (such as auth-code and redirecturi) with the connector-specific ConnectorProfileProperties when creating a new connector profile using Amazon AppFlow API operations. For example, Salesforce users can refer to the Authorize Apps with OAuth documentation.

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.

Using the Amazon Cognito User Pools API, you can create a user pool to manage directories and users. You can authenticate a user to obtain tokens related to user identity and access policies. This API reference provides information about user pools in Amazon Cognito User Pools. For more information, see the Amazon Cognito Documentation.

AWS IoT Jobs is a service that allows you to define a set of jobs — remote operations that are sent to and executed on one or more devices connected to AWS IoT. For example, you can define a job that instructs a set of devices to download and install application or firmware updates, reboot, rotate certificates, or perform remote troubleshooting operations. To create a job, you make a job document which is a description of the remote operations to be performed, and you specify a list of targets that should perform the operations. The targets can be individual things, thing groups or both. AWS IoT Jobs sends a message to inform the targets that a job is available. The target starts the execution of the job by downloading the job document, performing the operations it specifies, and reporting its progress to AWS IoT. The Jobs service provides commands to track the progress of a job on a specific target and for all the targets of the job

AWS Auto Scaling Use AWS Auto Scaling to create scaling plans for your applications to automatically scale your scalable AWS resources. API Summary You can use the AWS Auto Scaling service API to accomplish the following tasks: Create and manage scaling plans Define target tracking scaling policies to dynamically scale your resources based on utilization Scale Amazon EC2 Auto Scaling groups using predictive scaling and dynamic scaling to scale your Amazon EC2 capacity faster Set minimum and maximum capacity limits Retrieve information on existing scaling plans Access current forecast data and historical forecast data for up to 56 days previous To learn more about AWS Auto Scaling, including information about granting IAM users required permissions for AWS Auto Scaling actions, see the AWS Auto Scaling User Guide.

Amazon Kinesis Data Streams Service API Reference Amazon Kinesis Data Streams is a managed service that scales elastically for real-time processing of streaming big data.

AWS Elastic Beanstalk AWS Elastic Beanstalk makes it easy for you to create, deploy, and manage scalable, fault-tolerant applications running on the Amazon Web Services cloud. For more information about this product, go to the AWS Elastic Beanstalk details page. The location of the latest AWS Elastic Beanstalk WSDL is https://elasticbeanstalk.s3.amazonaws.com/doc/2010-12-01/AWSElasticBeanstalk.wsdl. To install the Software Development Kits (SDKs), Integrated Development Environment (IDE) Toolkits, and command line tools that enable you to access the API, go to Tools for Amazon Web Services. Endpoints For a list of region-specific endpoints that AWS Elastic Beanstalk supports, go to Regions and Endpoints in the Amazon Web Services Glossary.

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.

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.

For more information about AWS CloudHSM, see AWS CloudHSM and the AWS CloudHSM User Guide.

The Amazon Chime API (application programming interface) is designed for developers to perform key tasks, such as creating and managing Amazon Chime accounts, users, and Voice Connectors. This guide provides detailed information about the Amazon Chime API, including operations, types, inputs and outputs, and error codes. It also includes some server-side API actions to use with the Amazon Chime SDK. For more information about the Amazon Chime SDK, see Using the Amazon Chime SDK in the Amazon Chime Developer Guide. You can use an AWS SDK, the AWS Command Line Interface (AWS CLI), or the REST API to make API calls. We recommend using an AWS SDK or the AWS CLI. Each API operation includes links to information about using it with a language-specific AWS SDK or the AWS CLI. Using an AWS SDK You don't need to write code to calculate a signature for request authentication. The SDK clients authenticate your requests by using access keys that you provide. For more information about AWS SDKs, see the AWS Developer Center. Using the AWS CLI Use your access keys with the AWS CLI to make API calls. For information about setting up the AWS CLI, see Installing the AWS Command Line Interface in the AWS Command Line Interface User Guide. For a list of available Amazon Chime commands, see the Amazon Chime commands in the AWS CLI Command Reference. Using REST APIs If you use REST to make API calls, you must authenticate your request by providing a signature. Amazon Chime supports signature version 4. For more information, see Signature Version 4 Signing Process in the Amazon Web Services General Reference. When making REST API calls, use the service name chime and REST endpoint https://service.chime.aws.amazon.com. Administrative permissions are controlled using AWS Identity and Access Management (IAM). For more information, see Identity and Access Management for Amazon Chime in the Amazon Chime Administration Guide.

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.

AWS License Manager AWS License Manager makes it easier to manage licenses from software vendors across multiple AWS accounts and on-premises servers.

Amazon Relational Database Service Amazon Relational Database Service (Amazon RDS) is a web service that makes it easier to set up, operate, and scale a relational database in the cloud. It provides cost-efficient, resizeable capacity for an industry-standard relational database and manages common database administration tasks, freeing up developers to focus on what makes their applications and businesses unique. Amazon RDS gives you access to the capabilities of a MySQL, MariaDB, PostgreSQL, Microsoft SQL Server, Oracle, or Amazon Aurora database server. These capabilities mean that the code, applications, and tools you already use today with your existing databases work with Amazon RDS without modification. Amazon RDS automatically backs up your database and maintains the database software that powers your DB instance. Amazon RDS is flexible: you can scale your DB instance's compute resources and storage capacity to meet your application's demand. As with all Amazon Web Services, there are no up-front investments, and you pay only for the resources you use. This interface reference for Amazon RDS contains documentation for a programming or command line interface you can use to manage Amazon RDS. Amazon RDS is asynchronous, which means that some interfaces might require techniques such as polling or callback functions to determine when a command has been applied. In this reference, the parameter descriptions indicate whether a command is applied immediately, on the next instance reboot, or during the maintenance window. The reference structure is as follows, and we list following some related topics from the user guide. Amazon RDS API Reference For the alphabetical list of API actions, see API Actions. For the alphabetical list of data types, see Data Types. For a list of common query parameters, see Common Parameters. For descriptions of the error codes, see Common Errors. Amazon RDS User Guide For a summary of the Amazon RDS interfaces, see Available RDS Interfaces. For more information about how to use the Query API, see Using the Query API.

Amazon EMR is a web service that makes it easier to process large amounts of data efficiently. Amazon EMR uses Hadoop processing combined with several Amazon Web Services services to do tasks such as web indexing, data mining, log file analysis, machine learning, scientific simulation, and data warehouse management.

The REST API specification for Ably.

Amazon Simple Notification Service Amazon Simple Notification Service (Amazon SNS) is a web service that enables you to build distributed web-enabled applications. Applications can use Amazon SNS to easily push real-time notification messages to interested subscribers over multiple delivery protocols. For more information about this product see the Amazon SNS product page. For detailed information about Amazon SNS features and their associated API calls, see the Amazon SNS Developer Guide. For information on the permissions you need to use this API, see Identity and access management in Amazon SNS in the Amazon SNS Developer Guide. We also provide SDKs that enable you to access Amazon SNS from your preferred programming language. The SDKs contain functionality that automatically takes care of tasks such as: cryptographically signing your service requests, retrying requests, and handling error responses. For a list of available SDKs, go to Tools for Amazon Web Services.

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.