Mock sample for your project: AWS Amplify API

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 DocumentDB API documentation

IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight. Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources. IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.

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

Elastic Load Balancing A load balancer can distribute incoming traffic across your EC2 instances. This enables you to increase the availability of your application. The load balancer also monitors the health of its registered instances and ensures that it routes traffic only to healthy instances. You configure your load balancer to accept incoming traffic by specifying one or more listeners, which are configured with a protocol and port number for connections from clients to the load balancer and a protocol and port number for connections from the load balancer to the instances. Elastic Load Balancing supports three types of load balancers: Application Load Balancers, Network Load Balancers, and Classic Load Balancers. You can select a load balancer based on your application needs. For more information, see the Elastic Load Balancing User Guide. This reference covers the 2012-06-01 API, which supports Classic Load Balancers. The 2015-12-01 API supports Application Load Balancers and Network Load Balancers. To get started, create a load balancer with one or more listeners using CreateLoadBalancer. Register your instances with the load balancer using RegisterInstancesWithLoadBalancer. All Elastic Load Balancing operations are idempotent, which means that they complete at most one time. If you repeat an operation, it succeeds with a 200 OK response code.

Amazon Kendra is a service for indexing large document sets.

AWS Elastic Transcoder Service The AWS Elastic Transcoder Service.

Amazon Kinesis Data Firehose API Reference Amazon Kinesis Data Firehose is a fully managed service that delivers real-time streaming data to destinations such as Amazon Simple Storage Service (Amazon S3), Amazon Elasticsearch Service (Amazon ES), Amazon Redshift, and Splunk.

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.

Provides APIs for creating and managing Amazon Forecast resources.

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.

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.

The DevTest Labs Client.

Glue Defines the public endpoint for the Glue service.

This is the Amazon Rekognition API reference.

Amazon EMR on EKS provides a deployment option for Amazon EMR that allows you to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). With this deployment option, you can focus on running analytics workloads while Amazon EMR on EKS builds, configures, and manages containers for open-source applications. For more information about Amazon EMR on EKS concepts and tasks, see What is Amazon EMR on EKS. Amazon EMR containers is the API name for Amazon EMR on EKS. The emr-containers prefix is used in the following scenarios: It is the prefix in the CLI commands for Amazon EMR on EKS. For example, aws emr-containers start-job-run. It is the prefix before IAM policy actions for Amazon EMR on EKS. For example,"Action": [ "emr-containers:StartJobRun"]. For more information, see Policy actions for Amazon EMR on EKS. It is the prefix used in Amazon EMR on EKS service endpoints. For example, emr-containers.us-east-2.amazonaws.com. For more information, see Amazon EMR on EKS Service Endpoints.

Amazon CloudSearch Configuration Service You use the Amazon CloudSearch configuration service to create, configure, and manage search domains. Configuration service requests are submitted using the AWS Query protocol. AWS Query requests are HTTP or HTTPS requests submitted via HTTP GET or POST with a query parameter named Action. The endpoint for configuration service requests is region-specific: cloudsearch. region.amazonaws.com. For example, cloudsearch.us-east-1.amazonaws.com. For a current list of supported regions and endpoints, see Regions and Endpoints.

Amazon Cloud Directory Amazon Cloud Directory is a component of the AWS Directory Service that simplifies the development and management of cloud-scale web, mobile, and IoT applications. This guide describes the Cloud Directory operations that you can call programmatically and includes detailed information on data types and errors. For information about Cloud Directory features, see AWS Directory Service and the Amazon Cloud Directory Developer 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.

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.

Welcome to the Audit Manager API reference. This guide is for developers who need detailed information about the Audit Manager API operations, data types, and errors. Audit Manager is a service that provides automated evidence collection so that you can continuously audit your Amazon Web Services usage, and assess the effectiveness of your controls to better manage risk and simplify compliance. Audit Manager provides pre-built frameworks that structure and automate assessments for a given compliance standard. Frameworks include a pre-built collection of controls with descriptions and testing procedures, which are grouped according to the requirements of the specified compliance standard or regulation. You can also customize frameworks and controls to support internal audits with unique requirements. Use the following links to get started with the Audit Manager API: Actions : An alphabetical list of all Audit Manager API operations. Data types : An alphabetical list of all Audit Manager 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 Audit Manager, we recommend that you review the Audit Manager User Guide.

This is the Firewall Manager API Reference. This guide is for developers who need detailed information about the Firewall Manager API actions, data types, and errors. For detailed information about Firewall Manager features, see the Firewall Manager Developer Guide. Some API actions require explicit resource permissions. For information, see the developer guide topic Firewall Manager required permissions for API actions.

The AWS Cost and Usage Report API enables you to programmatically create, query, and delete AWS Cost and Usage report definitions. AWS Cost and Usage reports track the monthly AWS costs and usage associated with your AWS account. The report contains line items for each unique combination of AWS product, usage type, and operation that your AWS account uses. You can configure the AWS Cost and Usage report to show only the data that you want, using the AWS Cost and Usage API. Service Endpoint The AWS Cost and Usage Report API provides the following endpoint: cur.us-east-1.amazonaws.com