Mock sample for your project: Amazon Polly API

Amazon Mobile Analytics is a service for collecting, visualizing, and understanding app usage data at scale.

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.

Identity and Access Management Identity and Access Management (IAM) is a web service for securely controlling access to Amazon Web Services services. With IAM, you can centrally manage users, security credentials such as access keys, and permissions that control which Amazon Web Services resources users and applications can access. For more information about IAM, see Identity and Access Management (IAM) and the Identity and Access Management User Guide.

Glue Defines the public endpoint for the Glue service.

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 Health The AWS Health API provides programmatic access to the AWS Health information that appears in the AWS Personal Health Dashboard. You can use the API operations to get information about AWS Health events that affect your AWS services and resources. You must have a Business or Enterprise Support plan from AWS Support to use the AWS Health API. If you call the AWS Health API from an AWS account that doesn't have a Business or Enterprise Support plan, you receive a SubscriptionRequiredException error. You can use the AWS Health endpoint health.us-east-1.amazonaws.com (HTTPS) to call the AWS Health API operations. AWS Health supports a multi-Region application architecture and has two regional endpoints in an active-passive configuration. You can use the high availability endpoint example to determine which AWS Region is active, so that you can get the latest information from the API. For more information, see Accessing the AWS Health API in the AWS Health User Guide. For authentication of requests, AWS Health uses the Signature Version 4 Signing Process. If your AWS account is part of AWS Organizations, you can use the AWS Health organizational view feature. This feature provides a centralized view of AWS Health events across all accounts in your organization. You can aggregate AWS Health events in real time to identify accounts in your organization that are affected by an operational event or get notified of security vulnerabilities. Use the organizational view API operations to enable this feature and return event information. For more information, see Aggregating AWS Health events in the AWS Health User Guide. When you use the AWS Health API operations to return AWS Health events, see the following recommendations: Use the eventScopeCode parameter to specify whether to return AWS Health events that are public or account-specific. Use pagination to view all events from the response. For example, if you call the DescribeEventsForOrganization operation to get all events in your organization, you might receive several page results. Specify the nextToken in the next request to return more results.

The operations for managing an Amazon MSK cluster.

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.

Amazon DocumentDB API documentation

AWS IoT Wireless API documentation

Amazon DynamoDB Amazon DynamoDB Streams provides API actions for accessing streams and processing stream records. To learn more about application development with Streams, see Capturing Table Activity with DynamoDB Streams in the Amazon DynamoDB Developer Guide.

Amplify enables developers to develop and deploy cloud-powered mobile and web apps. The Amplify Console provides a continuous delivery and hosting service for web applications. For more information, see the Amplify Console User Guide. The Amplify Framework is a comprehensive set of SDKs, libraries, tools, and documentation for client app development. For more information, see the Amplify Framework.

AWS Systems Manager Incident Manager is an incident management console designed to help users mitigate and recover from incidents affecting their AWS-hosted applications. An incident is any unplanned interruption or reduction in quality of services. Incident Manager increases incident resolution by notifying responders of impact, highlighting relevant troubleshooting data, and providing collaboration tools to get services back up and running. To achieve the primary goal of reducing the time-to-resolution of critical incidents, Incident Manager automates response plans and enables responder team escalation.

Infrastructure role instance operation endpoints and objects.

Amazon API Gateway V2

Logical network operation endpoints and objects.

Amazon Web Services Systems Manager is a collection of capabilities that helps you automate management tasks such as collecting system inventory, applying operating system (OS) patches, automating the creation of Amazon Machine Images (AMIs), and configuring operating systems (OSs) and applications at scale. Systems Manager lets you remotely and securely manage the configuration of your managed instances. A managed instance is any Amazon Elastic Compute Cloud instance (EC2 instance), or any on-premises server or virtual machine (VM) in your hybrid environment that has been configured for Systems Manager. This reference is intended to be used with the Amazon Web Services Systems Manager User Guide. To get started, verify prerequisites and configure managed instances. For more information, see Setting up Amazon Web Services Systems Manager in the Amazon Web Services Systems Manager User Guide. Related resources For information about how to use a Query API, see Making API requests. For information about other API operations you can perform on EC2 instances, see the Amazon EC2 API Reference. For information about AppConfig, a capability of Systems Manager, see the AppConfig User Guide and the AppConfig API Reference. For information about Incident Manager, a capability of Systems Manager, see the Incident Manager User Guide and the Incident Manager API Reference.

The Admin Gallery Management Client.

Use these REST APIs for performing retrieving a collection of policy snippets available in Azure API Management deployment.

Describes all of the AWS IoT 1-Click device-related API operations for the service.
Also provides sample requests, responses, and errors for the supported web services
protocols.

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.

The Admin Backup Management Client.