Mock sample for your project: AWS Database Migration Service API

AWS CloudFormation CloudFormation allows you to create and manage Amazon Web Services infrastructure deployments predictably and repeatedly. You can use CloudFormation to leverage Amazon Web Services products, such as Amazon Elastic Compute Cloud, Amazon Elastic Block Store, Amazon Simple Notification Service, Elastic Load Balancing, and Auto Scaling to build highly-reliable, highly scalable, cost-effective applications without creating or configuring the underlying Amazon Web Services infrastructure. With CloudFormation, you declare all of your resources and dependencies in a template file. The template defines a collection of resources as a single unit called a stack. CloudFormation creates and deletes all member resources of the stack together and manages all dependencies between the resources for you. For more information about CloudFormation, see the CloudFormation Product Page. CloudFormation makes use of other Amazon Web Services products. If you need additional technical information about a specific Amazon Web Services product, you can find the product's technical documentation at docs.aws.amazon.com .

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.

Amazon Web Services Single Sign On (SSO) is a cloud SSO service that makes it easy to centrally manage SSO access to multiple Amazon Web Services accounts and business applications. This guide provides information on SSO operations which could be used for access management of Amazon Web Services accounts. For information about Amazon Web Services SSO features, see the Amazon Web Services Single Sign-On User Guide. Many operations in the SSO APIs rely on identifiers for users and groups, known as principals. For more information about how to work with principals and principal IDs in Amazon Web Services SSO, see the Amazon Web Services SSO Identity Store API Reference.

Amazon Polly is a web service that makes it easy to synthesize speech from text. The Amazon Polly service provides API operations for synthesizing high-quality speech from plain text and Speech Synthesis Markup Language (SSML), along with managing pronunciations lexicons that enable you to get the best results for your application domain.

Detective uses machine learning and purpose-built visualizations to help you analyze and investigate security issues across your Amazon Web Services (AWS) workloads. Detective automatically extracts time-based events such as login attempts, API calls, and network traffic from AWS CloudTrail and Amazon Virtual Private Cloud (Amazon VPC) flow logs. It also extracts findings detected by Amazon GuardDuty. The Detective API primarily supports the creation and management of behavior graphs. A behavior graph contains the extracted data from a set of member accounts, and is created and managed by an administrator account. Every behavior graph is specific to a Region. You can only use the API to manage graphs that belong to the Region that is associated with the currently selected endpoint. A Detective administrator account can use the Detective API to do the following: Enable and disable Detective. Enabling Detective creates a new behavior graph. View the list of member accounts in a behavior graph. Add member accounts to a behavior graph. Remove member accounts from a behavior graph. A member account can use the Detective API to do the following: View the list of behavior graphs that they are invited to. Accept an invitation to contribute to a behavior graph. Decline an invitation to contribute to a behavior graph. Remove their account from a behavior graph. All API actions are logged as CloudTrail events. See Logging Detective API Calls with CloudTrail. We replaced the term "master account" with the term "administrator account." An administrator account is used to centrally manage multiple accounts. In the case of Detective, the administrator account manages the accounts in their behavior graph.

Amazon Macie Classic Amazon Macie Classic is a security service that uses machine learning to automatically discover, classify, and protect sensitive data in AWS. Macie Classic recognizes sensitive data such as personally identifiable information (PII) or intellectual property, and provides you with dashboards and alerts that give visibility into how this data is being accessed or moved. For more information, see the Amazon Macie Classic User Guide.

This is the Amazon Lookout for Vision API Reference. It provides descriptions of actions, data types, common parameters, and common errors. Amazon Lookout for Vision enables you to find visual defects in industrial products, accurately and at scale. It uses computer vision to identify missing components in an industrial product, damage to vehicles or structures, irregularities in production lines, and even minuscule defects in silicon wafers — or any other physical item where quality is important such as a missing capacitor on printed circuit boards.

Amazon Connect is a cloud-based contact center solution that you use to set up and manage a customer contact center and provide reliable customer engagement at any scale. Amazon Connect provides metrics and real-time reporting that enable you to optimize contact routing. You can also resolve customer issues more efficiently by getting customers in touch with the appropriate agents. There are limits to the number of Amazon Connect resources that you can create. There are also limits to the number of requests that you can make per second. For more information, see Amazon Connect Service Quotas in the Amazon Connect Administrator Guide. You can connect programmatically to an AWS service by using an endpoint. For a list of Amazon Connect endpoints, see Amazon Connect Endpoints. Working with contact flows? Check out the Amazon Connect Flow language.

Direct Connect links your internal network to an Direct Connect location over a standard Ethernet fiber-optic cable. One end of the cable is connected to your router, the other to an Direct Connect router. With this connection in place, you can create virtual interfaces directly to the Cloud (for example, to Amazon EC2 and Amazon S3) and to Amazon VPC, bypassing Internet service providers in your network path. A connection provides access to all Regions except the China (Beijing) and (China) Ningxia Regions. Amazon Web Services resources in the China Regions can only be accessed through locations associated with those Regions.

AWS Mobile Service provides mobile app and website developers with capabilities required to configure AWS resources and bootstrap their developer desktop projects with the necessary SDKs, constants, tools and samples to make use of those resources.

The AWS Migration Hub home region APIs are available specifically for working with your Migration Hub home region. You can use these APIs to determine a home region, as well as to create and work with controls that describe the home region. You must make API calls for write actions (create, notify, associate, disassociate, import, or put) while in your home region, or a HomeRegionNotSetException error is returned. API calls for read actions (list, describe, stop, and delete) are permitted outside of your home region. If you call a write API outside the home region, an InvalidInputException is returned. You can call GetHomeRegion action to obtain the account's Migration Hub home region. For specific API usage, see the sections that follow in this AWS Migration Hub Home Region API reference.

The Azure Data Catalog Resource Provider Services API.

The Admin Backup Management Client.

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.

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.

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.

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.

Catalog API actions allow you to manage your entities through list, describe, and update capabilities. An entity can be a product or an offer on AWS Marketplace. You can automate your entity update process by integrating the AWS Marketplace Catalog API with your AWS Marketplace product build or deployment pipelines. You can also create your own applications on top of the Catalog API to manage your products on AWS Marketplace.

The Amazon AppIntegrations service enables you to configure and reuse connections to external applications. For information about how you can use external applications with Amazon Connect, see Set up pre-built integrations in the Amazon Connect Administrator Guide.

Amazon CloudFront This is the Amazon CloudFront API Reference. This guide is for developers who need detailed information about CloudFront API actions, data types, and errors. For detailed information about CloudFront features, see the Amazon CloudFront Developer Guide.

AWS Data Exchange is a service that makes it easy for AWS customers to exchange data in the cloud. You can use the AWS Data Exchange APIs to create, update, manage, and access file-based data set in the AWS Cloud. As a subscriber, you can view and access the data sets that you have an entitlement to through a subscription. You can use the APIS to download or copy your entitled data sets to Amazon S3 for use across a variety of AWS analytics and machine learning services. As a provider, you can create and manage your data sets that you would like to publish to a product. Being able to package and provide your data sets into products requires a few steps to determine eligibility. For more information, visit the AWS Data Exchange User Guide. A data set is a collection of data that can be changed or updated over time. Data sets can be updated using revisions, which represent a new version or incremental change to a data set. A revision contains one or more assets. An asset in AWS Data Exchange is a piece of data that can be stored as an Amazon S3 object. The asset can be a structured data file, an image file, or some other data file. Jobs are asynchronous import or export operations used to create or copy assets.

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.

IoT data IoT data enables secure, bi-directional communication between Internet-connected things (such as sensors, actuators, embedded devices, or smart appliances) and the Amazon Web Services cloud. It implements a broker for applications and things to publish messages over HTTP (Publish) and retrieve, update, and delete shadows. A shadow is a persistent representation of your things and their state in the Amazon Web Services cloud. Find the endpoint address for actions in IoT data by running this CLI command: aws iot describe-endpoint --endpoint-type iot:Data-ATS The service name used by Amazon Web ServicesSignature Version 4 to sign requests is: iotdevicegateway.