Mock sample for your project: AWS Route53 Recovery Readiness API

The AWS Serverless Application Repository makes it easy for developers and enterprises to quickly find
and deploy serverless applications in the AWS Cloud. For more information about serverless applications,
see Serverless Computing and Applications on the AWS website. The AWS Serverless Application Repository is deeply integrated with the AWS Lambda console, so that developers of
all levels can get started with serverless computing without needing to learn anything new. You can use category
keywords to browse for applications such as web and mobile backends, data processing applications, or chatbots.
You can also search for applications by name, publisher, or event source. To use an application, you simply choose it,
configure any required fields, and deploy it with a few clicks. You can also easily publish applications, sharing them publicly with the community at large, or privately
within your team or across your organization. To publish a serverless application (or app), you can use the
AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDKs to upload the code. Along with the
code, you upload a simple manifest file, also known as the AWS Serverless Application Model (AWS SAM) template.
For more information about AWS SAM, see AWS Serverless Application Model (AWS SAM) on the AWS Labs
GitHub repository. The AWS Serverless Application Repository Developer Guide contains more information about the two developer
experiences available:
Consuming Applications – Browse for applications and view information about them, including
source code and readme files. Also install, configure, and deploy applications of your choosing.
Publishing Applications – Configure and upload applications to make them available to other
developers, and publish new versions of applications.

AWS IoT Core Device Advisor is a cloud-based, fully managed test capability for validating IoT devices during device software development. Device Advisor provides pre-built tests that you can use to validate IoT devices for reliable and secure connectivity with AWS IoT Core before deploying devices to production. By using Device Advisor, you can confirm that your devices can connect to AWS IoT Core, follow security best practices and, if applicable, receive software updates from IoT Device Management. You can also download signed qualification reports to submit to the AWS Partner Network to get your device qualified for the AWS Partner Device Catalog without the need to send your device in and wait for it to be tested.

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 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.

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.

Amazon Connect is a cloud-based contact center solution that makes it easy to set up and manage a customer contact center and provide reliable customer engagement at any scale. Amazon Connect enables customer contacts through voice or chat. The APIs described here are used by chat participants, such as agents and customers.

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.

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.

Amazon Elasticsearch Configuration Service Use the Amazon Elasticsearch Configuration API to create, configure, and manage Elasticsearch domains. For sample code that uses the Configuration API, see the Amazon Elasticsearch Service Developer Guide. The guide also contains sample code for sending signed HTTP requests to the Elasticsearch APIs. The endpoint for configuration service requests is region-specific: es. region.amazonaws.com. For example, es.us-east-1.amazonaws.com. For a current list of supported regions and endpoints, see Regions and Endpoints.

EC2 Image Builder is a fully managed Amazon Web Services service that makes it easier to automate the creation, management, and deployment of customized, secure, and up-to-date "golden" server images that are pre-installed and pre-configured with software and settings to meet specific IT standards.

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.

Amazon Elastic Kubernetes Service (Amazon EKS) is a managed service that makes it easy for you to run Kubernetes on Amazon Web Services without needing to stand up or maintain your own Kubernetes control plane. Kubernetes is an open-source system for automating the deployment, scaling, and management of containerized applications. Amazon EKS runs up-to-date versions of the open-source Kubernetes software, so you can use all the existing plugins and tooling from the Kubernetes community. Applications running on Amazon EKS are fully compatible with applications running on any standard Kubernetes environment, whether running in on-premises data centers or public clouds. This means that you can easily migrate any standard Kubernetes application to Amazon EKS without any code modification required.

AWS Elastic Transcoder Service The AWS Elastic Transcoder Service.

Use these REST APIs for performing operations on Identity Provider entity associated with your Azure API Management deployment. Setting up an external Identity Provider for authentication can help you manage the developer portal logins using the OAuth2 flow.

Scale unit node operation endpoints and objects.

Amazon S3 Glacier (Glacier) is a storage solution for "cold data." Glacier is an extremely low-cost storage service that provides secure, durable, and easy-to-use storage for data backup and archival. With Glacier, customers can store their data cost effectively for months, years, or decades. Glacier also enables customers to offload the administrative burdens of operating and scaling storage to AWS, so they don't have to worry about capacity planning, hardware provisioning, data replication, hardware failure and recovery, or time-consuming hardware migrations. Glacier is a great storage choice when low storage cost is paramount and your data is rarely retrieved. If your application requires fast or frequent access to your data, consider using Amazon S3. For more information, see Amazon Simple Storage Service (Amazon S3). You can store any kind of data in any format. There is no maximum limit on the total amount of data you can store in Glacier. If you are a first-time user of Glacier, we recommend that you begin by reading the following sections in the Amazon S3 Glacier Developer Guide : What is Amazon S3 Glacier - This section of the Developer Guide describes the underlying data model, the operations it supports, and the AWS SDKs that you can use to interact with the service. Getting Started with Amazon S3 Glacier - The Getting Started section walks you through the process of creating a vault, uploading archives, creating jobs to download archives, retrieving the job output, and deleting archives.

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.

Azure Bot Service is a platform for creating smart conversational agents.

AWS Elemental MediaConvert

Azure Application Insights client for Components.

Amazon MQ is a managed message broker service for Apache ActiveMQ and RabbitMQ that makes it easy to set up and operate message brokers in the cloud. A message broker allows software applications and components to communicate using various programming languages, operating systems, and formal messaging protocols.

Amazon EventBridge helps you to respond to state changes in your Amazon Web Services resources. When your resources change state, they automatically send events to an event stream. You can create rules that match selected events in the stream and route them to targets to take action. You can also use rules to take action on a predetermined schedule. For example, you can configure rules to: Automatically invoke an Lambda function to update DNS entries when an event notifies you that Amazon EC2 instance enters the running state. Direct specific API records from CloudTrail to an Amazon Kinesis data stream for detailed analysis of potential security or availability risks. Periodically invoke a built-in target to create a snapshot of an Amazon EBS volume. For more information about the features of Amazon EventBridge, see the Amazon EventBridge User Guide.