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Amazon SageMaker is a fully managed machine learning service. With Amazon SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don't have to manage servers. It also provides common machine learning algorithms that are optimized to run efficiently against extremely large data in a distributed environment. With native support for bring-your-own-algorithms and frameworks, Amazon SageMaker offers flexible distributed training options that adjust to your specific workflows. Deploy a model into a secure and scalable environment by launching it with a single click from the Amazon SageMaker console. Training and hosting are billed by minutes of usage, with no minimum fees and no upfront commitments.

Amazon Elastic Container Registry (Amazon ECR) is a managed AWS Docker registry service that is secure, scalable, and reliable. Amazon ECR supports private Docker repositories with resource-based permissions using AWS IAM so that specific users or Amazon EC2 instances can access repositories and images. Developers can use the Docker CLI to push, pull, and manage images.

Amazon Rekognition makes it easy to add image and video analysis to your applications. You just provide an image or video to the Rekognition API, and the service can identify objects, people, text, scenes, and activities. It can detect any inappropriate content as well. Amazon Rekognition also provides highly accurate facial analysis and facial recognition. You can detect, analyze, and compare faces for a wide variety of use cases, including user verification, cataloging, people counting, and public safety.Amazon Rekognition is based on the same proven, highly scalable, deep learning technology developed by Amazon's computer vision scientists to analyze billions of images and videos daily-and requires no machine learning expertise to use. Amazon Rekognition includes a simple, easy-to-use API that can quickly analyze any image or video file that's stored in Amazon S3. Amazon Rekognition is always learning from new data, and we're continually adding new labels and facial recognition features to the service.

Amazon Kinesis Data Firehose is a fully managed service for delivering real-time streaming data to destinations such as Amazon Simple Storage Service (Amazon S3), Amazon Redshift, Amazon Elasticsearch Service (Amazon ES), and Splunk. Kinesis Data Firehose is part of the Kinesis streaming data platform, along with Kinesis Streams and Amazon Kinesis Data Analytics. With Kinesis Data Firehose, you don't need to write applications or manage resources. You configure your data producers to send data to Kinesis Data Firehose, and it automatically delivers the data to the destination that you specified. You can also configure Kinesis Data Firehose to transform your data before delivering it.

AWS X-Ray is a service that collects data about requests that your application serves, and provides tools you can use to view, filter, and gain insights into that data to identify issues and opportunities for optimization. For any traced request to your application, you can see detailed information not only about the request and response, but also about calls that your application makes to downstream AWS resources, microservices, databases and HTTP web APIs.

Amazon WorkDocs is a fully managed, secure, enterprise storage and sharing service with strong administrative controls and feedback capabilities that improve user productivity. Your files are stored in the cloud, safely and securely. Amazon WorkDocs even includes a synchronization application that always keeps selected folders on your local computer in sync with your cloud folders. Your files are only visible to you, and your designated contributors and viewers. Other members of your organization do not have access to any of your files unless you specifically grant them access. You can share your files with other members of your organization for collaboration or review. The Amazon WorkDocs client applications can be used to view many different types of files, depending on the Internet media type of the file. Amazon WorkDocs supports all common document and image formats, and support for additional media types is constantly being added.

You can use Amazon Route 53 to help you get a website or web application up and running. Route 53 performs three main functions: Register domain names - Your website needs a name, such as example.com. Route 53 lets you registera name for your website or web application, known as a domain name. For an overview, see How Domain Registration Works. Route internet traffic to the resources for your domain - When a user opens a web browser and enters your domain name in the address bar, Route 53 helps the Domain Name System (DNS) connect the browser with your website or web application. For an overview, see How Internet Traffic Is Routed to Your Website or Web Application. Check the health of your resources - Route 53 sends automated requests over the internet to a resource, such as a web server, to verify that it's reachable, available, and functional. You also can choose to receive notifications when a resource becomes unavailable and choose to route internet traffic away from unhealthy resources. For an overview, see How Amazon Route 53 Checks the Health of Your Resources. You can use any combination of these functions. For example, you can use Route 53 both to register your domain name and to route internet traffic for the domain, or you can use Route 53 to route internet traffic for a domain that you registered with another domain registrar. If you choose to use Route 53 for all three functions, you register your domain name, then configure Route 53 to route internet traffic for your domain, and finally configure Route 53 to check the health of your resources.

AWS Elemental MediaStore is a video origination and storage service that offers the high performance and immediate consistency required for live origination. With AWS Elemental MediaStore, you can manage video assets as objects in containers to build dependable, cloud-based media workflows.To use the service, you upload your objects from a source, such as an encoder or data feed, to a container that you create in AWS Elemental MediaStore.AWS Elemental MediaStore is a great choice for storing fragmented video files when you need strong consistency, low-latency reads and writes, and the ability to handle high volumes of concurrent requests.

Amazon Elastic Container Service (Amazon ECS) is a highly scalable, fast, container management service that makes it easy to run, stop, and manage Docker containers on a cluster. You can host your cluster on a serverless infrastructure that is managed by Amazon ECS by launching your services or tasks using the Fargate launch type. For more control you can host your tasks on a cluster of Amazon Elastic Compute Cloud (Amazon EC2) instances that you manage by using the EC2 launch type. For more information about launch types, see Amazon ECS Launch Types.Amazon ECS lets you launch and stop container-based applications with simple API calls, allows you to get the state of your cluster from a centralized service, and gives you access to many familiar Amazon EC2 features.You can use Amazon ECS to schedule the placement of containers across your cluster based on your resource needs, isolation policies, and availability requirements. Amazon ECS eliminates the need for you to operate your own cluster management and configuration management systems or worry about scaling your management infrastructure.Amazon ECS can be used to create a consistent deployment and build experience, manage, and scale batch and Extract-Transform-Load (ETL) workloads, and build sophisticated application architectures on a microservices model. For more information about Amazon ECS use cases and scenarios, see Container Use Cases.