Atlassian Managed Hosting is an AWS Solutions Consulting Offer delivered via a consulting engagement from kreuzwerker, an AWS DevOps Competency Partner. Atlassian Managed Hosting allows customers to run all Atlassian server-deployed applications on AWS. Customers that request this consulting offer will participate in an engagement that delivers an assessment of existing data, onboarding, and testing to prepare for migration, product migration, and postmigration support.

Amazon Textract, a machine learning service, extracts text and other data from documents as well as tables and forms. Today, we are pleased to announce two new features:

• Amazon Textract now supports recognition of handwritten text from documents such as healthcare forms, prescriptions, dispute letters, tax documents, income documents, checks, claims, academic papers and many more. You can use the Detect Document Text or Analyze Document APIs to process images or PDF’s of scanned documents and extract both printed text and handwriting making it easy for you to automate almost any scanned document processing. You can also use Amazon Augmented AI (Amazon A2I), another AWS service, which makes it easy to build the workflows for human review of the machine learning predictions. You can log in to the Amazon Textract console to test out the handwriting feature, or check out the new demo by Amazon Machine Learning Hero Mike Chambers . 
• Amazon Textract now supports processing of documents with printed text in Spanish, German, Italian, Portuguese, and French. You can start sending documents in these languages for text extraction, and Amazon Textract will automatically detect and extract the information for you.

Amazon Kendra is a highly accurate and easy to use intelligent search service powered by machine learning. Starting today, AWS customers using Amazon Kendra can easily validate the identity of individual users, as well as user groups who perform searches with the addition of secure search tokens.  

Patches 1.7.6 / 2.5.6 / 3.2.6 are now available for customers using Amazon Aurora PostgreSQL. For detailed release notes visit our version documentation . You can apply the new patch version in the AWS Management Console, via the AWS CLI, or via the RDS API. For detailed instructions, please see our technical documentation .  

The EKS Construct Library is an AWS CDK module that helps customers provision Amazon EKS clusters using infrastructure-as-code best practices. Up until now, it has been in an experimental state, incorporating lots of customer feedback and undergoing multiple API and behavioral changes. Starting from version 1.65.0 (https://github.com/aws/aws-cdk/releases/tag/v1.65.0), the library is graduating to Developer Preview. This means that we are not planning any breaking changes going forward and are preparing the library for GA.

Today, we are excited to announce the AWS DeepRacer League’s 2020 season is nearing the final lap with the Championship at AWS re:Invent 2020. From November 10 through December 15, there are three ways to join in the racing fun: learn how to develop a competitive reinforcement learning model through our sessions, enter and compete in the racing action for a chance to win prizes, and watch to cheer on other developers as they race for the cup. More than 100 racers have already qualified for the Championship Cup, but there is still time to compete. Log in today to qualify for a chance to win the Championship Cup by entering the Wildcard round, offering the top 5 racers spots in the Knockout Rounds.

Starting today, Amazon Augmented AI (Amazon A2I) is a HIPAA eligible service. Amazon Augmented AI makes it easy to build the workflows required for human review of ML predictions. HIPPA eligibility applies to AWS Regions where the service is available and means you can use Amazon A2I to help you add human review of Protected Health Information (PHI) to power your healthcare workflows through your private workforce.

AWS Shield Advanced now allows you to bundle resources into protection groups, giving you a self-service way to customize the scope of detection and mitigation for your application by treating multiple resources as a single unit. Resource grouping improves the accuracy of detection, reduces false positives, eases automatic protection of newly created resources, and accelerates the time to mitigate attacks against multiple resources. For example, if an application consists of four CloudFront distributions, you can add them to one protection group to receive detection and protection for the collection of resources as a whole. Reporting can be consumed at the protection group level, in addition to the resource level, giving a more holistic view of overall application health.

AWS Step Functions is now integrated with Amazon EKS, making it easier to build resilient applications that orchestrate jobs running on Kubernetes with AWS services such as AWS Lambda, Amazon SNS, and Amazon SQS with minimal code. You can now build workflows including steps that launch tasks in Amazon EKS and wait for its completion without writing code to manage the state of the Kubernetes job.  

Today we are excited to announce that Amazon SageMaker Studio now supports multi-GPU instances of ml.g4dn.12xlarge, ml.p3.8xlarge, and ml.p3.16xlarge. Multi-GPU instances accelerate machine learning model training significantly, allowing users to train more advanced machine learning models that are too large to fit into a single GPU. They also provide the flexibility to process larger batches of data such as 4k images for image classification and object detection.