AWS Direct Connect makes it easy to establish resilient network connectivity from your premises to AWS. Using AWS Direct Connect, you can establish private connectivity between AWS and your data center, office, or colocation environment, which in many cases can reduce your network costs, increase bandwidth throughput, and provide a more consistent network experience than connections over the public internet.

AWS Auto Scaling with scaling plans and predictive scaling (for Amazon EC2) is now available in 7 additional AWS Regions. Using AWS Auto Scaling, customers can configure predictive scaling to automatically scale their Amazon EC2 Auto Scaling groups in advance of impending traffic changes. Customers can also use AWS Auto Scaling to manage scaling configuration for multiple resources with a single scaling plan for services such as Amazon EC2, Amazon ECS, Amazon DynamoDB, and Amazon Aurora.

Amazon Redshift now processes queries 2x faster when they need to be compiled. This improvement gives you better query performance when you create a new Redshift cluster, onboard a new workload on an existing cluster, or after a software update of an existing cluster. These query performance improvements are available at no extra charge to you, and no action is needed to enable it on your clusters.  

Today, Amazon Athena has released a new feature that allows you to connect Athena to your Apache Hive Metastore. 

Amazon FSx, a fully managed service that makes it easy to launch and run feature-rich and highly-performant file systems, is now available in the AWS Asia Pacific (Mumbai) Region. With Amazon FSx, customers can leverage the rich feature sets and fast performance of widely-used open source and commercially-licensed file systems, while avoiding time-consuming administrative tasks like hardware provisioning, software configuration, patching, and backups. 

You can now restrict the amount of disk space used by a schema in Amazon Redshift. With the CREATE and ALTER SCHEMA statement, administrators can set quotas on the maximum amount of storage consumed by schemas. 

Today, we announced the public preview of Amazon SageMaker Components for Kubeflow Pipelines . Machine learning (ML) developers using Kubeflow Pipelines can convert their existing pipeline steps to run on SageMaker with the SageMaker Components. For instance, ML teams can use SageMaker for managed training on Spot instances which will automatically set up model checkpoints to S3 so that you can pause and resume training from the last saved state. Other SageMaker features that are supported in Kubeflow Pipelines are built-in algorithms, managed distributed training, and hyperparameter tuning. In addition, SageMaker can change instance types with one parameter swap, replacing the complicated autoscaling config in Kubernetes.

Today, Amazon Web Services (AWS) announced Amazon Textract, a machine learning service that quickly and easily extracts text and data from forms and tables in scanned documents, can now be used for workloads that are subject to Service Organization Control (SOC) compliance, and International Organization for Standardization (ISO) compliance. This launch builds upon the existing portfolio of AWS machine learning services that are SOC and ISO compliant, including Amazon Sagemaker, Amazon Rekognition, Amazon Comprehend, Amazon Lex, and Amazon Connect. The AWS compliance program continues to enable our global customer base to maintain confidence in our secured control environments with a focus on information security, confidentiality, and availability.

Amazon FSx for Windows File Server now enables you to increase the storage capacity and to change the throughput capacity of your file systems with the click of a button, providing you the flexibility to grow your file storage and to scale up or down the available performance as needed to meet evolving storage needs over time. 

Amazon DynamoDB support for empty values for non-key String and Binary attributes in DynamoDB tables is now available in the AWS GovCloud (US) Regions. Empty value support gives you greater flexibility to use attributes for a broader set of use cases without having to transform such attributes before sending them to DynamoDB. List, Map, and Set data types also support empty String and Binary values.