You can now package and deploy AWS Lambda functions as a container image of up to 10 GB. This makes it easy to build Lambda based applications using familiar container tooling, workflows, and dependencies. Just like functions packaged as ZIP archives, functions deployed as container images will benefit from AWS Lambda’s operational simplicity, automatic scaling with sub-second startup times, high availability, and native integrations with 140 AWS services. Customers can start building functions as container images by using either a set of AWS base images for Lambda, or by using one of their preferred community or enterprise images.

Amazon Elastic Kubernetes Service (Amazon EKS) now allows you to install and manage Kubernetes operational software (add-ons) as part of the Amazon EKS console, CLI, and API. Today, EKS supports managing the Amazon VPC CNI networking plugin , with more add-ons coming soon.

Amazon Elastic Kubernetes Service (EKS) Distro is the same Kubernetes distribution used by Amazon EKS for customers who create Kubernetes clusters manually wherever their applications are deployed. Amazon EKS Distro provides builds and code of open source Kubernetes, etcd, CoreDNS, upstream CNI Core binaries, CSI Sidecar Containers, and the latest security patches. Amazon EKS Distro is available as an open source project from GitHub and Amazon ECR Public Gallery .

Now in preview, AWS Glue Elastic Views is a new capability of AWS Glue that makes it easy to build materialized views that combine and replicate data across multiple data stores without you having to write custom code. With AWS Glue Elastic Views, you can use familiar Structured Query Language (SQL) to quickly create a virtual table—a materialized view—from multiple different source data stores. AWS Glue Elastic Views copies data from each source data store and creates a replica in a target data store. AWS Glue Elastic Views continuously monitors for changes to data in your source data stores, and provides updates to the materialized views in your target data stores automatically, ensuring data accessed through the materialized view is always up-to-date.

Contact Lens for Amazon Connect , launched at re:Invent 2019, provides a set of machine learning (ML) capabilities integrated into Amazon Connect that analyze call recordings or customer sentiment, trends, and compliance of conversations. Now, Contact Lens supports real-time call analytics capabilities, enabling you to detect customer issues during live calls and resolve them faster.

Amazon Lookout for Vision is a new machine learning service that enables you to find visual defects in industrial products, accurately and at scale. With Lookout for Vision you can automate real-time visual inspection with computer vision for processes like quality control and defect assessment – with no machine learning expertise required. It uses computer vision to identify missing components in products, damage to vehicles or structures, irregularities in production lines, and even miniscule defects in silicon wafers — or any other physical item where quality is important.  

Today, we are excited to announce Amazon Lookout for Equipment, a service which provides customers with existing sensors on their industrial equipment, a way to send their sensor data to AWS to build machine learning models for them and return predictions to detect abnormal equipment behavior. This enables predictive maintenance that allows them to take action before machine failures occur and avoid unplanned downtime. 

Amazon Connect Tasks improves agent productivity and lowers costs by empowering contact center managers to prioritize, assign, and track customer service tasks across the disparate applications used by agents. This includes tasks like following up on a case in a Customer Relationship Management (CRM) application such as Salesforce, or processing a claim in a business-specific application. You can also automate repetitive work by creating contact flows in Amazon Connect to automate action items that don’t require agent interaction (e.g., notifying a customer of an update on their case), so that agents can focus more of their time interacting with customers.

Today we are announcing preview of AWS Local Zones in Boston, Houston, and Miami, with plans to launch 12 additional AWS Local Zones throughout 2021 in key metro areas in the United States including Atlanta, Chicago, and New York. Using these new AWS Local Zones, customers will now be able to deliver ultra-low latency applications to end-users in cities across the continental United States.

We are excited to announce Amazon Monitron, an end-to-end system that uses machine learning (ML) to detect abnormal behavior in industrial machinery, enabling you to implement predictive maintenance and reduce unplanned downtime.