Today, I’m happy to introduce advanced AI/ML threat detection capabilities in Amazon GuardDuty. This new feature uses the extensive cloud visibility and scale of AWS to provide improved threat detection for your applications, workloads, and data. GuardDuty Extended Threat Detection employs sophisticated AI/ML to identify both known and previously unknown attack sequences, offering a more comprehensive and proactive approach to cloud security. This enhancement addresses the growing complexity of modern cloud environments and the evolving landscape of security threats, simplifying threat detection and response. Many organizations face challenges in efficiently analyzing and responding to the high volume of security events generated across their cloud environments. With the increasing frequency and sophistication of security threats, it has become more challenging to…
Container Insights with enhanced observability now available in Amazon ECS
Last year, we announced enhanced observability in Amazon CloudWatch Container Insights, a new capability to improve your observability for Amazon Elastic Kubernetes Service (Amazon EKS). This capability helps you detect and fix container issues faster by providing detailed performance metrics and logs. Expanding this capability, today we’re launching enhanced observability for your container workloads running on Amazon Elastic Container Service (Amazon ECS). This new capability will help reduce your mean time to detect (MTTD) and mean time to repair (MTTR) for your overall applications, helping prevent issues that could negatively impact your user experience. Here’s a quick look at Container Insights with enhanced observability for Amazon ECS. Container Insights with enhanced observability addresses a critical gap in container monitoring. Previously,…
AWS Clean Rooms now supports multiple clouds and data sources
Today, we are announcing support for Snowflake and Amazon Athena as new sources for AWS Clean Rooms data collaborations. AWS Clean Rooms helps you and your partners more seamlessly and securely analyze your collective datasets without sharing or copying one another’s underlying data. This enhancement helps you collaborate with datasets stored in Snowflake or those queryable through Athena features, such as AWS Lake Formation permissions or AWS Glue Data Catalog views, without moving or revealing the source data. You often need to collaborate with partners to analyze datasets to get insights for research and development, investments, or marketing and advertising campaigns. In some cases, your partners’ datasets are stored or managed outside of Amazon Simple Storage Service (Amazon S3), and…
New physical AWS Data Transfer Terminals let you upload to the cloud faster
Today, we’re announcing the general availability of AWS Data Transfer Terminal, a secure physical location where you can bring your storage devices and upload data faster to the AWS Cloud. The first Data Transfer Terminals are located in Los Angeles and New York, with plans to add more locations globally. You can reserve a time slot to visit your nearest location and upload data rapidly and securely to any AWS public endpoints, such as Amazon Simple Storage Service (Amazon S3), Amazon Elastic File System (Amazon EFS), or others, using a high throughput connection. Using AWS Data Transfer Terminal, you can significantly reduce the time of ingesting data with high throughput connectivity in the location near by you. You can upload…