Amazon QuickSight now supports connectivity to Exasol, a high-performance, in-memory, MPP database designed for analytics. QuickSight’s new data connector allows business users to directly connect, analyze and report on the data in Exasol using a live connection, or import data from Exasol into QuickSight’s SPICE in-memory engine for scaling access to 1000s of users. 

Today, we are announcing three new enhancements for AWS IoT SiteWise that make it easier for customers to collect data from industrial equipment at scale. The new enhancements reduce the number of steps required to ingest equipment data to the cloud, and add flexibility for customers modeling their physical operations using AWS IoT SiteWise asset models and assets.

Elastic Beanstalk now supports AWS Graviton-based Amazon Elastic Compute Cloud (Amazon EC2) instance types. AWS Graviton is an arm64-based processor built by Amazon that provides up to 40% better price-performance over a comparable x86-based processor. AWS Graviton on Elastic Beanstalk enables customers to benefit from the superior price-performance of arm64-based processors along with the ease-of-use of Elastic Beanstalk.

Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation. Amazon Translate now supports Amazon Virtual Private Cloud (VPC) endpoints via AWS PrivateLink so you can securely initiate API calls to Amazon Translate from within your VPC and without using public IPs. AWS PrivateLink provides private connectivity between VPCs and AWS services, without ever leaving the Amazon network, significantly simplifying your internal network architecture. You no longer need to use an Internet Gateway, Network Address Translation (NAT) devices or firewall proxies to connect to Amazon Translate.

AWS App Runner now supports GitHub Actions to build and deploy applications. GitHub Actions provide a way to implement complex orchestration and CI/CD functionality directly in GitHub by initiating a workflow on any GitHub event. If you have your source code in a GitHub repository, you can use GitHub Actions to enable App Runner to build a Docker image based on the language runtime and to deploy your application based on the generated image. For supported runtimes on App Runner, refer to the documentation . If you already have a container image of your application in a GitHub repository, you can use GitHub Actions to directly use the image to deploy your application on App Runner.

The Amazon Chime SDK lets developers add real-time audio, video, screen-sharing, and messaging capabilities to their web or mobile applications. The Amazon Chime SDK now offers machine learning (ML) based echo reduction to help improve audio experiences. Acoustic echoes disrupt meetings or conference calls when the sound played by the loudspeaker is picked up by the microphone and it circulates back into the call. The new ML-based echo reduction capability is designed to reduce acoustic echoes and preserve voice quality during double-talk conditions, when two or more people speak at the same time.

Starting today, your IPv6 AWS resources in Amazon Virtual Private Cloud (VPC) can use NAT64 (on AWS NAT Gateway) and DNS64 (on Amazon Route 53 Resolver) to communicate with IPv4 services. As you transition your workloads to IPv6 networks, they would continue to need access to IPv4 network and services. With NAT64 and DNS64, your IPv6 resources can communicate with IPv4 services within the same VPC or connected VPCs, your on-premises networks, or the Internet.

Amazon Redshift support for GEOGRAPHY data type is now available for spatial analytics. GEOGRAPHY data type is used in queries requiring higher precision results for spatial data with geographic features that can be represented with a spheroid model of the Earth and referenced using latitude and longitude as spatial coordinate system.

With Amazon EC2 Auto Scaling’s new predictive scaling policy, you can now use custom metrics to predict the EC2 instance capacity needed by an Auto Scaling group. Predictive scaling proactively increases the capacity of an Auto Scaling group to meet predicted demand. For workloads that experience recurring, steep demand changes, predictive scaling can help improve your application’s responsiveness without having to overprovision capacity, resulting in lower EC2 costs. Custom metrics are useful when the predefined metrics (CPU Utilization, Network I/O, and ALB Request Count) are not sufficient to capture the load on your application. Previously, you could only use custom metrics with step scaling and target tracking, but you can now use them with predictive scaling as well.

AWS today announced AWS WAF Captcha to help block unwanted bot traffic by requiring users to successfully complete challenges before their web request are allowed to reach AWS WAF protected resources. Captcha is an acronym for Completely Automated Public Turing test to tell Computers and Humans Apart and is commonly used to distinguish between robotic and human visitors to prevent activity like web scraping, credential stuffing, and spam. You can configure AWS WAF rules to require WAF Captcha challenges to be solved for specific resources that are frequently targeted by bots such as login, search, and form submissions. You can also require WAF Captcha challenges for suspicious requests based on the rate, attributes, or labels generated from AWS Managed Rules, such as AWS WAF Bot Control or the Amazon IP Reputation list. WAF Captcha challenges are simple for humans while remaining effective against bots. WAF Captcha includes an audio version and is designed to meet WCAG accessibility requirements.