Contact Lens for Amazon Connect is a set of integrated ML analytics capabilities for Amazon Connect that gives contact centers the ability to understand the sentiment, trends, and compliance of customer conversations to improve customer experience and identify crucial customer feedback.

AWS Fargate now supports Fargate Spot, a new deployment option on AWS Fargate to run fault-tolerant applications with up to 70% discount compared to Fargate prices. Starting today, Fargate Spot is supported for applications orchestrated by Amazon ECS.  

Express Workflows are a new type of AWS Step Functions workflow type that cost-effectively orchestrate AWS compute, database, and messaging services at event rates greater than 100,000 events per second. Express Workflows automatically start in response to events such as HTTP requests via Amazon API Gateway, AWS Lambda requests, AWS IoT Rules Engine actions, and over 100 other AWS and SaaS event sources from Amazon EventBridge. Express Workflows is suitable for high-volume event processing workloads such as IoT data ingestion, streaming data processing and transformation, and high-volume microservices orchestration.

Today, Amazon Web Services (AWS) launched Amazon Rekognition Custom Labels, a new feature of Amazon Rekognition that enables customers to build their own machine learning (ML) based image analysis capabilities to detect unique objects and scenes, relevant to their business need. For example, customers using Amazon Rekognition to detect machine parts from images can now train a ML model with a small set of labeled images to detect “turbochargers” and “torque converters” without needing any ML expertise. Instead of having to train a model from scratch, which requires specialized machine learning expertise and millions of high-quality labeled images, customers can now use Amazon Rekognition Custom Labels to achieve state-of-the-art performance for their unique image analysis needs. 

Amazon RDS Proxy, a fully managed, highly available database proxy for Amazon Relational Database Service (RDS), is now available in preview. RDS Proxy makes applications more scalable, more resilient to database failures, and more secure.

We are announcing Provisioned Concurrency, a feature that provides customers greater control over performance of their serverless applications at any scale. Functions using Provisioned Concurrency execute with consistent start-up latency making them ideal for building interactive mobile or web backends, latency sensitive microservices, and synchronously invoked APIs.

AWS Security Hub now integrates with AWS Identity and Access Management (IAM) Access Analyzer. IAM Access Analyzer is an IAM feature that that makes it simple for security teams and administrators to check that their policies provide only the intended access to resources. The IAM Access Analyzer integration with Security Hub will send findings to Security Hub when policies allow public or cross-account access to resources. Security Hub will automatically enable this integration if you are already using IAM Access Analyzer, and you will begin receiving findings from IAM Access Analyzer without any action needed on your end. To learn more, visit the Integration page in the Security Hub console and click on the “Configuration” link for IAM Access Analyzer.

Amazon SageMaker Autopilot is now Generally Available. With this feature, Amazon SageMaker can use your tabular data and the target column you specify to automatically train and tune your model, while providing full visibility into the process. As the name suggests, you can use it on autopilot, deploying the model with the highest accuracy with one click in Amazon SageMaker Studio, or use it as a guide to decision making, enabling you to make tradeoffs, such as accuracy with latency or model size. 

Amazon SageMaker Studio is an integrated development environment (IDE) for machine learning (ML) that lets you easily build, train, debug, deploy and monitor your machine learning models.

Amazon Braket is a fully managed service that makes it easy for scientists, researchers, and developers to build, test, and run quantum computing algorithms. Amazon Braket helps you get started learning about quantum computing by providing a development environment to build quantum algorithms, test them on simulated quantum computers, and run them on your choice of different quantum hardware technologies.