Today, AWS announces the general availability of AWS Amplify Studio Figma-to-React code capabilities, giving frontend developers a faster workflow for building full-stack apps. These new capabilities add to existing Amplify Studio backend creation and management capabilities, helping developers accelerate UI development. Typically, there is a lot of back and forth between frontend developers and designers, which can lead to suboptimal end-user experiences because of compromises made to ship on time. With Amplify Studio, developing UI as per design is as easy as “import from Figma, export to code, and extend code with custom logic.”

Amazon Aurora Serverless v2, the next version of Aurora Serverless, is now generally available. Aurora Serverless v2 scales instantly to support even the most demanding applications, delivering up to 90% cost savings compared to provisioning for peak capacity.

AWS Glue Studio Job Notebooks are now generally available, providing interactive, notebook-based job authoring in AWS Glue. They help simplify the process of developing data integration jobs. Job Notebooks also provide a serverless, built-in interface for AWS Glue Interactive Sessions, another new feature that allows customers to run interactive Apache Spark workloads on demand.

AWS Glue Interactive Sessions are now generally available. They provide a new interface into AWS Glue’s highly scalable Serverless Spark environment. They support interactive data integration job development, data exploration, and on-demand distributed data processing for customers’ own applications.

Sensitive data detection and processing in AWS Glue is now generally available. This feature uses pattern matching and machine learning to automatically detect Personal Identifiable Information (PII) and other sensitive data at both the column and cell levels during an AWS Glue job run. AWS Glue includes options to log the type of PII and its location as well as to take action on it.

Auto Scaling in AWS Glue Apache Spark jobs is now generally available. AWS Glue 3.0 can now dynamically scale resources up and down based on the workload. With Auto Scaling, you no longer need to worry about over-provisioning resources for jobs, spend time optimizing the number of workers, or pay for idle workers.

Amazon QuickSight now supports 1-click public embedding, a feature that allows you to embed your dashboards into public applications, wikis, and portals without any coding or development. Once enabled, anyone on the internet can start accessing these embedded dashboards with to up-to-date information instantly, without server deployments or infrastructure licensing needed! 1-click public embedding helps you empower your end users with access to insights in seconds. To access this feature in preview please contact quicksight-public-embedding-preview@amazon.com.

Amazon Textract is a machine learning service that automatically extracts text, handwriting, and data from any document or image. Textract now provides you the flexibility to specify the data you need to extract from documents using the new Queries features within Analyze Document API. You do not need to know the structure of the data in the document (table, form, implied field, nested data) or worry about variations across document versions and formats. Queries leverages a combination of visual, spatial, and language cues to extract the information you seek with high accuracy.

Today, we are excited to announce general availability of Amazon SageMaker Serverless Inference in all AWS Regions where SageMaker is generally available (except the AWS China regions). With SageMaker Serverless Inference, you can quickly deploy machine learning (ML) models for inference without having to configure or manage the underlying infrastructure. When deploying your ML models, simply select the serverless option and Amazon SageMaker automatically provisions, scales, and turns off compute capacity based on the volume of inference requests. With SageMaker Serverless Inference, you pay only for the compute capacity used to process inference requests (billed by the millisecond) and the amount of data processed; you do not pay for idle time. SageMaker Serverless Inference is ideal for applications with intermittent or unpredictable traffic.

Today we are announcing the general availability of 10 new data source connectors for Amazon Athena. With Athena, you can query data stored in relational, non-relational, object, and custom data sources without the need for ETL scripts to pre-process or copy data. This release expands the number of data sources you can query with Athena and helps analysts, data engineers, data scientists, and developers unlock business value from data stored in databases running on-premises or in the cloud.