Today we are excited to announce the general availability of EMR Studio, an integrated development environment (IDE) that makes it easy for data scientists and data engineers to develop, visualize, and debug big data and analytics applications written in R, Python, Scala, and PySpark. EMR Studio provides fully managed Jupyter Notebooks, and tools like Spark UI and YARN Timeline Service to simplify debugging. EMR Studio uses AWS Single Sign-On and allows you to log in directly with your corporate credentials without logging into the AWS console.

Today, Amazon Athena announced the general availability of a new capability that makes working with machine learning models as simple as running a SQL query. You can now build and deploy machine learning models in Amazon SageMaker and use SQL functions in Amazon Athena to generate predictions from your SageMaker models. This enables analytics teams to make model-driven insights available to business users and analysts without the need for specialized tools and infrastructure.

AWS Glue Studio is now available in the AWS Africa (Cape Town) Region. AWS Glue Studio is a visual interface for AWS Glue that makes it easy for extract-transform-and-load (ETL) developers to author, run, and monitor AWS Glue ETL jobs. You can now use a simple visual interface to compose jobs that move and transform data and run them on AWS Glue. You can then use AWS Glue Studio’s job run dashboard to monitor ETL execution and ensure that your jobs are operating as intended.

Today, we are announcing new functionality in AWS Control Tower that provides you the ability to customize your landing zone naming. You can retain the names that AWS Control Tower recommends for the organizational units (OUs) and core accounts, or you can modify these names during the initial landing zone set up process.

The AWS Solutions team recently updated Machine to Cloud Connectivity Framework, a solution that provides secure factory equipment connectivity to the AWS Cloud. This solution is a framework to send equipment telemetry data to your AWS account, allowing you to leverage AWS Services to conduct analysis on your equipment data instead of managing underlying infrastructure operations. The solution currently allows for robust data ingestion using either the OPC Data Access (OPC DA) protocol or the CC-Link Partner Association (CLPA) Seamless Messaging Protocol (SLMP). Support for OPC Unified Access (OPC UA) protocol will follow in the next release. 

IoT Resource Monitoring Framework is an AWS Solutions Consulting Offer delivered via a consulting engagement from Trek10, an AWS IoT Competency Partner. IoT Resource Monitoring Framework gives companies clear and constant visibility into their IoT device and backend operations from a single pane. Customers that request this consulting offer will participate in an engagement that delivers a discovery session, AWS infrastructure deployment, a dashboard with monitors and alerts, and an application design document.

The Amplify CLI now gives developers the ability to make multiple global secondary index (GSI) updates to their Amazon DynamoDB tables in a single deployment, enabling faster and safer data model iterations. AWS Amplify CLI is a command line toolchain that helps frontend web and mobile developers create cloud backends and connect them to their app for common use cases, like managing app data using AWS AppSync and Amazon DynamoDB.  

IAM helps customers with capabilities to analyze access and achieve least privilege. When you are working on new permissions for your teams, you can use IAM Access Analyzer policy generation to create a policy based on your access activity and set fine-grained permissions. To analyze and refine existing permissions, you can use last accessed information to identify unused actions in your IAM policies and reduce access. When we launched action last accessed in 2020, we started with S3 management actions to help you restrict access to your critical business data. Now, IAM is increasing visibility into access history by extending last accessed information to Amazon EC2, AWS IAM, and AWS Lambda management actions. This makes it easier for you to analyze access and reduce EC2, IAM, and Lambda permissions by providing the latest timestamp when an IAM user or role accessed an action. Using last accessed information, you can identify unused actions in your IAM policies and tighten permissions confidently.  

AWS CloudFormation StackSets extend the functionality of stacks by enabling you to create, update, or delete stacks across multiple AWS accounts and Regions with a single operation. We are now announcing the support for CloudFormation Macros and transforms in templates that are used to create a stack set. AWS CloudFormation macros perform custom processing on CloudFormation templates from simple actions such as find-and-replace, to helping transform the entire template. CloudFormation macros use the same technology that powers AWS::Include and AWS::Serverless transforms. CloudFormation transforms help simplify template authoring by condensing the expression of AWS infrastructure as code and enabling reuse of template components.

User Defined Functions (UDF), which enable users to apply custom operations to their data, are now generally available for Amazon Athena. While Athena provides a wide range of built-in functions, users can extend these capabilities with their own functions and use them directly within their queries. This allows users to address specific use cases, such as redacting or encrypting sensitive data, without the need for complex data processing steps elsewhere in their data pipeline.