You now can use AWS CloudTrail to log Amazon DynamoDB Streams data-plane APIs—GetRecords and GetShardIterator—to monitor and investigate item-level changes in your DynamoDB tables. Previously, you could use CloudTrail to log DynamoDB Streams control-plane activity (and not data-plane activity) on your DynamoDB tables.

IT admins and security teams can now view, analyze, and report on the patch compliance of their environment from a single dashboard using Patch Manager. The Patch Manager dashboard provides you with enhanced reporting capabilities and integrates key patching information such as non-compliant instances and instances never scanned for patches into a single pane of glass. It further enables you to troubleshoot issues easily by providing a drilled down view of patch compliance, enabling you to monitor missing patches and analyze execution logs. Using this feature, you can generate patch compliance reports on demand or on a schedule to simplify analysis and sharing of patch compliance information.  

Amazon Textract has achieved Federal Risk and Authorization Management Program (FedRAMP) High authorization, approved by the FedRAMP Joint Authorization Board (JAB), for the AWS GovCloud (US) Regions. Additionally, Amazon Textract is now authorized in the US East (N. Virginia), US East (Ohio), US West (N. California), and US West (Oregon) Regions under FedRAMP Moderate.

Today we are announcing Amazon SageMaker Savings Plans, a new flexible pricing model that allows you to save up to 64% on Amazon SageMaker ML instances in exchange for making a commitment to a consistent amount of eligible usage (e.g. $10/hour) for a 1- or 3-year term. We are also pleased to share that effective April 19th, 2021 we are reducing the prices by up to 14% for instances in Amazon SageMaker. The price reductions apply to instances families ml.t2, ml.t3, ml.m4, ml.m5, ml.m5d, ml.c4, ml.c5, ml.c5d, ml.c5n, ml.r5, ml.r5d, ml.inf1 and ml.g4dn for SageMaker Studio notebooks, SageMaker On-Demand Notebooks, SageMaker Processing, SageMaker Training, SageMaker Real-Time Inference, SageMaker Data Wrangler and SageMaker Batch Transform.

Amazon EMR Release 5.33 now supports 10 new instance types – C6gd, M6gd, R6gd, C6gn,C5a, C5ad, d3, d3en, m5zn and R5b. These instances are supported in all commercial regions where the instances are available. Amazon EMR 5.33 ships with Apache Hudi 0.7.0, ApacheFlink 1.12.1, PrestoDB 0.245 and Zeppelin 0.9.0.

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.