Infineon and Swoboda are developing current sensor modules for automotive traction inverters and battery management systems. The deal combines Infineon’s sensor ICs with Swoboda’s expertise in sensor modules, and the …

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You can now use Amazon EC2 instances reserved using Capacity Blocks for ML natively in Amazon EKS clusters with managed node groups. EKS managed node groups make it easy to run highly-available and secure Kubernetes clusters by automating the provisioning and lifecycle of cluster worker nodes. EC2 Capacity Blocks provide you with assured and predictable access to GPU instances for your artificial intelligence / machine learning (AI/ML) workloads.

Customers increasingly choose Kubernetes as the platform for their AI/ML workloads and Amazon EKS lets them combine the benefits of Kubernetes with the security, scalability, and availability of the AWS cloud. Native support for EC2 Capacity Blocks in Amazon EKS simplifies capacity planning for cutting-edge AI/ML workloads in Kubernetes clusters, helping to ensure that GPU capacity is available when and where it’s needed. To get started, create an EKS managed node group with an EC2 Launch Template targeting a Capacity Block reservation so that the reserved GPU capacity will be accessible in the EKS cluster when the reservation becomes active. EC2 Capacity Blocks can be reserved up to eight weeks in advance and for just the amount of time that you require the instances.

Native EKS support for EC2 Capacity Blocks via managed node groups is available in the US East (Ohio), US East (N. Virginia), and US West (Oregon) AWS Regions . Read more about Amazon EKS support for EC2 Capacity Blocks for ML in the Amazon EKS User Guide .
 

Amazon MQ now provides support for RabbitMQ version 3.13, which includes several fixes and performance improvements to the previous versions of RabbitMQ supported by Amazon MQ. Starting from RabbitMQ 3.13, Amazon MQ will manage patch version upgrades for your brokers. All brokers on version 3.13 will be automatically upgraded to the latest compatible and secure patch version in your scheduled maintenance window.

If you are running earlier versions of RabbitMQ, such as 3.8, 3.9, 3.10, 3.11 or 3.12, we strongly encourage you to upgrade to RabbitMQ 3.13. This can be accomplished with just a few clicks in the AWS Management Console . Amazon MQ for RabbitMQ will soon end support for RabbitMQ versions 3.8, 3.9 and 3.10. To learn more about upgrading, see Managing Amazon MQ for RabbitMQ engine versions in the Amazon MQ Developer Guide. To learn more about the changes in RabbitMQ 3.13, see the Amazon MQ release notes . This version is available in all the regions Amazon MQ is available in. For a full list of available regions see the AWS Region Table .
 

We are excited to announce that AWS now supports cross-subnet communication between Elastic Fabric Adapter (EFA) interfaces for Amazon EC2 instances within the same Availability Zone (AZ). This enhancement makes it possible to communicate with EC2 instances across subnets while benefiting from the low latency and high throughput provided by EFA. EFA is a network device that you can attach to your Amazon EC2 instance to accelerate High Performance Computing (HPC) and Machine Learning (ML) applications.

Previously, EFA traffic was limited to the same subnet, thus requiring all instances to be configured within a single subnet. With this update, you have the option to send traffic over EFA across subnets for both existing and new instances. To take advantage of this capability, you need to configure your security group rules to allow traffic to and from security groups of instances from other subnets. You will also need to ensure your application configuration and orchestration logic accounts for hosts from other subnets when provisioning and managing EFA-enabled instances to communicate across subnets over EFA.

The cross-subnet communication support over EFA is available in all AWS commercial regions, the AWS GovCloud (US) regions, and the Amazon Web Services China (Beijing) region, operated by Sinnet, and the Amazon Web Services China (Ningxia) region, operated by NWCD. For more information about EFA, please visit EFA documentation page .
 

Today, Amazon Web Services, Inc. launches the general availability of Amazon Q Developer in the Visual Studio IDE, available as part of the AWS Toolkit extension. You can now chat with Amazon Q about your project and ask Amazon Q to scan your project for security vulnerabilities.

Amazon Q Developer helps simplify the software development lifecycle by answering questions about technical topics, generating code, and explaining code. You can ask Amazon Q to answer questions such as “How do I debug issues with my Lambda functions locally before deploying to AWS?”. You can also request Amazon Q to generate code with prompts like “Generate test cases for [function name]”, where you reference a function name in an open file.

Amazon Q Developer can also keep your software secure by highlighting security vulnerabilities. You can click “Run Security Scan” from the margin menu, which will return with a list of vulnerabilities. Currently, security scans only support C#.

You can ask Amazon Q questions, update your code, and initiate actions with quick commands all from the Amazon Q chat panel in your IDE. When you ask Amazon Q a question, it uses the current file that is open in your IDE as context, including the programming language and the file path.

Today, Amazon DataZone has introduced fine-grained access control, providing data owners granular control over their data at row and column levels. Customers use Amazon DataZone to catalog, discover, analyze, share, and govern data at scale across organizational boundaries with governance and access controls. Data owners can now restrict access to specific records of data, instead of granting access to the entire dataset. For example, if your table contains data for multiple regions, you can create row filters to grant access to rows with different regions to different projects. Additionally, column filters allow you to restrict access to specific columns, such as those containing Personally Identifiable Information (PII), ensuring that subscribers can only access the necessary and less sensitive data.

To get started, you can create row and column filters within the Amazon DataZone portal. When a user requests access to your data asset, you can approve the subscription by applying the appropriate filters. Amazon DataZone enforces these filters using AWS Lake Formation and Amazon Redshift, ensuring that the subscriber can only access the rows and columns that you have authorized.

Fine-grained access control support for both Amazon Redshift and AWS Lake Formation is now generally available in the following AWS Regions : US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (Stockholm), Europe (London), and South America (São Paulo).

Learn more about fine-grained access control in the user documentation .
 

Amazon Relational Database Service (Amazon RDS) for PostgreSQL, MySQL, and MariaDB now supports AWS Graviton2-based M6gd and R6gd database instances in the AWS GovCloud (US) Regions.

With this regional expansion, M6gd instances are now available for Amazon RDS for PostgreSQL, MySQL, and MariaDB in US East (Ohio, N. Virginia), US West (Oregon), Asia Pacific (Hong Kong, Hyderabad, Jakarta, Melbourne, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo), Canada (Calgary, Central), Europe (Frankfurt, Ireland, London, Milan, Paris, Spain, Stockholm, Zurich), Middle East (Bahrain, UAE), and the AWS GovCloud (US) Regions. R6gd instances are available for Amazon RDS for PostgreSQL, MySQL, and MariaDB in US East (Ohio, N. Virginia), US West (Oregon), Asia Pacific (Jakarta, Mumbai, Singapore, Sydney, Tokyo), Canada (Central), Europe (Frankfurt, Ireland, Paris), and the AWS GovCloud (US) Regions. For complete information on pricing and regional availability, please refer to the Amazon RDS pricing page .

M6gd and R6gd database instances are available on Amazon RDS for PostgreSQL version 16.1 and higher, 15.2 and higher, 14.5 and higher, and 13.4 and higher. M6gd and R6gd database instances are available on Amazon RDS for MySQL version 8.0.32 and higher, and Amazon RDS for MariaDB version 10.11.4 and higher, 10.6.13 and higher, 10.5.20 and higher, and 10.4.29 and higher. Get started by creating a fully managed M6gd database instance using the Amazon RDS Management Console. For more details, refer to the Amazon RDS User Guide .
 

AWS Lambda now supports runtime management controls in the AWS GovCloud (US) Regions. The operational simplicity of automatic runtime updates is one of the features customers most like about Lambda. This release provides customers running critical production workloads with more visibility and control over when runtime updates are applied to their functions.

For each runtime, Lambda provides a managed execution environment which includes the underlying Amazon Linux OS, programming language runtime, and SDKs. Lambda takes care of applying patches and security updates to all these components. These runtime updates allow customers to delegate responsibility for patching from the customer to Lambda. With this release, the updates made to the managed runtimes provided by Lambda are now visible to customers as distinct runtime versions. Customers also have more control over when Lambda updates their functions to a new runtime version, either automatically or synchronized with customer-driven function updates. In the very rare event of an unexpected runtime incompatibility with an existing function, they can also roll back to an earlier runtime version.

Visit our product documentation for more information about runtime management controls. Sign in to the AWS Lambda console to get started.

AWS Lambda announces advanced logging controls that enable you to natively capture logs in JSON structured format, adjust log levels, and select the Amazon CloudWatch log group for your Lambda functions.

You can now capture your Lambda logs in JSON structured format without having to bring your own logging libraries. JSON format allows logs to be structured as a series of key-value pairs, enabling you to quickly search, filter, and analyze your function logs. You can also control the log level (e.g. ERROR, DEBUG, INFO, etc.) of your Lambda logs without making any code changes. This enables you to choose the desired logging granularity level for your function, eliminating the need to sift through large volumes of logs while debugging and troubleshooting critical errors. Lastly, you can choose the CloudWatch log group to which Lambda sends your logs. This allows you to easily aggregate logs from multiple functions within an application in one place, and apply security, governance, and retention policies at the application level, rather than applying them individually to every function.

To get started, you can specify advanced logging controls for your Lambda functions using Lambda API, Lambda console, AWS CLI, AWS Serverless Application Model (SAM), and AWS CloudFormation. To learn more, visit the launch blog post or Lambda Developer Guide .

Lambda advanced logging controls are now available in AWS GovCloud (US) Regions, at no additional cost. For more information, see the AWS Region table .

The body responds to extreme heat  with gradually worsening symptoms: heat cramps, heat exhaustion and heatstroke. Heatstroke occurs when the body’s heat-regulating system is overwhelmed. The expert medical platform Patient.info outlines …

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