The SBC3518 is a rugged 3U VPX single board computer that sees Abaco Systems building on Intel’s Core Ultra Series 3 processors. It’s designed for demanding commercial, defence and aerospace applications, …

The post Rugged 3U VPX SBC aims for 100TOPS with Intel Core Ultra 3 appeared first on Electronics Weekly .

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R7gd instances with up to 3.8 TB of local NVMe-based SSD block-level storage are available in Europe (Paris) Region.

R7gd are powered by AWS Graviton3 processors with DDR5 memory are built on the AWS Nitro System . They are ideal for memory-intensive workloads such as open-source databases, in-memory caches, and real-time big data analytics and are a great fit for applications that need access to high-speed, low latency local storage, including those that need temporary storage of data for scratch space, temporary files, and caches. 

To learn more, see Amazon R7gd Instances . To get started, see the AWS Management Console .

Amazon DynamoDB global tables with multi-Region strong consistency (MRSC) now supports application resiliency testing with AWS Fault Injection Service (FIS), a fully managed service for running controlled fault injection experiments to improve application performance, observability, and resilience. With this launch, you can create real-world failure scenarios to MRSC global tables, such as during regional failures, enabling you to observe how your applications respond to these disruptions and validate your resilience mechanisms.

MRSC global tables replicate your DynamoDB tables automatically across your choice of AWS Regions to achieve fast, strongly consistent read and write performance, providing you 99.999% availability , increased application resiliency, and improved business continuity. FIS is a fully managed service for running controlled fault injection experiments to improve an application’s performance, observability, and resilience. You can use the new FIS action to observe how your application responds to a pause in regional replication and tune monitoring and recovery processes to improve resiliency and application availability.

MRSC global tables support for FIS is available in the following AWS Regions : US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Tokyo), Asia Pacific (Osaka), Asia Pacific (Seoul), Europe (Ireland), Europe (London), Europe (Frankfurt), and Europe (Paris). To get started, visit the DynamoDB FIS actions documentation .

You can now use Amazon MSK Replicator to replicate streaming data across Amazon Managed Streaming for Apache Kafka (Amazon MSK ) clusters in Asia Pacific (New Zealand) Region.

MSK Replicator is a feature of Amazon MSK that enables you to reliably replicate data across Amazon MSK clusters in different or the same AWS Region(s) in a few clicks. With MSK Replicator, you can easily build regionally resilient streaming applications for increased availability and business continuity. MSK Replicator provides automatic asynchronous replication across MSK clusters, eliminating the need to write custom code, manage infrastructure, or setup cross-region networking. MSK Replicator automatically scales the underlying resources so that you can replicate data on-demand without having to monitor or scale capacity. MSK Replicator also replicates the necessary Kafka metadata including topic configurations, Access Control Lists (ACLs), and consumer group offsets. If an unexpected event occurs in a region, you can failover to the other AWS Region and seamlessly resume processing.

You can get started with MSK Replicator from the Amazon MSK console or the Amazon CLI. With this launch, MSK Replicator is now available in thirty six AWS Regions. To learn more, visit the MSK Replicator documentation , product page , and pricing page .

Amazon GameLift Servers now enables automatic scaling to and from zero instances, addressing a critical cost optimization challenge for game developers. Previously, developers had to maintain running instances even during periods of low or no activity in order for Fleet autoscaling to remain active. This resulted in unnecessary infrastructure costs during off-peak hours. With automatic scaling to and from zero instances, game developers using Amazon GameLift Servers can optimize their multiplayer gaming infrastructure costs while maintaining responsive performance.

By eliminating charges for unused instances during inactive periods, while automatically scaling up when game sessions are requested, this new capability delivers significant cost savings for game developers. This is particularly valuable for games with distinct peak and off-peak periods, seasonal or event-based games, new game launches with uncertain traffic patterns, and regional games with time-zone specific activity. Additionally, scaling decisions no longer need manual intervention, as Amazon GameLift Servers intelligently adapts to natural gaming activity patterns.

The automatic scaling to zero instances capability is available in all Amazon GameLift Servers supported regions. To learn more about Amazon GameLift Servers automatic scaling capabilities and implementation details, visit the Amazon GameLift Servers documentation .

Kubernetes version 1.35 introduced several new features and bug fixes, and AWS is excited to announce that you can now use Amazon Elastic Kubernetes Service (EKS) and Amazon EKS Distro to run Kubernetes version 1.35. Starting today, you can create new EKS clusters using version 1.35 and upgrade existing clusters to version 1.35 using the EKS console, the eksctl command line interface, or through an infrastructure-as-code tool.

Kubernetes version 1.35 introduces several key improvements, including In-Place Pod Resource Updates allowing CPU and memory adjustments without restarting Pods, and PreferSameNode Traffic Distribution prioritizing local endpoints before routing to remote nodes for reduced latency. The release brings Node Topology Labels via Downward API enabling Pods to access region and zone information without API server queries, alongside Image Volumes delivering data artifacts like AI models using OCI container images. To learn more about the changes in Kubernetes version 1.35, see our documentation and the Kubernetes project release notes.

EKS now supports Kubernetes version 1.35 in all the AWS Regions where EKS is available, including the AWS GovCloud (US) Regions.

You can learn more about the Kubernetes versions available on EKS and instructions to update your cluster to version 1.35 by visiting EKS documentation. You can use EKS cluster insights to check if there are any issues that can impact your Kubernetes cluster upgrades. EKS Distro builds of Kubernetes version 1.35 are available through ECR Public Gallery and GitHub. Learn more about the EKS version lifecycle policies in the documentation .

AWS announces the launch of deployment Standard Operating Procedures (SOPs) available in the AWS MCP Server . SOPs are structured, natural language instructions that guide AI agents through complex, multi-step tasks to ensure consistent, reliable, and efficient behavior. With these automated procedures, customers can deploy web applications to their AWS account using natural language prompts from any MCP-compatible IDE or CLI, including Kiro, Kiro CLI, Cursor, and Claude Code. Deployment works by generating AWS CDK infrastructure, deploying CloudFormation stacks, and creating CI/CD pipelines with recommended AWS security best practices.

Previously, developers struggled to take their vibe-coded applications to production with DevOps best practices in place. Now, developers can move quickly from prototype to production in as little as one prompt. When you ask your AI assistant configured with AWS MCP Server to deploy your web application, your AI agent will follow the multi-step plan defined in Agent SOPs to analyze the project structure, generate CDK infrastructure, and deploy a preview environment hosted on Amazon S3 and Amazon CloudFront. Once you are ready, it can configure AWS CodePipeline for automated production deployments from source repositories, setting up CI/CD automatically for your application. The Agent SOPs support web applications built with popular frameworks including React, Vue.js, Angular, and Next.js. Deployment documentation is automatically created in the repository, enabling agents to handle future deployments, query logs for troubleshooting and resume work across sessions.

The Agent SOPs are available in preview as part of the AWS MCP Server at no additional cost in the US East (N. Virginia) Region. You pay only for AWS resources you create and applicable data transfer costs. To get started, see the AWS MCP Server documentation .

Amazon Cognito introduces inbound federation Lambda triggers that enable you to transform and customize federated user attributes during the authentication process. You can now modify responses from external SAML and OIDC providers before they are stored in your user pool, providing complete programmatic control over the federation flow without requiring changes to your identity provider configuration..

Inbound federation Lambda trigger addresses current limitations in federated authentication workflows, particularly issues caused by attribute size limits and the need for selective attribute storage from external identity providers. For example, large group attributes from external SAML or OIDC identity providers that exceed Cognito’s 2,048 character limit per attribute can block the authentication flow. This capability allows you to add, override, or suppress attribute values, such as modifying large group attributes, before creating new federated users or updating existing federated user profiles in Cognito.

The new inbound federation Lambda trigger is available through hosted UI (classic) and managed login in all AWS Regions where Amazon Cognito is available. To get started, configure the trigger using the AWS Management Console, AWS Command Line Interface (CLI), AWS Software Development Kits (SDKs), Cloud Development Kit (CDK), or AWS CloudFormation by adding the new parameter to your User Pool LambdaConfig. To learn more, see the Amazon Cognito Developer Guide  for implementation examples and best practices.

Amazon Keyspaces (for Apache Cassandra) now supports table pre-warming, allowing you to proactively prepare both new and existing tables to meet future traffic demands. This capability is available for tables in both provisioned and on-demand capacity modes, including multi-Region replicated tables.

Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. Amazon Keyspaces is serverless, so you pay for only the resources that you use and you can build applications that serve thousands of requests per second with virtually unlimited throughput and storage.

While Amazon Keyspaces automatically scales to accommodate growing workloads, certain scenarios like application launches, marketing campaigns, or seasonal events can create sudden traffic spikes that exceed normal scaling patterns. With pre-warming, you can now manually specify your expected peak throughput requirements during table creation or update operations, ensuring your tables are immediately ready to handle large traffic surges without scaling delays or increased error rates.

The pre-warming process is non-disruptive and runs asynchronously, allowing you to continue making other table modifications while pre-warming is in progress. Pre-warming incurs a one-time charge based on the difference between your specified values and the baseline capacity. The feature is now available in all AWS Commercial and AWS GovCloud (US) Regions where Amazon Keyspaces is offered. To learn more, visit the pre-warming launch blog or Amazon Keyspaces documentation .

Amazon Bedrock now supports server-side tools in the Responses API using OpenAI API-compatible service endpoints. Bedrock already supports client-side tool use with the Converse, Chat Completions, and Responses APIs. Now, with the launch of server-side tool use for Responses API, Amazon Bedrock calls the tools directly without going through a client, enabling your AI applications to perform real-time, multi-step actions such as searching the web, executing code, and updating databases within the organizational, governance, compliance, and security boundaries of your AWS accounts. You can either submit your own custom Lambda function to run custom tools or use AWS-provided tools, such as notes and tasks.

Server-side tools using the Responses API is available starting today with OpenAI’s GPT OSS 20B/120B models in US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Tokyo), Asia Pacific (Mumbai), South America (São Paulo), Europe (Ireland), Europe (London), and Europe (Milan) AWS Regions. Support for other regions and models is coming soon.

To get started, visit the service documentation .