ChangXin Memory Technologies (CXMT)  saw Q1 revenues rise 700% to $7.5 billion for a profit of  $1.26 billion. In Q1 2025 it made a loss. CXMT forecast an H1 revenue …

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Blackstone, the private equity company, and Google are forming a neo-cloud company to acquire, build and rent out datacentre capacity. The initial investment is $5 billion in equity from Blackstone …

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The recent launch of the Artemis II spacecraft tested the latest communication equipment, write Ethan Hutchings and Nick Reeve. The Artemis II mission represented a major step forward in human …

The post The role of communications IP and innovation in the Artemis II mission appeared first on Electronics Weekly .

A PCIe 7.0 clock generator with six-outputs from Diodes features a sub-30fs jitter for next-gen AI infrastructure, the company highlights. The PI6CG33A06 provides a stable reference clock for 128.0 GT/s …

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Vishay is announcing its VETH100A1DD1 ESD protection diode meets all three OPEN Alliance EMC test specifications for ESD protection devices. The part has passed IEEE 10BASE-T1S compliance testing, highlights Vishay, …

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Amazon Relational Database Service (Amazon RDS) for MySQL  now supports MySQL minor versions 8.0.46 and 8.4.9, the latest minors released by the MySQL community. We recommend upgrading to the newer minor versions to fix known security vulnerabilities in prior versions of MySQL and to benefit from bug fixes, performance improvements, and new functionality added by the MySQL community. Learn more about the enhancements in RDS for MySQL 8.0.46 and 8.4.9 in the Amazon RDS user guide .

You can leverage automatic minor version upgrades to automatically upgrade your databases to more recent minor versions during scheduled maintenance windows. You can also use Amazon RDS Managed Blue/Green deployments  for safer, simpler, and faster updates to your MySQL instances. Learn more about upgrading your database instances, including automatic minor version upgrades and Blue/Green Deployments, in the Amazon RDS User Guide.

Amazon RDS for MySQL makes it simple to set up, operate, and scale MySQL deployments in the cloud. Learn more about pricing details and regional availability at Amazon RDS for MySQL . Create or update a fully managed Amazon RDS for MySQL database in the Amazon RDS Management Console .

Amazon SageMaker Studio IDEs, including JupyterLab and Code Editor, now support GPU capacity reservations through SageMaker Flexible Training Plans (FTP) , giving you predictable access to high-demand, high-performance computational resources within your budget. By leveraging FTP, you can achieve up to 65% cost savings compared to On-Demand instances while running ML workflows in JupyterLab or Code Editor.

FTP provides a fully self-serve procurement experience. To get started, navigate to the SageMaker FTP console and select your preferred instance type, reservation length, and start date for your Studio IDE workload. Review your order, complete the purchase, and wait for the plan to become active. When creating a Studio app from the SageMaker Studio UI, select your purchased plan from the Instance dropdown. SageMaker provisions the instance automatically with no infrastructure management required on your part. As your plan nears expiration, the IDE proactively notifies you, giving you time to save your work before the reservation ends.

To learn more about using FTP capacity reservation capability with Studio IDEs, see Using Training Plans with Studio IDEs .
To learn about launching JupyterLab and Code Editor applications in SageMaker Studio, see Studio Spaces documentation .

 

Amazon Redshift now supports writing directly to Apache Iceberg tables via the AWS Glue Data Catalog (awsdatacatalog) mount and ALTER TABLE DDL statements to modify the schema, partitioning, and properties of Apache Iceberg tables. With write access through the auto-mounted awsdatacatalog, you can land Redshift transformations in your data lake for any engine to query without creating external schemas—particularly useful for Iceberg tables federated with AWS Lake Formation. Supported ALTER TABLE operations include ADD/DROP/ALTER columns, RENAME COLUMN, SET TABLE PROPERTIES to overwrite the default compression type, and ADD/DROP/REPLACE PARTITION FIELD to adapt partitioning strategies as data volumes grow. Previously, updating the structure of Iceberg tables required deleting the table and its data, adding complexity and latency to data pipelines. Tables modified by Redshift remain compatible with other Iceberg-compatible engines, including Amazon EMR and Amazon Athena , preserving cross-engine interoperability. AWS Lake Formation permissions are supported for Iceberg write operations.

These capabilities are available in all AWS Regions where Amazon Redshift is available. To get started, visit the Referencing Iceberg tables in Amazon Redshift and Altering table definitions sections in the Amazon Redshift Database Developer Guide.

AWS SAM CLI now supports AWS CloudFormation Language Extensions , enabling you to reduce duplication in your infrastructure as code (IaC) templates while retaining the full local development workflow. This accelerates your serverless development by letting you define resources once and iterate locally without waiting for cloud deployments.

Developers frequently need to define multiple similar resources, such as Lambda functions, DynamoDB tables, or SNS topics, from a single template definition. However, developers who use SAM CLI to build, test, and deploy their serverless applications previously could not process templates that use CloudFormation Language Extensions. This required choosing between reducing template duplication and using SAM CLI for local development. Now, SAM CLI processes Language Extensions in memory for local operations while preserving your original template for CloudFormation deployment. You can define your resources once and test them locally across all SAM CLI commands, catching errors like invalid syntax or missing dependencies before deploying. This shortens your iteration cycles and reduces time spent debugging failed deployments in the cloud.

To get started, download or update SAM CLI to the latest version. Add the AWS::LanguageExtensions transform to your SAM template and use Fn::ForEach to generate multiple resources from a single definition. SAM CLI commands including sam build, sam local invoke, sam sync, sam local start-api, and sam validate will automatically expand your loops and process each generated resource. You can invoke expanded functions by name, for example sam local invoke AlphaFunction. SAM CLI also supports Fn::Length, Fn::ToJsonString, Fn::FindInMap with DefaultValue, and conditional DeletionPolicy and UpdateReplacePolicy attributes.

To learn more, visit the SAM CLI developer guide  and launch blog post .

Today, we are announcing that Amazon Elastic VMware Service (Amazon EVS) now supports up to 32 ESXi hosts per environment, double the previous limit of 16 hosts.

Amazon EVS gives you flexibility in how you configure VMware Cloud Foundation (VCF) domains and clusters within an environment. You can put all your hosts into a single large cluster, spread them across several smaller clusters, or any combination that fits your needs. With this release, you can now submit a service quota increase to scale up to a total of 32 hosts and reduce the operational overhead of managing multiple environments.

This latest release is available in all regions where Amazon EVS is offered.

For more details on the steps and procedure, visit the Amazon EVS product detail page  and user guide.