Mikroe has introduced a narrowband LTE IoT communication development board in its ‘Click’ format. It is called ‘NB IoT 6 Click’, and its active wireless module is the BC65 from …

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The UK Space Agency (UKSA) has awarded £287,000 to the University of Northumbria to further research the use of Blood Flow Restriction (BFR) exercise and associated hardware technology. Specifically, the …

The post University of Northumbria funding for astronaut BFR testing appeared first on Electronics Weekly .

Earlier today, TSMC announced Q3 revenue of  $33.1 billion with a profit of $14.76 billion. Q3  revenue increased 40.8% YoY and 10% QoQ while net income increased 39.1%. Compared to …

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AWS Backup now provides more details in backup job API responses and Backup Audit Manager reports to give you better visibility into backup configurations and compliance settings. You can verify your backup policies with a single API call.

List and Describe APIs for backup, copy, and restore jobs now return fields that required multiple API calls before. Delegated administrators can now view backup job details across their organization. Backup jobs APIs include retention settings, vault lock status, encryption details, and backup plan information like plan names, rule names, and schedules. Copy job APIs return destination vault configurations, vault type, lock state, and encryption settings. Restore job APIs show source resource details and vault access policies. Backup Audit Manager reports include new columns with vault type, lock status, encryption details, archive settings, and retention periods. You can use this information to enhance audit trails and verify compliance with data protection policies.

These expanded information fields are available today in all AWS Regions where AWS Backup and AWS Backup Audit Manager are supported , with no additional charges.

To learn more about AWS Backup Audit Manager, visit the product page and documentation . To get started, visit the AWS Backup console .

Amazon RDS for Oracle zero-ETL integration with Amazon Redshift is now available in the Asia Pacific (Hyderabad), Asia pacific (Jakarta), Asia Pacific (Melbourne), Canada West (Calgary), Europe (Spain), Europe (Zurich), Israel (Tel Aviv), and Middle East(UAE) Regions. Amazon RDS for Oracle zero-ETL integration with Amazon Redshift enables near real-time analytics and machine learning (ML) to analyze petabytes of transactional data in Amazon Redshift without complex data pipelines for extract-transform-load (ETL) operations. Within seconds of data being written to an Amazon RDS for Oracle database instance, the data is replicated to Amazon Redshift. Zero-ETL integrations simplify the process of analyzing data from Amazon RDS for Oracle database instances, enabling you to derive holistic insights across multiple applications with ease.

You can use the AWS management console, API, CLI, and AWS CloudFormation to create and manage zero-ETL integrations between RDS for Oracle and Amazon Redshift. If you use Oracle multitenant architecture, you can choose specific pluggable databases (PDBs) to selectively replicate them. In addition, you can choose specific tables and tailor replication to your needs.

RDS for Oracle zero-ETL integration with Redshift is available with Oracle Database version 19c. To learn more, refer Amazon RDS and Amazon Redshift documentation. 

Amazon Web Services (AWS) announces URL and Host Header rewrite capabilities for Application Load Balancer (ALB). This feature enables customers to modify request URLs and Host Headers using regex-based pattern matching before routing requests to targets.

With URL and Host Header rewrites, you can transform URLs using regex patterns (e.g., rewrite “/api/v1/users” to “/users”), standardize URL patterns across different applications, modify Host Headers for internal service routing, remove or add URL path prefixes, and redirect legacy URL structures to new formats. This capability eliminates the need for additional proxy layers and simplifies application architectures. The feature is valuable for microservices deployments where maintaining a single external hostname while routing to different internal services is critical.

You can configure URL and Host Header rewrites through the AWS Management Console, AWS CLI, AWS SDKs, and AWS APIs. There are no additional charges for using URL and Host Header rewrites. You pay only for your use of Application Load Balancer based on Application Load Balancer pricing.

This feature is now available in all AWS commercial regions.

To learn more, visit the ALB Documentation , and the AWS Blog post on URL and Host Header rewrites with Application Load Balancer.

Amazon Managed Streaming for Apache Kafka (Amazon MSK) now supports Apache Kafka version 4.1, introducing Queues as a preview feature, a new Streams Rebalance Protocol in early access, and Eligible Leader Replicas (ELR). Along with these features, Apache Kafka version 4.1 includes various bug fixes and improvements. For more details, please refer to the Apache Kafka release notes for version 4.1.

A key highlight of Kafka 4.1 is the introduction of Queues as a preview feature. Customers can use multiple consumers to process messages from the same topic partitions, improving parallelism and throughput for workloads that need point-to-point message delivery. The new Streams Rebalance Protocol builds upon Kafka 4.0’s consumer rebalance protocol, extending broker coordination capabilities to Kafka Streams for optimized task assignments and rebalancing. Additionally, ELR is now enabled by default to strengthen availability.

To start using Apache Kafka 4.1 on Amazon MSK, simply select version 4.1.x when creating a new cluster via the AWS Management Console, AWS CLI, or AWS SDKs. You can also upgrade existing MSK provisioned clusters with an in-place rolling update. Amazon MSK orchestrates broker restarts to maintain availability and protect your data during the upgrade. Kafka version 4.1 support is available today across all AWS regions where Amazon MSK is offered. To learn how to get started, see the Amazon MSK Developer Guide .

Amazon Kinesis Data Streams now supports Fault Injection Service (FIS) actions for Kinesis API errors. Customers can now test their application’s error handling capabilities, retry mechanisms (such as exponential backoff patterns), and CloudWatch alarms in a controlled environment. This allows customers to validate their monitoring systems and recovery processes before encountering real-world failures, ultimately improving application resilience and availability. This integration supports Kinesis Data Streams API errors including throttling, internal errors, service unavailable, and expired iterator exceptions for Amazon Kinesis Data Streams.

Amazon Kinesis Data Streams is a serverless data streaming service that enables customers to capture, process, and store real-time data streams at any scale. Now customers can create real-world Kinesis Data Stream API errors (including 500, 503, and 400 errors for GET and PUT operations) to test application resilience. This feature eliminates the previous need for custom implementation or to wait for actual production failures to verify error handling mechanisms. To get started, customers can create experiment templates through the FIS console to run tests directly or integrate them into their continuous integration pipeline. For additional safety, FIS experiments include automatic stop mechanisms that trigger when customer-defined thresholds are reached, ensuring controlled testing without risking application stability.

These actions are generally available in all AWS Regions where FIS is available , including the AWS GovCloud (US) Regions. To learn more about using these actions, please see the Kinesis Data Streams User Guide and FIS User Guide .

Amazon RDS for MySQL and Amazon RDS for PostgreSQL zero-ETL integration with Amazon Redshift is now available in the Asia Pacific (Hyderabad), Asia Pacific (Jakarta), Asia Pacific (Melbourne), Canada West (Calgary), Europe (Spain), Europe (Zurich), Israel (Tel Aviv), and Middle East (UAE) regions. Zero-ETL integrations enable near real-time analytics and machine learning (ML) on petabytes of transactional data using Amazon Redshift. Within seconds of data being written to Amazon RDS for MySQL or Amazon RDS for PostgreSQL, the data is replicated to Amazon Redshift.

You can create multiple zero-ETL integrations from a single Amazon RDS database, and you can apply data filtering for each integration to include or exclude specific databases and tables, tailoring the zero-ETL integration to your needs. You can also use AWS CloudFormation to automate the configuration and deployment of resources needed for zero-ETL integrations.

To learn more about zero-ETL and how to get started, visit the documentation for Amazon RDS and Amazon Redshift .

Amazon Elastic Container Services (Amazon ECS) now allows you to run Firelens containers as a non-root user, by specifying a User ID in your Task Definition.

Specifying a non-root user with a specific user ID reduces the potential attack footprint by users who may gain access to such software, a security best practice and a compliance requirement by some industries and security services such as the AWS Security Hub . With this release, Amazon ECS allows you to specify a user ID in the “user” field of your Firelens containerDefinition element of your Task Definition, instead of only allowing “user”: “0” (root user).

The new capability is supported in all AWS Regions. See the documentation for using Firelens for more details on how to set up your Firelens container to run as non-root.