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Mouser is shipping the u-blox ZED-X20P high precision module, which is described as a professional grade all-band, all-constellation GNSS receiver. Basically, the module integrates all-band GNSS with signal modernisation and …

Today, Amazon Bedrock announces the expansion of the Reserved service tier designed for workloads requiring predictable performance and guaranteed tokens-per-minute capacity. The Reserved tier provides the ability to reserve prioritized compute capacity, keeping service levels predictable for your mission critical applications. It also includes the flexibility to allocate different input and output tokens-per-minute capacities to match the exact requirements of your workload and control cost. This is particularly valuable because many workloads have asymmetric token usage patterns. For instance, summarization tasks consume many input tokens but generate fewer output tokens, while content generation applications require less input and more output capacity. When your application needs more tokens-per-minute capacity than what you reserved , the service automatically overflows to the pay-as-you-go Standard tier, ensuring uninterrupted operations. The Reserved tier and is available today for Anthropic Claude Opus 4.5 and Claude Haiku 4.5. Customers can reserve capacity for 1 month or 3 month duration. Customers pay a fixed price per 1K tokens-per-minute and are billed monthly.

With the expansion of the Reserved service tier, Amazon Bedrock continues to provide more choice to customers, helping them develop, scale, and deploy applications and agents that improve productivity and customer experiences while balancing performance and cost requirements.

For more information about the AWS Regions where Amazon Bedrock Reserved tier is available, refer to the Documentation . To get access to the Reserved tier, please contact your AWS account team. 

AWS Graviton4-based R8g database instances are now generally available for Amazon Aurora (MySQL and PostgreSQL compatibility) and Amazon RDS for PostgreSQL, MySQL, and MariaDB in additional Asia Pacific regions (Hong Kong, Osaka, and Jakarta). R8G instances are now supported for Amazon Aurora with MySQL compatibility and Amazon RDS for PostgreSQL, MySQL, and MariaDB in Asia Pacific (Seoul and Singapore), and Canada (Central) regions, expanding on the previous launch of R8g support for Amazon Aurora with PostgreSQL compatibility in these three regions. Additionally, Amazon Aurora with MySQL and PostgreSQL compatibility now also supports R7i database instances in Asia Pacific (Hyderabad) and R7g database instances in Africa (Cape Town).

AWS Graviton4-based instances provide up to 40% performance improvement and up to 29% price/performance improvement for on-demand pricing over Graviton3-based instances of equivalent sizes on Amazon Aurora and Amazon RDS databases, depending on database engine, version, and workload. Built on the AWS Nitro System, the new R8g database instances introduce 24xlarge and 48xlarge sizes, delivering up to 192 vCPUs, an 8:1 ratio of memory to vCPU with the latest DDR5 memory, up to 50Gbps enhanced networking bandwidth, and up to 40Gbps of bandwidth to Amazon Elastic Block Store (Amazon EBS).

You can easily launch R8g, R7g, or R7i database instances through the Amazon RDS Management Console  or by using the AWS Command Line Interface  (CLI). For detailed information about specific engine versions that support these database instance types, please refer to the Aurora  and RDS  documentation. For complete information on pricing and regional availability, please refer to the Amazon RDS pricing page .

Amazon CloudWatch Database Insights expands the availability of its on-demand analysis experience to four additional Regions – Asia Pacific (New Zealand), Asia Pacific (Taipei), Asia Pacific (Thailand), and Mexico (Central). CloudWatch Database Insights is a monitoring and diagnostics solution that helps database administrators and developers optimize database performance by providing comprehensive visibility into database metrics, query analysis, and resource utilization patterns. This feature leverages machine learning models to help identify performance bottlenecks during the selected time period, and gives advice on what to do next.

Previously, database administrators had to manually analyze performance data, correlate metrics, and investigate root cause. This process is time-consuming and requires deep database expertise. With this launch, you can now analyze database performance monitoring data for any time period with automated intelligence. The feature automatically compares your selected time period against normal baseline performance, identifies anomalies, and provides specific remediation advice. Through intuitive visualizations and clear explanations, you can quickly identify performance issues and receive step-by-step guidance for resolution. This automated analysis and recommendation system reduces mean-time-to-diagnosis from hours to minutes.

You can get started with this feature by enabling the Advanced mode of CloudWatch Database Insights on your Amazon Aurora and Amazon RDS databases using the RDS service console, AWS APIs, the AWS SDK, or AWS CloudFormation. Please refer to Aurora documentation  or RDS documentation  to get started. 

Amazon Elastic VMware Service (Amazon EVS) now supports the ability to specify supported combinations of VMware Cloud Foundation (VCF) and ESX software versions when setting up your EVS environments and hosts.

Amazon EVS lets you run VCF natively within your Amazon Virtual Private Cloud (VPC), powered by AWS Nitro EC2 bare-metal instances. Amazon EVS automates deployment of a complete VCF environment in hours using either an intuitive step-by-step configuration workflow on the AWS console or the AWS Command Line Interface (CLI). This newest enhancement addresses the critical need for version flexibility to help you migrate workloads to AWS faster, reduce operational complexity and risk, and meet data center exit deadlines with Amazon EVS.

With software versioning support, you can now specify a VCF version when creating new environments using the CreateEnvironment API and select an ESX version when adding new hosts to existing environments using the CreateEnvironmentHost API. You can also query supported version combinations with the new GetVersions API. As part of this capability, we’re also adding support for new environment deployments with VCF 5.2.2.

To get started, visit the Amazon EVS product detail page  and user guide .

On January 20, 2026 Amazon announced quarterly security and critical updates for Amazon Corretto Long-Term Supported (LTS) versions of OpenJDK. Corretto 25.0.2, 21.0.10, 17.0.18, 11.0.30, and 8u482 are now available for download . Amazon Corretto is a no-cost, multi-platform, production-ready distribution of OpenJDK.

Click on the Corretto home page to download Corretto 25, Corretto 21, Corretto 17, Corretto 11, or Corretto 8. You can also get the updates on your Linux system by configuring a Corretto Apt, Yum, or Apk repo .

Feedback is welcomed !

Amazon Relational Database Service (Amazon RDS) now supports faster Blue/Green Deployments switchover, reducing your primary database, or writer node, upgrade downtime to typically five seconds or lower for single-Region configurations. Blue/Green Deployment creates a staging environment (Green) to test changes while keeping production (Blue) safe, enabling seamless switchover that requires no application endpoint changes.

Your database writer instance downtime during switchover varies based on your connection method. For single-Region configurations, applications connecting directly to the database endpoint experience typically five seconds or lower downtime, while those using the AWS Advanced JDBC Driver typically see two seconds or lower due to eliminated DNS propagation delays. You can use Amazon RDS Blue/Green Deployments for deploying changes to production, such as major version database engine upgrades, maintenance updates, and scaling instances.

Support for faster RDS Blue/Green Deployments switchover for single-Region configurations is available for Amazon Aurora and Amazon RDS database engines including PostgreSQL, MySQL, and MariaDB in all AWS regions.

In a few clicks, update your databases using RDS Blue/Green Deployments via the Amazon RDS Console or Amazon RDS CLI . Learn more about RDS Blue/Green Deployments and the supported engine versions here .

Amazon RDS for Oracle now supports bare metal instances with Bring Your Own License (BYOL) license for Oracle Standard Edition 2. You can use M7i, R7i, X2iedn, X2idn, X2iezn, M6i, M6id, M6in, R6i, R6id, and R6in bare metal instances at 25% lower price compared to equivalent virtualized instances.

With bare metal instances, you may be able to reduce your commercial database license and support costs by using bare metal instances since they provide full visibility into the number of CPU cores and sockets of the underlying server. Most bare metal instances have 2 sockets while db.m7i.metal-24xl and db.r7i.metal-24xl instances each have a single socket. Consult your legal or licensing partner to determine if you can use bare metal instances with Oracle Standard Edition 2 and if you can reduce license and support costs.

Bare metal instances are available with Bring Your Own License (BYOL) license for Oracle Enterprise Edition Standard Edition 2. Refer to Amazon RDS for Oracle Pricing for available instance configurations, pricing, and region availability.

Amazon Quick Suite SPICE engine is now supporting higher scale, faster ingestion, and broader data types to power advanced analytics and AI-driven workloads. With this launch, customers can load up to 2TB of data per dataset, doubling the previous 1TB limit, when using the new data preparation experience. Despite the increased dataset size, SPICE continues to deliver strong performance, with ingestion further optimized to enable even faster data loading and refresh to reduce time to insight. We’ve also expanded SPICE’s data type support by increasing string length limits from 2K to 64K Unicode characters and extending the supported timestamp range from year 1400 back to year 0001. As Quick Suite customers bring richer, more complex, and increasingly AI-driven workloads into SPICE, these enhancements enable broader data coverage, faster data onboarding, and more powerful analytics, without compromising performance. To learn more, visit our documentation.

The new SPICE dataset size limitation is now available in Amazon Quick Sight Enterprise Editions across all supported Amazon Quick Sight regions .