Tag: SysAdmin

Amazon Bedrock expands model selection for customers by adding support for GLM 5 and Minimax M2.5. GLM 5 is a frontier‑class, general‑purpose large language model optimized for complex systems engineering and long‑horizon agentic tasks. It builds on the GLM 4.5 agent‑centric lineage and is designed to support multi‑step reasoning, math (including AIME‑style benchmarks), advanced coding, and tool‑augmented workflows, with long context support suitable for sophisticated agents and enterprise applications. MiniMax M2.5 is an agent‑native frontier model trained explicitly to reason efficiently, decompose tasks optimally, and complete complex workflows under real‑world time and cost constraints. It achieves task completion speeds comparable to or faster than leading proprietary frontier models by combining high inference throughput with reinforcement learning focused on token‑efficient reasoning and better decision‑making in agentic scaffolds. MiniMax M2.5 a

Amazon EC2 High Memory U7i instances with 6TB of memory (u7i-6tb.112xlarge) are now available in AWS Asia Pacific (Malaysia). U7i instances are part of AWS 7th generation and are powered by custom fourth generation Intel Xeon Scalable Processors (Sapphire Rapids). U7i-6tb instances offer 6TiB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment. U7i-6tb instances deliver 448 vCPUs with up to 100 Gbps of Amazon EBS bandwidth for faster data loading and backups, 100 Gbps of network bandwidth, and ENA Express. U7i instances are ideal for customers using mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server. To learn more about U7i instances, visit the High Memory instances page.

Amazon Bedrock now supports NVIDIA Nemotron 3 Super, an open hybrid Mixture-of-Experts (MoE) model designed for complex multi-agent applications. Built for agentic workloads, Nemotron 3 Super delivers fast, and cost-efficient inference enabling AI agents to maintain focus and accuracy across long, multi-step tasks without losing context. Fully open with weights, datasets, and recipes, the model supports easy customization and secure deployment, making it well-suited for enterprises, startups, and individual developers building multi-agent workflows, and advanced reasoning applications. Amazon Bedrock gives customers access to Nemotron 3 Super through a single, fully managed API — with no infrastructure to provision or models to host. Bedrock's serverless inference, built-in security controls, and compatibility with OpenAI API specifications make it easy to integrate Nemotron 3 Super into existing workflows and deploy at production scale with confidence. NVIDIA Nemo

Amazon Elastic Container Registry (Amazon ECR) pull through cache now supports Chainguard’s registry as an upstream source. With today’s release, customers now benefit from the security and availability of Amazon ECR for private Chainguard images. As customers continue to scale their use of Chainguard images, keeping them synchronized with Chainguard's registry becomes increasingly important. With ECR's pull through cache feature, customers can keep Chainguard images in sync without additional workflows or tools to manage. Amazon ECR's pull through cache supports frequent registry syncs, helping to keep container images sourced from Chainguard up to date. Later, customers can apply ECR features such as image scanning and lifecycle policies to their cached Chainguard images. The pull through cache for Chainguard is available in all AWS Regions where Amazon ECR pull through cache is supported. To get s

You can now create Amazon S3 Access Grants in the AWS Asia Pacific (New Zealand) Region. Amazon S3 Access Grants map identities in directories such as Microsoft Entra ID, or AWS Identity and Access Management (IAM) principals, to datasets in S3. This helps you manage data permissions at scale by automatically granting S3 access to end users based on their corporate identity. Visit the AWS Region Table for complete regional availability information. To learn more about Amazon S3 Access Grants, visit our product page.

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M6in and M6idn instances are available in AWS London Region. These sixth-generation network optimized instances, powered by 3rd Generation Intel Xeon Scalable processors and built on the AWS Nitro System, deliver up to 200Gbps network bandwidth, for 2x more network bandwidth over comparable fifth-generation instances. Customers can use M6in and M6idn instances to scale their performance and throughput of network-intensive workloads such as high-performance file systems, distributed web scale in-memory caches, caching fleets, real-time big data analytics, and Telco applications such as 5G User Plane Function. M6in and M6idn instances are available in 10 different instance sizes including metal, offering up to 128 vCPUs and 512 GiB of memory. They deliver up to 100Gbps of

Starting today, the compute-optimized Amazon EC2 C8a instances are available in the Asia Pacific (Tokyo) region. C8a instances are powered by 5th Gen AMD EPYC processors (formerly code named Turin) with a maximum frequency of 4.5 GHz, delivering up to 30% higher performance and up to 19% better price-performance compared to C7a instances. C8a instances deliver 33% more memory bandwidth compared to C7a instances, making these instances ideal for latency sensitive workloads. Compared to Amazon EC2 C7a instances, they are up to 57% faster for GroovyJVM allowing better response times for Java-based applications. C8a instances offer 12 sizes including 2 bare metal sizes. This range of instance sizes allows customers to precisely match their workload requirements. C8a instances are built on AWS Nitro System and are ideal for high performance, compute-intensive workloads such as batch processing, distributed

Amazon Inspector now offers expanded agentless EC2 scanning with enhanced detection coverage, including new support for Windows operating system vulnerability scanning without requiring an agent. Security teams and IT administrators can now detect vulnerabilities across a broader range of software and applications on their EC2 instances — including WordPress, Apache HTTP Server, Python packages, and Ruby gems — as well as Windows OS vulnerabilities, all through agentless scanning. Customers automatically receive findings for newly supported software and applications with no configuration changes required. Amazon Inspector is also introducing Windows Knowledge Base (KB)-based findings for Windows OS vulnerabilities. Rather than receiving a separate finding for each CVE addressed by a single Microsoft patch, customers now receive a single consolidated KB finding that groups all related CVEs together. Each KB finding surfaces the highest CVSS score, EPSS score, and exploit

AWS Config announces the launch of an additional 75 managed Config rules for various use cases such as security, durability, and operations. You can now search, discover, enable and manage these additional rules directly from AWS Config and govern more use cases for your AWS environment. With this launch, you can now enable these controls across your account or across your organization. For example, you can assess your security posture across AWS Amplify, Amazon SageMaker, Amazon Route 53, and more. Additionally, you can leverage Conformance Packs to group these new controls and deploy across an account or across organization, streamlining your multi-account governance. For the full list of recently released rules, visit the AWS Config developer guide. For description of each rule and the AWS Regions in which it is available, please refer our 

Amazon Redshift improves the performance of BI dashboards and ETL workloads by speeding up new queries by up to 7x. This significantly improves the response times of low-latency SQL queries, such as those used in near real-time analytics applications, BI dashboards, ETL pipelines, and autonomous, goal-seeking AI agents. Customers experience substantially faster query response times as Redshift accelerates the process of preparing the SQL query for execution. Queries start faster and return results quicker. This improvement is automatically enabled at no additional cost. To deliver this major improvement, Redshift added a new optimization to query compilation where new queries are processed immediately using composition. Composition is a technique that generates a lightweight arrangement of pre-existing logic while simultaneously creating highly optimized, query-specific code that is compiled and executed across available compute