All news in category “Vendor and Hyperscaler Watch”

📧 Fortinet was named a Challenger in the 2025 Gartner Magic Quadrant for Email Security, reflecting continued progress across its email protection portfolio. FortiMail Email Security and FortiMail Workspace Security combine AI-native detection, sandboxing, DMARC, enhanced BEC and account takeover defenses, and flexible on-premises and cloud deployment options. The company positions this suite as a cost-effective, integrated alternative that also extends protection to web browsers, cloud storage, and collaboration apps.

✅ Check Point has been recognized as a Leader in the 2025 Gartner Magic Quadrant for Email Security. This independent evaluation reinforces our commitment to delivering best-in-class email protection that blocks increasingly sophisticated threats while remaining easy to deploy and manage. According to Check Point Research, 68% of attacks start with email and 61% of harmful files are delivered as HTML attachments, underscoring the need for robust, reliable defenses.

🚀 Amazon SageMaker HyperPod now supports checkpointless training, a foundational capability that eliminates the need for checkpoint-based, job-level restarts for distributed model training. Checkpointless training preserves forward training state across the cluster, automatically swaps out failed nodes, and uses peer-to-peer state transfer to resume progress, reducing recovery time from hours to minutes. The feature can deliver up to 95% training goodput at very large scale, is available in all Regions where HyperPod runs, and can be enabled with zero code changes for popular recipes or with minimal PyTorch modifications for custom models.

🚀 Amazon SageMaker AI now offers a serverless model customization capability that lets developers quickly fine-tune popular models using supervised learning, reinforcement learning, and direct preference optimization. The fully managed, end-to-end workflow simplifies data preparation, synthetic data generation, training, evaluation, and deployment through an easy-to-use interface. Supported base models include Amazon Nova, Llama, Qwen, DeepSeek, and GPT-OSS. The AI agent-guided workflow is in preview with regional availability and a waitlist.

🚀 AWS has announced TypeScript support in preview for the Strands Agents SDK, giving developers a choice between Python and TypeScript for building model-driven AI agents. The TypeScript implementation provides idiomatic, type-safe APIs with async/await and modern JavaScript/TypeScript patterns, and is designed to run in browsers, client applications, and server runtimes such as AWS Lambda and Bedrock AgentCore. AWS also introduced three SDK updates: edge device support is now GA, Strands steering is available experimentally, and Strands evaluations is in preview to help validate agent behavior.

🧬 Combining Google’s ADK, Gemini, and Cloud infrastructure, this work reframes variant interpretation as a conversational workflow that removes repetitive scripting and context switching. A two-phase design performs heavy VEP annotation once, stores versioned ADK artifacts and public BigQuery datasets, and enables sub-5-second interactive queries via a QueryAgent. Validation with an APOB spike-in demonstrated single-variant precision, compatibility across DeepVariant versions, and scalability to ~8.8M variants.

🔧 Amazon Bedrock now supports reinforcement fine-tuning, enabling developers to improve model accuracy without deep ML expertise or large labeled datasets. The service automates the reinforcement fine-tuning workflow and trains models by learning from feedback on multiple candidate responses, improving model judgment about what makes a good reply. AWS reports an average 66% accuracy gain over base models, allowing teams to deploy smaller, faster, and more cost-effective variants while maintaining quality. At launch the feature supports Amazon Nova 2 Lite, and it can be accessed via the Bedrock console or APIs.

⚡ Amazon SageMaker HyperPod now supports elastic training, automatically scaling distributed training jobs to absorb idle accelerators and contract when higher‑priority workloads require resources. This eliminates the manual cycle of halting jobs, reconfiguring parameters, and restarting distributed training, which previously demanded specialized engineering time. Organizations can start training with minimal resources and grow opportunistically, improving cluster utilization and reducing costs. Elastic training can be enabled with zero code changes for public models like Llama and GPT OSS, and requires only lightweight configuration updates for custom architectures.

🚀 The GKE Turns 10 Hackathon showcased developer teams building agentic AI on GKE integrated with Google models such as Gemini. More than 4,700 participants from 133 countries produced 133 projects demonstrating multi-agent pipelines, model orchestration, and microservice integration. Grand prize winner Amie Wei’s Cart-to-Kitchen assistant uses GKE Autopilot, the Agent Development Kit (ADK), and Agent-to-Agent protocols to analyze grocery carts and recommend recipes. Google also announced GEAR, an educational sprint launching in early 2026 to help developers learn, build, and deploy AI agents.

⚠️ Microsoft is mitigating an ongoing incident affecting the Defender XDR portal that began roughly 10 hours ago and was first acknowledged at 06:10 UTC. The outage stemmed from a traffic spike that drove high CPU utilization on components responsible for portal functions, blocking access and disrupting features such as advanced threat-hunting alerts and device visibility. Microsoft applied mitigation to increase processing throughput and reports partial recovery for some customers while it analyzes HAR traces and coordinates client-side diagnostics with impacted organizations.

🚀 Over the past decade Microsoft and Red Hat have built a strategic partnership centered on open source and enterprise cloud innovation. Together they delivered offerings such as Red Hat Enterprise Linux on Azure and Azure Red Hat OpenShift, combining managed services, integrated support, and Marketplace availability. At Ignite 2025 the collaboration brought GA of OpenShift Virtualization and Confidential Containers, enabling VMs and hardware-isolated containers to run side-by-side for modernization and secure workloads.

🔒 Fortinet announced expanded integrations with AWS at re:Invent, including Fortinet Managed IPS Rules for AWS Network Firewall, FortiSASE on AWS Marketplace, and participation in the AWS European Sovereign Cloud. These offerings combine AI-driven FortiGuard threat intelligence, simplified procurement and Euro-denominated options for EU customers. The goal is to reduce operational burden, accelerate compliance with standards like PCI-DSS and HIPAA, and enable rapid deployment and scaling across hybrid and multi-cloud environments.

🚀 Starting today, AWS is previewing new general-purpose high-frequency Amazon EC2 M8azn instances powered by fifth-generation AMD EPYC processors that deliver up to 5 GHz maximum CPU frequency. These instances offer up to 2× the compute performance of M5zn and about 24% higher performance than M8a, and are built on the AWS Nitro System for secure, high-performance cloud delivery. They target workloads such as gaming, HFT, HPC, CI/CD, and simulation modeling; customers can request preview access.

🛠️ AWS announced the Apache Spark upgrade agent, a capability that automates and accelerates Spark version upgrades for Amazon EMR on EC2 and EMR Serverless. The agent performs automated code analysis across PySpark and Scala, identifies API and behavioral changes for Spark 2.4→3.5, and suggests precise code transformations. Engineers can invoke the agent from SageMaker Unified Studio, the Kiro CLI, or any MCP-compatible IDE, interact via natural-language prompts, review proposed edits, and approve implementations. Functional correctness is validated through data quality checks to help maintain processing accuracy during migration.

🆕 Amazon RDS for SQL Server now supports SQL Server 2022 Developer Edition, enabling teams to run a feature-complete, free edition of SQL Server in non-production RDS instances. The Developer Edition includes all Enterprise features for building, testing, and demonstrating applications while reducing licensing costs for development and test environments. Core RDS capabilities — automated backups, automated software updates, monitoring, and encryption — are supported on Developer Edition. The license is strictly limited to development and testing and may not be used in production or for commercial end-user scenarios.

📂 You can now attach Amazon S3 Access Points to Amazon FSx for NetApp ONTAP file systems so applications can access file data as if it were stored in S3. This lets a broad range of AI, ML, and analytics services—including Amazon Bedrock, SageMaker, and Glue—use your FSx file data without copying it. Create and attach access points via the Amazon FSx console, AWS CLI, or SDK; support for existing file systems will arrive in a forthcoming maintenance window. The capability is available in select AWS Regions.

🔧Amazon RDS for SQL Server introduces an Optimize CPU option with support for M7i and R7i instance families, lowering prices by up to 55% compared with equivalent sixth‑generation instances. Optimize CPU disables SMT on instances with two or more physical CPU cores to halve vCPU counts and associated third‑party licensing charges while preserving the same number of physical cores and near‑equivalent performance. The biggest savings appear on 2Xlarge and larger sizes and on Multi‑AZ deployments; memory‑ or I/O‑intensive workloads can be further tuned to reduce costs.

🚀 AWS has announced general availability of Amazon EC2 P6e-GB300 UltraServers powered by the NVIDIA GB300 NVL72. The new UltraServers deliver 1.5× GPU memory and 1.5× FP4 compute (without sparsity) compared with P6e-GB200, enabling higher-context inference and improved throughput for large models. Ideal for reasoning, Agentic AI, and production inference; contact your AWS sales representative to get started.

🎁 This holiday season Google Skills provides no-cost AI courses and hands-on labs taught by Google Cloud experts, intended for both technical and non-technical learners. Technical offerings include sandboxed labs covering Gemini Code Assist, Vibe coding, Model Context Protocol (MCP) integration, ADK agents, fine-tuning, and AI infrastructure, with 35 free monthly credits to practice in real environments. Non-technical content emphasizes leadership, Gemini Enterprise, NotebookLM, short practical lessons, and skill badges or certification prep to validate progress.

🚀 Amazon Web Services today announced a preview of Amazon EC2 X8i, a next-generation memory-optimized instance family built on custom Intel Xeon 6 processors. X8i offers up to 6 TB of memory—1.5× the capacity of X2i—and up to 3.4× the memory bandwidth of the previous generation. AWS reports 35% higher overall performance compared with X2i, and X8i is SAP-certified with a 46% SAPS increase for mission-critical SAP deployments. The instances target in-memory databases, large-scale databases, analytics, and EDA workloads; customers can request preview access to evaluate performance and fit.