All news with #google cloud tag

🚀 The G4 VM is now generally available on Google Cloud, powered by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs and offering up to 768 GB of GDDR7 memory per instance class. It targets latency-sensitive and regulated workloads for generative AI, real-time rendering, simulation, and virtual workstations. Features include FP4 precision support, Multi-Instance GPU (MIG) partitioning, an enhanced PCIe P2P interconnect for faster multi‑GPU All-Reduce, and an NVIDIA Omniverse VMI on Marketplace for industrial digital twins.

🔐 Dataproc 2.3 on Google Compute Engine provides a streamlined image that includes only the essential core components for Spark and Hadoop, reducing the attack surface and simplifying compliance. The image is FedRAMP High compliant and leverages both automated CVE remediation and manual engineering intervention for complex fixes. Optional tools like Flink, Hudi, Ranger, and Zeppelin are available on-demand during cluster creation, or can be pre-baked into custom images to speed provisioning while preserving the security benefits of the lightweight base.

🔧 Google Cloud’s Q3 AI Hypercomputer update highlights inference improvements and expanded tooling to accelerate model serving and diagnostics. The release integrates vLLM with Cloud TPUs via the new tpu-inference plugin, unifying JAX and PyTorch runtimes and boosting TPU inference for models such as Gemma, Llama, and Qwen. Additional launches include improved XProf profiling and Cloud Diagnostics XProf, an AI inference recipe for NVIDIA Dynamo, NVIDIA NeMo RL recipes, and GA of the GKE Inference Gateway and Quickstart to help optimize latency and cost.

🏆 Google Cloud announced it was named a Leader in the 2025 IDC MarketScape for Worldwide GenAI Life-Cycle Foundation Model Software, spotlighting the Gemini model family and the Vertex AI platform. The post highlights Gemini 2.5’s expanded “thinking” capabilities and new cost controls such as thinking budgets and thought summaries for improved auditability. It also underscores native multimodality, creative variants like Nano Banana, developer tooling including the Gemini CLI, and enterprise features for customization, grounding, security, and governance.

🚀 Google Cloud's newly GA G4 VMs combine NVIDIA RTX PRO 6000 Blackwell GPUs with a custom, software-defined PCIe fabric to enable high-performance peer-to-peer (P2P) GPU communication. The platform accelerates collective operations like All-Gather and All-Reduce without code changes, delivering up to 2.2x faster collectives. For tensor-parallel inference, customers can see up to 168% higher throughput and up to 41% lower inter-token latency. G4 integrates with GKE Inference Gateway for horizontal scaling and production deployments.

🤖 This post explains how System Integrator partners can build, scale, and manage enterprise-grade AI agents using Google Cloud technologies like Agent Engine, the Agent Development Kit (ADK), and Gemini Enterprise. It summarizes architecture patterns including runtime, memory, the Model Context Protocol (MCP), and the Agent-to-Agent (A2A) protocol, and contrasts managed Agent Engine with self-hosted options such as Cloud Run or GKE. Customer examples from Deloitte and Quantiphi illustrate supply chain and sales automation benefits. The guidance highlights security, observability, persistent memory, and model tuning for enterprise readiness.

🔍 The Oklahoma Employment Security Commission modernized its 40‑year mainframe data architecture with a cloud-first data platform built on BigQuery and analytics delivered via Looker. Partnering with Google Public Sector and Phase2, OESC reorganized opaque, mainframe-mimicking schemas into a performant, intuitive model and enabled point-in-time snapshots previously impossible. Critical reporting moved from months to hours, stakeholders gained self-service access, and the agency unlocked employer insights that supported tax analysis, improved auditability, and accelerated fraud detection.

🛠️ Google Cloud demonstrates how the Gemini CLI and GKE Inference Quickstart integrate via the Model Context Protocol (MCP) to streamline selecting, benchmarking, and deploying LLMs on GKE. The post outlines installation steps, example prompts to discover cost and performance trade-offs, and how manifests can be generated for target accelerators. This approach reduces manual tuning and provides data-driven recommendations to optimize cost-per-token while preserving performance.

🚀 Google has made Axion-powered C4A and Intel-based N4 virtual machines generally available for Cloud SQL Enterprise Plus and Enterprise editions, promising substantial gains in throughput and price-performance. Hyperdisk Balanced storage is supported on both families to boost I/O, increase throughput, and allow independent configuration of capacity, throughput, and IOPS. Customer tests report lower costs, reduced latency, and large throughput gains. These machines are available in select regions; check Cloud SQL pricing and region documentation for details.

🔧 BigQuery Studio unveils a simplified, organized console interface designed to help data analysts, engineers, and scientists work more efficiently. The update introduces an expanded Explorer view for easier resource discovery, a context-aware Reference panel that surfaces table schemas and lets you insert query snippets, and a decluttered layout including a dedicated Job history tab. These changes reduce context switching and tab proliferation so users can focus on analysis.

🔎 Moloco’s AI-native retail media platform, integrated with Vertex AI Vector Search on Google Cloud, delivers semantic, real-time ad retrieval and personalized recommendations. The joint architecture uses TPUs and GPUs for model training and scoring while vector search runs efficiently on CPUs, enabling outcomes-based bidding at scale. Internal benchmarks report ~10x capacity, up to ~25% lower p95 latency, and a ~4% revenue uplift. The managed service reduces operational overhead and accelerates time-to-value for retailers.

🎬 This guide introduces Veo 3.1, Google Cloud's improved generative video model available in preview on Vertex AI, and explains how to move beyond "prompt and pray" toward deliberate creative control. It highlights core capabilities—high-fidelity 720p/1080p output, variable clip lengths, synchronized dialogue and sound effects, and stronger image-to-video fidelity. The article presents a five-part prompting formula and detailed techniques for cinematography, soundstage direction, negative prompting, and timestamped scenes. It also describes advanced multi-step workflows that combine Gemini 2.5 Flash Image to produce consistent characters and controlled transitions, and notes SynthID watermarking and certain current limitations.

🤝 At the end of October in Washington, D.C., Google Cloud and NVIDIA will lead a week of events highlighting advances in AI, high-performance computing, and secure mission deployments. NVIDIA GTC DC (Oct. 27–29) features keynotes, demos, and hands-on sessions showcasing next-generation models and infrastructure. The Google Public Sector Summit (Oct. 29) convenes government leaders to explore practical uses of technologies like Gemini for Government and discuss secure, scalable AI adoption for mission impact.

🤖 LiveX AI outlines a Google Cloud blueprint to scale conversational customer experiences across chat, voice, and avatar interfaces. The post details how Cloud Run hosts elastic front-end microservices while GKE provides GPU-backed AI inference, and how AgentFlow orchestrates conversational state, knowledge retrieval, and human escalation. Reported customer outcomes include a >90% self-service rate for Wyze and a 3× conversion uplift for Pictory. The design emphasizes cost efficiency, sub-second latency, multilingual support, and secure integrations with platforms such as Stripe, Zendesk, and Salesforce.

🚀 Google Cloud announced enhancements to NetApp Volumes, adding unified iSCSI block and file storage to support SAN migrations and NetApp FlexCache for high-performance local caching in hybrid environments. The service integrates with Gemini Enterprise as a data store for retrieval-augmented generation, and includes large-capacity volumes, SnapMirror replication, and auto-tiering to optimize performance and costs.

🚀 Google Cloud announces the general availability of open-source IBM Spectrum Symphony HostFactory connectors for Google Compute Engine and GKE. The connectors enable organizations to extend on‑premises Symphony clusters into Google Cloud or deploy fully cloud-native clusters with automatic provisioning and decommissioning to match workload demand. Partner-built by Accenture and validated by Aneo, the connectors support enterprise features such as Spot and on‑demand VMs, GPUs, Local SSD, Confidential VMs, Pub/Sub event-driven management, Kubernetes CRDs, and integration with managed instance group (MIG) APIs for large-scale HPC operations.

🤖 Google Cloud Marketplace offers a vetted path for organizations to deploy, buy, or build AI agents that integrate with Gemini Enterprise, simplifying procurement and deployment. Listings are pre-validated for A2A integration and allow consolidated billing, while administrators can enforce governance using IAM and Private Marketplace controls. For partners, the Marketplace provides global reach, co-selling, and flexible monetization (subscription, usage-based, private offers, outcome-based) plus automated provisioning via Pub/Sub and the Cloud Commerce Partner Procurement API.

🧠 Google Cloud is introducing two Cloud Storage features—auto annotate and object contexts—that apply pretrained AI to generate metadata and attach custom key-value tags to stored objects. Auto annotate (experimental) produces image annotations such as object detection, labels, and objectionable-content signals tied to an object's lifecycle. Object contexts (preview) let teams add, manage, and query contextual tags with IAM controls and Storage Insights integration. Together they enable scalable discovery, curation, and governance of previously unanalyzed unstructured “dark data.”

🔒 BigQuery data clean room query templates are now available in preview, enabling clean room owners to publish fixed, reusable TVF-based queries that accept table or field inputs and return only aggregated rows. Templates reduce data exfiltration risk, simplify onboarding for non-SQL users, and enforce consistent analytical and privacy controls via aggregation thresholds and approval workflows. They support single-direction and multi-party collaboration while keeping query logic hidden from subscribers.

⚙️ This post introduces the fundamentals of chaos engineering and explains why deliberately injecting controlled failures helps teams build more resilient cloud-native systems. It covers core principles — such as defining a steady-state hypothesis, limiting blast radius, replicating realistic failure modes, and automating experiments — and translates them into practical steps for experiment design, fault injection, probing, and rollback. The article recommends using Chaos Toolkit and points to Google Cloud–specific recipes to help engineers begin safely and iteratively.