All news with #google cloud tag

🔐 In Google Cloud, IAM enforces the Principle of Least Privilege by combining predefined and custom roles with Allow and Deny policies across resource hierarchies. When resource-level bindings are not possible, IAM conditions let you scope broad roles to specific APIs, services, MCP servers, tools, or time windows. Use conditions alongside Deny policies to surgically remove excessive permissions and strengthen defense-in-depth.

🛠️ Panasonic Automotive’s vSkipGen virtualization platform is validated on Google Cloud’s Axion-based C4A-metal, enabling cloud-native development and validation of Cockpit Domain Controller (CDC) software. The solution pairs vSkipGen’s Unified HMI remote GPU offload with support for Android Automotive OS and Android SDV to provide high-fidelity graphics, VirtIO device virtualization, and integration with automotive simulators. C4A-metal delivers high-performance Arm-based bare metal instances optimized for digital twins, accelerated testing, and scalable CI/CD pipelines.

🔎 Google Cloud outlines how to integrate Gemini Enterprise telemetry into BigQuery to enable scalable analytics and governance. The article explains pre-computed dashboards, streaming log sinks, and five partitioned telemetry tables for prompts, model responses, user activity, and audit logs. It highlights BigQuery Conversational Analytics, auto-generated schema documentation, and techniques to build executive dashboards and compliance workflows.

🛡️ This post from Mandiant highlights how publicly exposed serverless applications — often unauthenticated by design — are frequent targets for application-level attacks like LFI/RFI and command injection. It explains exploitation paths including file retrieval and service account token exfiltration, and demonstrates attack examples against Cloud Run Python functions. The article provides actionable hardening guidance such as using dedicated service accounts with least privilege, isolating public services in separate projects, enforcing S‑SDLC practices, and deploying Cloud Armor WAF and Layer 7 load balancing for centralized protection.

🤖 Claude on Google Cloud pairs Anthropic's frontier models with Google Cloud's managed infrastructure, enabling enterprises to run large-scale AI in production. It provides unified IAM, VPC controls, observability, and global, regional, and multi-region endpoints to meet latency and data-residency needs. Built-in model features like prompt caching, streaming, and extended context combine with Google Cloud serving capabilities such as batch prediction and provisioned throughput for cost and performance optimization.

🛡️ Today Google Cloud announced that on July 10 the U.K. Treasury designated Google Cloud EMEA as a critical third party (CTP) to the U.K. financial sector. The designation acknowledges the systemic impact of services used by U.K. firms and places Google Cloud EMEA under direct oversight by the Bank of England, PRA, and FCA. Google Cloud commits to constructive engagement with regulators and to help customers meet operational resilience and third‑party risk requirements.

🔧 Smart Tiered Cache now supports public cloud regions by accepting a user-provided region hint. Cloudflare maps ambiguous anycast or regional unicast origins to the correct cloud region so it can select optimal primary and fallback upper tiers, improving cache efficiency and reducing hairpin latency. The feature is available via dashboard, API, and Terraform and initially supports AWS, GCP, Azure, and Oracle Cloud.

🛡️ Cloud Run sandboxes are now in public preview, offering a native, secure, and ultra-fast runtime to execute untrusted code and agent workloads in milliseconds. These lightweight, isolated execution boundaries can spawn within existing Cloud Run service instances and enforce credential isolation, deny-by-default network egress, and a safe read-only filesystem overlay. Enabling sandboxes requires a single deployment flag and integrates with the Agent Development Kit and ComputeSDK for streamlined use.

🚀 C4N is Google Cloud’s new network- and block-storage-optimized Compute Engine instance family, now generally available after its Next ’26 preview. Built on a custom Titanium offload architecture and 5th Gen Intel Xeon CPUs, C4N delivers up to 400 Gbps network bandwidth, 95M PPS, and up to 25 GiB/s with Hyperdisk Extreme. It targets network-intensive, storage-heavy, and latency-sensitive workloads without requiring premium add-ons.

🛡️ Google for Startups has selected 33 cybersecurity startups for the Gemini Startup Forum: Cybersecurity, pairing each company with experts from Google DeepMind, Google Cloud, and Wiz. The cohort addresses six focus areas including autonomous agent protection, post-quantum cryptography, and data-in-use protection. Startups span agent security, cloud posture, DLP, cryptography, and AI-native SOC tooling. The forum offers APIs, tools, training, and technical resources to accelerate AI-native security innovations.

🧭 This guide explains how to build, register, and commercialize AI agents as Agents-as-a-Service (AaaS) for deployment in the Gemini Enterprise app and Google Cloud Marketplace. It details required artifacts like the A2A Agent Card, authentication options including OAuth and Dynamic Client Registration (DCR), and the integration points for procurement, billing, and entitlement management. The article also outlines the seller journey, testing, and the end-to-end procurement and registration lifecycle across Billing Administrator, Discovery Engine Administrator, and end-user roles.

🧭 This Google Cloud blog summarizes findings from a survey of over 1,400 IT leaders showing a widening gap between AI ambitions and existing infrastructure. It explains why agentic AI stresses legacy systems and highlights needs for fluid compute, unified data layers, hybrid deployments, and energy-efficient co-designed silicon like TPU 8t. The post also promotes Google Cloud’s AI Hypercomputer and governance solutions such as Agent Gateway.

🔒 Google Cloud and Valtech introduce Nexus SDV, an open-source, modular platform that enables AI-native, scalable management of software-defined vehicles. The platform integrates with Android Automotive OS and supports up to 100 million devices while emphasizing TCO reduction via Arm-based compute and Bigtable. Nexus AI leverages Gemini models and the Gemini Enterprise Agent Platform for real-time telemetry analysis and agentic vehicle capabilities. Security is built-in with mTLS/PKI, identity brokering, secret management, network isolation, and an enterprise Secure AI Framework.

🔍 AlloyDB introduces AI-native capabilities that bring Gemini’s foundation-model intelligence directly into the database via AI functions. The post announces GA for core functions (ai.generate, ai.rank, ai.if, ai.forecast) and three new functions: ai.summarize, ai.agg_summarize, and ai.analyze_sentiment, enabling structured extraction, summarization, and sentiment classification inside SQL. AlloyDB also adds Smart Batching and an optimized proxy-model mode to massively improve throughput and reduce LLM calls and costs.

🔒 Anthropic’s Claude Apps Gateway is a self-hosted intermediary that centralizes identity, policy, telemetry, spend controls, and routing between local Claude Code clients and Google Cloud. It replaces per-developer credentials with OIDC-based sessions, enforces RBAC server-side via gateway.yaml, and attributes metrics to verified user sessions. Deploy as a stateless container on Cloud Run (or GKE) with Cloud SQL and Secret Manager for state and secrets.

🔒 Google Cloud announced completion of a Dutch data protection impact assessment (DPIA) by SLM Rijk, confirming there are no known high data protection risks when recommended measures are applied. The outcome enables the Dutch central public sector to adopt Google Cloud from a privacy-assessment perspective and builds on earlier DPIA work for Google Workspace. Google emphasizes continued investment in privacy-enhancing technologies and support resources for customers.

📘 Enterprise LLM deployments face KV cache growth that can exceed node RAM and local SSD capacity. Google Cloud demonstrates using Managed Lustre as a shared, high-performance external KV cache tier integrated with vLLM and the llm-d offloading stack to bypass host-level limits and simplify cross-node data management. Benchmarks with Llama-3.3-70B on a six-node A3 Mega cluster show over 50% TCO savings and nearly 60% reduction in GPU-hour usage by achieving a 95% cache hit rate. The guide includes architecture, deployment steps, PVC evictor behavior, and validated tracks for Qwen and Gemma models.

🔒 Google Cloud introduces AlloyDB Omni, a hybrid deployment of AlloyDB for PostgreSQL designed to modernize financial services databases while preserving data residency and regulatory compliance. The offering promises PostgreSQL compatibility to reduce vendor lock-in, high transactional performance, and integrated analytics and AI capabilities delivered on-premises, at the edge, or in hybrid clouds. It targets legacy licensing, sovereignty, and real-time insights gaps, and highlights customer outcomes demonstrating faster transactions and accelerated analytics.

🧪 Schrödinger partnered with Google Cloud and DeepMind to deploy AlphaEvolve, an evolutionary AI coding agent that iteratively generates and refines algorithms to remove bottlenecks in MLFF training pipelines. The team targeted neighbor list computation and the Ewald summation in PyTorch, replacing slow for-loops with a batched parallel matrix multiplication implementation. This optimization increased the success rate of correct and faster programs from under 1% to over 60% and delivered a 4× speedup in training and inference, accelerating workflows in drug discovery, catalyst design, and materials development.

🔔 Google Cloud announces preview support for long-lookback alert policies in Cloud Monitoring using PromQL, enabling queries across up to two years of metric history. The feature unlocks dynamic thresholding—alerts that compare recent behavior to historical baselines—helping catch anomalies that static thresholds miss. Google outlines example algorithms (moving averages, z-score, and seasonal time-offsets), discusses trade-offs like flakiness for new workloads, and shows a practical use case for preventing runaway spend.