All news with #google cloud tag

🛡️ 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.

🔍 Curve partnered with Google Cloud to adopt BigQuery Graph, moving beyond relational joins to perform multi-hop network analysis across billions of connections. By modeling users and shared identifiers as a property graph, they can traverse massive datasets with GQL, combine graph traversals with standard SQL and ML workflows, and avoid costly data migrations. This integration has improved detection, operational efficiency, and enabled plans for real-time signals and visualization.

🔒 Google Cloud describes how it embeds modular AI agents across the software development lifecycle to create autonomous security guardrails. The approach includes centralized code analysis via the Mantis framework, multi-agent fuzz testing with self-reflection, and an autonomous patching pipeline that validates fixes before human review. Continuous reflection and a programmable posture management system help convert lessons into reusable skills that improve remediation speed and reduce false positives.

🔒 Google Cloud announces new VPC Service Controls features to secure agentic AI deployments by enforcing network-level perimeters and integrating agent identities. These updates let administrators add agent principals and principalSets to ingress/egress rules, apply conditional rules based on MCP attributes like mcp.toolName and mcp.method, and automatically protect the Gemini Enterprise Agent Platform from public internet access. The enhancements are designed to complement IAM and resource policies to prevent exfiltration and tool misuse in production agent fleets.

📣 Google Cloud now lets you create alerts in Observability Analytics using SQL to query logs and traces. This preview feature runs scheduled SQL queries via BigQuery on telemetry linked datasets and supports row count and boolean conditions. When conditions are met, Cloud Monitoring opens incidents and notifies configured channels. Note that BigQuery execution costs apply under your billing model.

🔒 Google Cloud announces general availability of cross-region backups for its Backup and DR Service. This release decouples backup destinations from source regions, enabling backups to be stored in distinct geographic regions to improve resilience and meet data residency requirements. The capability is available now for Compute Engine instances, Disks, and Filestore, with Cloud SQL and AlloyDB support coming soon.

🔒 Google Cloud announces expanded Confidential Computing capabilities to protect data in use for AI workloads. The update includes Confidential G4 VMs with NVIDIA RTX PRO 6000 Blackwell GPUs, open-source Prompt Encryption SDKs, Intel TDX on C4 machines, and broader Confidential Space enhancements. These innovations aim to provide verifiable attestation, end-to-end encrypted inference, and support for multi-party collaboration while preserving performance and scalability.

🛠️ Google Cloud announced enhancements to its Observability suite, rebranding Log Analytics as Observability Analytics and bringing trace data and the Observability API to general availability. The update unifies logs and traces, enables SQL queries across telemetry, and allows in-place analysis without duplicating data. Use cases include diagnosing AI agent tool failures and correlating latency with customer impact. Users can link observability buckets to BigQuery and run cross-dataset analytics directly in the Cloud console.