All news with #google cloud tag

📚 Google Cloud has consolidated all technical documentation onto a new, dedicated platform to improve discoverability and support AI-driven experiences. By centralizing content on a unified site and integrating Gemini into authoring tools, Google aims to accelerate content creation and deliver context-aware assistance. The site offers faster performance, AI-powered translation across 12 languages, and preserves existing URL patterns to minimize disruption.

🚀 Giles AI migrated its healthcare-focused platform to Google Cloud to reduce latency, improve scalability, and accelerate developer velocity. Using Google Kubernetes Engine, Cloud Run, and Compute Engine, the company orchestrates complex clinical data flows and routes prompts through Vertex AI and Model Garden to remain model-agnostic. Data storage and extraction are handled with Cloud SQL, Cloud Storage, and Document AI, while Cloud Armor and Security Command Center bolster security and compliance. Early customer results include dramatic reductions in research time and improvements in response accuracy.

🚀 Google Cloud is previewing managed DRANET on GKE, enabling Kubernetes to treat high-performance RDMA network interfaces as schedulable resources. The integration aligns NICs and GPUs by NUMA topology to reduce latency and increase throughput, while abstracting away operational complexity. It launches with the new A4X Max instances to deliver topology-aware networking for large multi-GPU AI workloads. Developers can request specific network interfaces in pod specs and rely on GKE to co-schedule NICs and accelerators, improving utilization and simplifying operations.

🚀 Google Cloud is expanding its NVIDIA collaboration with the new A4X Max instances powered by NVIDIA GB300 NVL72, delivering 72 GPUs with high‑bandwidth NVLink and shared memory for demanding multimodal reasoning. GKE now supports DRANET for topology‑aware RDMA scheduling and integrates NVIDIA NeMo Guardrails into GKE Inference Gateway, while Vertex AI Model Garden will host NVIDIA Nemotron models. Vertex AI Training adds NeMo and NeMo‑RL recipes and a managed Slurm environment to accelerate large‑scale training and deployment.

🔁 This Google Cloud post explains how enterprises can integrate Oracle Database with cloud-native analytics and AI by moving transactional data into BigQuery. It recommends ingestion patterns such as low-latency Change Data Capture via Datastream, batch staging to Cloud Storage, and notes ODBC/JDBC for interactive queries but not continuous replication. Once data resides in BigQuery, organizations can leverage Gemini-powered features, BigQuery ML, and AI agents (via the Agent Developer Kit) for natural-language exploration, assisted coding, multimodal analysis, and automated workflows across retail and education use cases.

🔐 Google Cloud outlines a pragmatic framework to secure the emerging agentic web while preserving smooth user experiences. The post details how reCAPTCHA and Google Cloud combine agent and user identity, continuous behavior analysis, and AI-resistant mitigations such as mobile-device attestations. It highlights enabling safe agentic commerce via protocols like AP2 and tighter integration with cloud AI services.

🚀 At Partner Connect during the Google Public Sector Summit, Google announced expanded investments to deepen collaboration and accelerate AI adoption across the public sector partner ecosystem. Highlights include increased Rapid Innovation Team funding, doubled capacity for Partner Development Sprints, and boosted Deal Acceleration Funds to shorten sales cycles. Google also launched three new Public Sector Partner Expertise badges for Google Distributed Cloud, Infrastructure Modernization, and Gemini for Government, a standardized Services Subcontractor Program, and an expanded ISV ATO Accelerator offering up to $250,000 in GCP credits plus $500,000 in services reimbursements to speed FedRAMP/Impact Level readiness. Partner Demo Portal improvements, enhanced analytics, new labs, and bootcamps round out efforts to simplify co-selling and accelerate partner time-to-market.

🛒 PayPal and Google Cloud announced a joint agentic commerce offering that integrates Google Cloud’s Conversational Commerce agent with payments powered by PayPal. The solution leverages the open Agent2Agent (A2A) Protocol and the Agent Payments Protocol (AP2)—which extends A2A and the Model Context Protocol—to enable agent-to-agent payment flows secured by Verifiable Digital Credentials. Merchants can deploy Google’s out‑of‑the‑box conversational agent or build custom agents with the Agent Development Kit (ADK), retaining control over tone, branding, and the customer relationship while benefiting from integrated payment and fraud controls.

🔔 Google Cloud previewed Bigtable tiered storage, which automatically moves less-frequently accessed data from high-performance SSD storage to an infrequent access tier while exposing the same Bigtable API. The fully managed feature integrates with Bigtable autoscaling so applications can read and write across hot and cold tiers via a single interface. Google says the infrequent access tier can be up to 85% less expensive than SSD and that a tiered-storage node offers substantially more usable capacity, making it suited for large time-series and telemetry datasets that require long-term retention for analytics or compliance.

🚀 Vertex AI Training introduces managed features designed for large-scale model development, simplifying cluster provisioning, job orchestration, and resiliency across hundreds to thousands of accelerators. The offering integrates Cluster Director, Dynamic Workload Scheduler, optimized checkpointing, and curated training recipes, including NVIDIA NeMo support. These capabilities reduce operational overhead and accelerate transitions from pretraining to fine-tuning while improving cost and uptime efficiency.

🔗 Google Cloud announced that Cross-Site Interconnect is now generally available, providing a cloud-delivered, transparent layer 2 connectivity overlay for global WANs. The service uses Google’s global backbone to deliver high-bandwidth, on-demand links with a 99.95% SLA, dynamic consumption pricing, and support for MACsec encryption and VLAN-based multi-destination handoffs. It exposes operational metrics via dashboards and APIs so teams can monitor latency, loss, and utilization while abstracting failover and resiliency management.

🔒 Google Cloud's Parameter Manager centralizes application configuration to avoid hard-coded credentials and fragile config files, supporting validated JSON and YAML payloads as well as arbitrary unformatted data. It integrates with Secret Manager using a __REF__ syntax to keep confidential values separate and uses versioned, immutable parameter versions to prevent accidental changes. The post walks through storing an API key in Secret Manager, granting the Parameter Manager IAM principal access, and calling renderParameterVersion from a Node backend. A sample React/Node weather app demonstrates runtime configuration, fallback dummy data, and advanced patterns such as regional parameters and feature rollouts.

🌐 This blog presents a reference architecture for deploying Network Virtual Appliances (NVAs) in a regional hub-and-spoke design using VPC Network Peering. It explains how Google’s Cross-Cloud Network and software-defined global backbone support any-to-any connectivity while preserving regional affinity for latency and data residency. The post details traffic flows and key services such as Cloud Interconnect, HA VPN, Internal Passthrough Network Load Balancers, policy-based routes, and Private Service Connect to integrate managed services and workload VPCs.

🔐 Organizations are rapidly replacing embedded API keys and passwords with platform-native managed identities to reduce manual credential management and leakage risk. Enterprises report significant productivity gains—case studies cite up to a 95% reduction in time spent managing credentials and a 75% drop in time learning platform authentication. While major clouds (AWS, Azure, GCP) and CI platforms have built-in solutions, legacy systems and third-party APIs remain the primary obstacles to eliminating static secrets entirely.

⚡ Google Cloud announced the H4D VM family (Preview), powered by 5th Gen AMD EPYC processors (Turin), aimed at delivering extreme performance for financial services workloads. The H4D series targets latency-sensitive use cases such as high-frequency trading, Monte Carlo risk simulations, backtesting, and derivatives pricing by offering faster core-to-core communication, larger memory capacity, and improved network throughput. AMD benchmarking with the open-source KX Nano test reported an average ~34% out-of-the-box performance gain over prior C3D VMs, with per-core and multi-threaded uplifts around 1.33–1.36x. Google Cloud will demonstrate H4D and complementary HPC solutions at STAC Summit NYC on October 28th and will have experts available to discuss performance, security, and compliance.

🔒 Google Cloud’s Model Armor integrates with Apigee to screen prompts, responses, and agent interactions, helping organizations mitigate prompt injection, jailbreaks, sensitive data exposure, malicious links, and harmful content. The model‑agnostic, cloud‑agnostic service supports REST APIs and inline integrations with Apigee, Vertex AI, Agentspace, and network service extensions. The article provides step‑by‑step setup: enable the API, create templates, assign service account roles, add SanitizeUserPrompt and SanitizeModelResponse policies to Apigee proxies, and review findings in the AI Protection dashboard.

🔍 Dataplex Universal Catalog now captures column-level lineage for BigQuery, extending object-level tracing to granular column transformations at no extra cost. The update provides interactive visual lineage graphs so users can inspect upstream and downstream flows for individual columns, trace origins, and assess downstream impact of modifications. This granularity helps validate authoritative sources for AI/ML features, enforce column-level governance, and improve compliance. It also surfaces freshness and usage metadata to support context-aware agents.

🛡️ Cloud Armor introduces hierarchical security policies and organization-scoped address groups to simplify centralized policy management across organization, folder, and project levels. The release also includes GA support for JA4 network fingerprinting and ASN/NTI controls for Media CDN, while an enhanced WAF request-body inspection (preview) expands inspection from 8 KB to 64 KB. These updates are designed to strengthen threat protection and reduce operational complexity for hybrid and multicloud deployments.

🔍 SmarterX uses Google Cloud to build custom LLMs that help retailers, manufacturers, and logistics companies manage regulatory compliance across product lifecycles. Using BigQuery, Cloud Storage, Gemini, and Vertex AI, the company ingests, normalizes, and indexes unstructured regulatory and product data, applies RAG and grounding, and trains customer-specific models. The integrated platform empowers subject matter experts to evaluate, correct, and deploy model updates without heavy engineering overhead.

🔧 Google details how its custom Axion Arm CPUs and a mix of automation and AI enabled large-scale migration from x86 to multi-architecture production across services such as YouTube, Gmail, and BigQuery. The team analyzed 38,156 commits (about 700K changed lines) and reports migrating more than 30,000 applications to Arm while keeping both Arm and x86 in production. Existing automation like Rosie, sanitizers, fuzzers, and the CHAMP rollout framework handled much of the work, while an LLM-driven agent called CogniPort fixed build and test failures, showing a 30% success rate on a 245-commit benchmark. Google plans to default new apps to multiarch and continue refining AI tools to address the remaining long tail.