All news with #google cloud tag

🔒 Google Cloud published a recommended security checklist based on Minimum Viable Secure Product principles, offering 60 curated controls across six domains to help organizations harden cloud environments. The tiered Basic, Intermediate, and Advanced guidance is designed to be simple and scalable. It’s also automatable via a companion Terraform repository and positioned as AI-ready to support adoption of agentic AI. Early customers reported the checklist enabled rapid activation of critical controls and hardened baselines in a single session.

🚗 BMW Group and Google Cloud present a proof-of-concept pipeline to compress, fine-tune, evaluate, and deploy domain-specific small language models (SLMs) for in-vehicle voice commands. They position SLMs as a practical compromise between full cloud-based LLMs and constrained onboard hardware, reducing latency and network dependence. Using Vertex AI Pipelines, the automated workflow explores quantization, pruning, distillation, LoRA fine-tuning, and RL-based alignment, and validates models on Android/AOSP head-unit environments. The team publishes the pipeline code to encourage reuse and reproducible experimentation.

🚀 H4D VMs are now generally available on Google Cloud, powered by 5th Gen AMD EPYC processors and featuring Cloud RDMA on the Titanium network adapter. They deliver substantial throughput and scaling gains across HPC domains—healthcare, manufacturing, EDA and weather—while supporting Slurm and GKE orchestration, Cluster Toolkit, Google Cloud Batch and DWS consumption models. Google cites multi-node benchmark speedups up to 5.8× and access to compute as low as $0.03 per core‑hour.

🔧 Google Cloud is extending its Autonomous Network Operations framework with the Gemini-powered Autonomous Data Steward and a Core Network VoLTE Agent, developed with Future Connections and piloted by One NZ. The Steward provides a zero-copy data layer using Dataplex Universal Catalog to expose metadata pointers and give agents access to real-time telemetry without duplicating datasets. The VoLTE Agent leverages that foundation for continuous monitoring, intelligent root-cause analysis of signaling and probe data, and autonomous recommendations to improve voice quality and accelerate operational tasks.

🔗 Google Cloud describes using graph-based digital twins and GraphML to enable autonomous telecommunications networks that self-configure, self-optimize, self-heal and self-secure with minimal human intervention. The post outlines an integrated stack combining tf-GNN and NetAI's fine-tuned GNNs to model live topology and dependencies as input for deterministic root-cause analysis. A MasOrange PoC at MWC 2026 showcases managed AIOps driven by these models.

🚀 Google Cloud demonstrates how Google Kubernetes Engine (GKE) can form a high-performance foundation for telco modernization via two complementary paths: cloud-centric evolution for full cloud migration and strategic hybrid modernization to retain local control over latency-sensitive functions. The post highlights carrier-grade enhancements—multi-networking API, simulated L2, a telco CNI, persistent IP, and GKE IP route—with sub-second convergence and HA Policy to minimize downtime. It frames modernization as a means to enable predictive AIOps, intent-driven automation, faster time-to-market, and new monetization opportunities through AI and data platforms.

📡 Google Cloud and DigitalRoute are delivering reusable, cloud-native data pipelines that turn diverse telecom telemetry into AI-ready datasets. Running DigitalRoute’s Usage Engine Private Edition on GKE, the solution normalizes proprietary formats at edge and core, filters noise, and routes data into Spanner for real-time digital twins and BigQuery for large-scale analytics and training with Vertex AI. The result is consistent, contextualized subscriber traces that accelerate production-grade autonomous network use cases.

🧭 This post launches Google Cloud's "Data Strategy = AI Strategy" series and reframes the database as the central context engine for production AI. It argues that by using fully PostgreSQL-compatible services such as AlloyDB and Cloud SQL, teams can eliminate latency and improve retrieval accuracy while reducing infrastructure friction. The article emphasizes three enterprise pillars — speed, scale, and security — and describes hands-on labs that cover batch embeddings, real-time inference with Gemini 3 Flash, and row-level security for zero-trust agents.

🚀 Google Cloud and Nokia announced an integration at MWC Barcelona that connects Nokia Network as Code (NaC) with Google Cloud’s agentic AI stack to enable AI agents to observe, program, and optimize mobile networks autonomously. The collaboration leverages Gemini models and standardized protocols such as A2A and MCP to translate natural-language intent into network actions. An Agent Development Kit (ADK) allows enterprises to build custom multi-agent workflows that bridge business logic and network intelligence, delivering a zero-code, intent-driven developer experience.

🔒 This Google Cloud blog outlines a reference architecture to deliver private-IP only connectivity for retrieval-augmented generation (RAG) applications that must not transit the public internet. It describes a multi-project topology—routing project, Shared VPC host, and service projects for Data Ingestion, Serving, and Frontend—and maps required services such as Cloud Interconnect/Cloud VPN, Network Connectivity Center, Private Service Connect, Cloud Router, Cloud Armor, and VPC Service Controls. The post also details RAG population and inference flows to show end-to-end private traffic paths and highlights management and routing orchestration for hybrid and VPC spokes.

🚀 At MWC Barcelona, Google Cloud outlines a shift from AI-driven insights to agentic telco operations, showcasing tools that embed AI into network control to achieve Level 4–5 autonomy. The company highlights a dynamic network digital twin, a unified graph data layer using Spanner Graph and BigQuery, and real-time GNN predictions in Vertex AI. New open-source telco data pipelines and two proof-of-value agents — a data steward and autonomous network agents — aim to accelerate trials and reduce legacy bottlenecks.

🔒 Eventarc Advanced is Google Cloud’s serverless eventing platform that separates centralized governance from distributed processing to balance SecOps control with developer autonomy. The platform uses a managed bus to enforce IAM, content-based access control, VPC Service Controls and required metadata while team-owned pipelines perform schema-aware transforms, format conversion, retries and destination auth. Generally available in August 2025, it addresses historical ESB and EDA governance gaps by combining fine-grained policy with team-level integration logic.

🧠 This article describes a polyglot storage pattern on Google Cloud to preserve conversational continuity for scaled chatbots. It recommends Memorystore for Redis for sub‑millisecond short‑term context, Cloud Bigtable as a petabyte‑scale mid‑term system of record, and BigQuery for long‑term archival and analytics. The design delegates unstructured artifacts to Cloud Storage and uses an async pipeline to balance low latency and durable persistence. Practical configuration and migration pointers help teams implement responsive, analyzable agent memory.

🛡️ Google Threat Intelligence Group, Mandiant, and partners executed a coordinated disruption against a global espionage campaign attributed to UNC2814 that abused cloud services for covert command and control. Investigators identified a novel C-based backdoor called GRIDTIDE that uses Google Sheets APIs as a high-availability C2 channel, protected by an AES-128-CBC key and service account credentials. Actions included terminating attacker-controlled Google Cloud projects, disabling accounts and Sheets API access, sinkholing infrastructure, and publishing IOCs and detection guidance to support defenders.

🔌 Google Cloud now offers managed MCP servers for databases and developer tooling, enabling MCP-compliant AI agents (including Gemini) to access data and infrastructure without deploying additional infrastructure. The expansion adds AlloyDB for PostgreSQL, Spanner, Cloud SQL, Bigtable and Firestore, plus a Developer Knowledge MCP server for IDE documentation access. These servers use IAM-based authentication and Cloud Audit Logs for observability and governance, letting teams scale agentic workloads securely.

🔷 Google Spanner has been ranked #1 by Gartner in the Critical Capabilities report for the Lightweight Transactions use case for the second consecutive year and #2 for OLTP. The post highlights Spanner’s distributed transaction support (5.0/5.0), high transactional consistency (4.9/5.0), and AI/ML integration (4.6/5.0). It also summarizes 2025 product advances—Spanner Graph GA, integrated hybrid search, a columnar engine, and Cassandra-compatible APIs—and cites customer deployments at Palo Alto Networks, Mercado Libre, and Unico.

🔗 Ab Initio and Google Cloud announce integrations of data connectors, metadata connectors, and agent capabilities to help enterprises build agentic AI across hybrid environments. The integration federates distributed data into a unified layer and extends Dataplex with bi-directional metadata exchange, lineage, and active metadata. Together with BigQuery and Gemini, this enables explainable, auditable agents that operate on trustworthy, multi-cloud data.

🔗 Google Cloud and Ab Initio announced an integrated suite of data and metadata connectors, agents, and governance capabilities to give Gemini and other AI models reliable access to enterprise data across hybrid environments. The partnership federates over 500 sources and supplies field-level lineage from 100+ extractors to populate Dataplex and BigQuery with AI-ready context. This unified metadata hub aims to support explainable, auditable agentic AI while preserving distributed data ownership and compliance.

🔗 Gemini CLI's Neo4j extension connects graph databases to Gemini's reasoning via the Model Context Protocol (MCP). The extension bundles four MCP servers to manage Neo4j Aura, translate natural language into Cypher, support interactive data modeling and visualization, and use Neo4j as long-term memory for agentic flows. Developers can provision databases, run Cypher queries, and persist knowledge from the terminal to accelerate GraphRAG workflows.

💡 Google Cloud updated its spend-based Committed Use Discounts (CUDs), moving from a credit-based model to a direct discounted price model that makes net costs and savings visible at a glance. The rollout began in July 2025 and is now generally available, expanding SKU coverage to include Cloud Run and H3/M-series VMs and correcting reporting gaps for mixed Flex CUD environments. The unified CUD Analysis provides hourly granularity (up to 30 days), CSV exports, and a metadata export for programmatic joins with Billing BigQuery Export datasets. Enhanced recommendation and scenario modeling let FinOps teams size commitments, tune coverage thresholds, and validate pre/post migration savings.