All news with #google cloud tag

🔒 DZ BANK and Google Cloud present a blueprint for delivering trustworthy off‑chain data to smart contracts, addressing a key barrier to enterprise DLT adoption. The design pairs Google Cloud secure global infrastructure with DZ BANK’s deterministic financial protocols to guarantee data correctness at source, integrity in transit, and timely delivery. The Smart Derivative Contract (SDC) use case demonstrates deterministic valuation, automated margining, and cryptographic attestation of oracle outputs. Production controls such as Binary Authorization, Private Service Connect, Confidential Space (TEE), and TLS are used to mitigate software supply‑chain, transport, and runtime threats.

⚙️ Google Cloud outlines a practical approach to adopt Gen4 VM families by pairing GKE compute classes with Compute Flexible CUDs, enabling prioritized machine-family fallbacks and spend-based discounts. Compute classes let teams define prioritized machine families (for example, N4 then N2) so the cluster autoscaler can provision preferred hardware while preserving availability. Flex CUDs apply discounts across eligible VM families and follow consumption, protecting committed discounts when fallbacks occur. Together these features reduce migration risk and simplify platform operations.

🚀 This roundup highlights how leading organizations are using Google Cloud to optimize networks, accelerate AI, and scale mission-critical services. From Uber reducing edge latency with Hybrid NEGs to Target rebuilding search with AlloyDB AI hybrid search, customers report measurable gains in performance, cost, and reliability. Healthcare, finance, media, and telecommunications teams also describe operational wins — faster inference, seamless migrations, and stronger real-time experiences.

🚀 The U.S. Air Force, working with Google Public Sector and GDIT, deployed the Google Distributed Cloud air-gapped appliance to run classified workloads at the tactical edge in DDIL environments. The rugged, transportable system demonstrated secure, Zero Trust-capable processing up to Secret, delivering on-device AI for transcription, OCR, translation, and summarization during Mobility Guardian 2025 in Guam. It also supported containerized IL2 collaboration, Luna AI integration for low-latency air-defense data, a Jupyter-based edge dev environment, and AI-enabled tele-maintenance to convert manuals and visual data into actionable maintenance insights.

🚀 Google Cloud has launched Flex-start VMs, a Compute Engine consumption option powered by Dynamic Workload Scheduler that lets single VM instances wait in a managed queue for scarce GPUs. By setting request-valid-for-duration (90 seconds–2 hours) users keep capacity requests in PENDING and avoid custom retry logic. Flex-start VMs offer significant discounts versus on‑demand SKUs, consume preemptible quota, run uninterrupted for up to seven days, and integrate directly via the instances.insert API, gcloud CLI, or the Cloud Console. Instances support stop/start to pause billing and an instanceTerminationAction = STOP to preserve configuration when the seven‑day runtime expires.

🚀 Indiana Department of Transportation built a week-long pilot on Google Cloud to meet a 30-day executive order, using a Retrieval-Augmented Generation workflow that combined rapid ETL, Vertex AI Search indexing, and Gemini. The system scraped and parsed decades of internal policies and manuals, produced draft reports across nine divisions with 98% fidelity, and saved an estimated 360 hours of manual effort, enabling INDOT to submit on time.

🤖 DB Lumina is Deutsche Bank Research’s AI-powered assistant, built on Google Cloud and integrating multimodal Gemini models, RAG retrieval, and vector search. It provides a conversational chat interface, reusable prompt templates, and document-grounded answers with inline citations and enterprise guardrails for compliance. Early deployment to roughly 5,000 analysts has yielded measurable time savings, deeper analysis, and improved editorial accuracy.

🧬 Escalante leverages JAX's functional, composable design to combine many predictive models into a single differentiable objective for protein engineering. By translating models (including AlphaFold and Boltz-2) into a JAX-native stack and composing them serially or linearly, they compute gradients with respect to input sequences and evolve candidates via optimization. Each job samples thousands of sequences, filters to roughly ten lab-ready designs, and runs at scale on Google Kubernetes Engine using spot TPU v6e, yielding a reported 3.65x performance-per-dollar advantage over H100 GPUs.

🛡️ CISA released an alert about a widespread software supply chain compromise affecting the npm registry: a self-replicating worm called 'Shai-Hulud' has compromised over 500 packages. The actor harvested GitHub Personal Access Tokens and cloud API keys for AWS, Google Cloud, and Azure, exfiltrating them to a public repository and using them to publish malicious package updates. CISA recommends immediate dependency reviews, credential rotation, enforcing phishing-resistant MFA, pinning package versions to releases before Sept. 16, 2025, hardening GitHub settings, and monitoring for anomalous outbound connections.

🔒 Google has added integrated security dashboards to GCE and GKE consoles, powered by Security Command Center. The dashboards surface top security findings, vulnerability trends, CVE prioritization, and container/workload misconfigurations informed by Google Threat Intelligence and Mandiant analysis. Teams can remediate misconfigurations, prioritize patches, and monitor threats directly in their compute and cluster consoles. Full vulnerability and threat widgets require upgrading to SCC Premium (30‑day trial available).

🚀 Google Cloud announced a new suite of AI training courses for intermediate and advanced learners across technical and non-technical roles. The curriculum covers designing and managing AI infrastructure using GCE and GKE, fine-tuning models like Gemini, serverless inference with Cloud Run, and securing generative AI deployments. Hands-on labs teach building AI agents that securely connect to enterprise databases and rapid prototyping in Google AI Studio. Courses are available on Google Cloud Skills Boost to help learners future-proof their AI skills.

🤖 Seattle Children’s partnered with Google Cloud to build Pathway Assistant, a multimodal AI chatbot that turns thousands of pediatric clinical pathway PDFs into conversational, searchable guidance. Using Vertex AI and Gemini, the assistant extracts JSON metadata, parses diagrams and flowcharts, and returns cited answers in seconds. The tool logs clinician feedback to BigQuery and stores source documents in Cloud Storage, enabling continuous improvement of documentation and metadata.

🔍 This post introduces the third installment in Google Cloud’s Network Performance Decoded series, summarizing three whitepapers that examine TCP retransmission tuning, the effects of headers and MTU on effective throughput, and techniques to measure packets-per-second with netperf. The guidance highlights practical kernel tuning (for example, rto_min and thin linear timeouts), how protocol and cloud-specific headers reduce payload efficiency, and rigorous netperf methodologies for sizing tests and correcting skew when measuring PPS. While examples reference Google Cloud features such as Protective ReRoute, the recommendations are broadly applicable to cloud deployments seeking improved responsiveness and accurate benchmarking.

🤖 Mr. Cooper partnered with Google Cloud to develop CIERA, a modular agentic AI framework that assembles specialized agents to support mortgage servicing representatives and customers. The design assigns distinct roles — orchestration, task execution, data retrieval, memory, and evaluation — while keeping humans in the loop for verification and personalization. Built on Vertex AI, CIERA aims to reduce research time, lower average handling time, and preserve trust and compliance in regulated workflows.

🔒 Google Cloud presents its certified MSSP ecosystem as a way to modernize security operations by combining partner expertise with Google Cloud Security products. Partners accelerate deployments and migrations, shorten time to value, and augment limited internal teams with specialized talent and AI-enabled tooling such as Google Security Operations and Mandiant. By providing scalable, 24/7 managed detection and response, MSSPs can reduce manual alerts, lower operational costs, and protect workloads across on-premises and multicloud environments.

🚀 Google Cloud highlights how its differentiated AI tech stack is accelerating startup innovation worldwide, with nine of the top ten AI labs, most AI unicorns, and more than 60% of generative AI startups using its platform. Startups are leveraging Vertex AI, TPUs, multimodal models like Veo 3 and Gemini, plus services such as AI Studio and GKE to build agents, generative media, medical tools, and developer platforms. Programs like the Google for Startups Cloud Program provide credits, mentorship, and engineering support to help founders scale.

🔒 A centralized proxy architecture on Google Cloud can secure remote Model Context Protocol (MCP) servers by intercepting tool calls and enforcing consistent policies across deployments. Author Lanre Ogunmola outlines five core MCP risks — unauthorized tool exposure, session hijacking, tool shadowing, token/theft and authentication bypass — and recommends an MCP proxy (Cloud Run, GKE, or Apigee) integrated with Cloud Armor, Secret Manager, and identity services for access control, secret scanning, and monitoring. The post emphasizes layered defenses including Model Armor for prompt/response screening and centralized logging to reduce blind spots and operational overhead.

🧰 MCP Toolbox now includes comprehensive Firestore tools that let AI assistants connect directly to Firestore from environments like Gemini CLI and other MCP-compatible interfaces. Built on the Model Context Protocol, these pre-built tools support document reads, collection queries, targeted updates, and security-rules validation to accelerate debugging, testing, and maintenance for NoSQL applications. Developers can perform complex queries and targeted updates in natural language, validate security rules before deployment, and reduce context switching between consoles and emulators. The release is accompanied by docs, quick start guides, a GitHub repo, and community channels to help teams adopt the features quickly.

📡 Over the past decade, Google Cloud evolved GKE pod networking from basic kubenet and route-based clusters to VPC-native alias IPs and the eBPF-powered Cilium Dataplane V2, improving performance, scalability, and observability. The platform now supports extreme-scale AI workloads with multi-NIC, terabit throughput, and persistent IPs for stateful functions. Looking forward, Google is exploring the Kubernetes Network Driver and the DRANET reference to expose node-level network resources via Dynamic Resource Allocation.

🚀 Google Cloud announced BigQuery performance and usability enhancements to accelerate generative AI inference. Improvements include >100x throughput for first-party text generation and >30x for embeddings, plus support for Vertex AI Provisioned Throughput and dynamic token batching to pack many rows per request. New reliability features—partial-failure mode, adaptive traffic control, and robust retries—prevent individual row failures from failing whole queries and simplify large-scale LLM workflows.