All news with #google cloud tag

🚀 California is partnering with Google Cloud to modernize state and local services by applying AI, security, and infrastructure solutions. Agencies such as Covered California use Document AI, Assured Workloads, and AI-driven security to speed eligibility decisions and protect sensitive data. Universities including UCR and Caltech are using Vertex AI and AI-optimized HPC for research acceleration. Workspace, Gemini, and Agentspace are cited as productivity and information-management enablers.

🔍 Google Cloud and consultancy 28Stone published benchmarks showing the C3 machine series delivers low-latency, low-jitter performance suited to electronic trading. Tests using DPDK and replayed CME Group equity pcaps reported decision latencies as low as 1.5 µs (P50) and 3.5 µs (P99) and demonstrated consistent profiles at up to 100× data rates. The results highlight sub‑50 µs end-to-end round-trip P99 performance, high throughput with up to 200 Gbps per VM networking, and network innovations such as Titanium offload and Cloud WAN layer‑2 connectivity.

🪱 Researchers have identified a self-propagating npm worm dubbed Shai-Hulud that injects a 3MB+ JavaScript bundle into packages published from compromised developer accounts. A postinstall action executes the bundle to harvest npm, GitHub, AWS and GCP tokens and to run TruffleHog for broader secret discovery. The worm creates public GitHub repositories to dump secrets, pushes malicious Actions to exfiltrate tokens, and has exposed at least 700 repositories; vendors urge rotation of affected tokens.

🛡️ Researchers disclosed a campaign that trojanized more than 40 npm packages, including the popular tinycolor, embedding self-replicating credential-stealing code. The malware harvested AWS, GCP and Azure credentials, used TruffleHog for secrets discovery, and established persistence via GitHub Actions backdoors. Affected packages were removed, but developers are urged to remove compromised versions, rebuild from clean caches, and rotate any exposed credentials.

🛡️ DNS Armor is a cloud-native DNS security service from Google Cloud, built in partnership with Infoblox, that provides preemptive detection and mitigation of DNS-based threats for Google Cloud workloads. By intercepting internet-bound DNS queries and inspecting them in real time with Infoblox Threat Defense, it identifies malicious and high-risk domains, C2 activity, DNS tunneling, DGA patterns and evasive techniques such as fast-flux, and forwards detailed logs to Cloud Logging, Security Command Center, or SIEMs. Delivered as a turnkey managed service with no VMs and no impact to Cloud DNS, DNS Armor is enabled at the project level for granular protection and is available now in preview.

🧭 Google Cloud has expanded the Data Science Agent in Colab Enterprise notebooks to support BigQuery ML, BigQuery DataFrames and Spark, enabling large-scale data transformation, model training, and inference directly on BigQuery or via Serverless for Apache Spark. The agent can now auto-retrieve BigQuery table metadata and lets you add tables via an @ mention from your current project to provide prompt context. To invoke frameworks, include keywords such as BigQuery ML, BigFrames, or PySpark; sample prompts are provided to guide forecasting, supervised learning, and dimensionality reduction workflows. Notable limitations: generated PySpark targets Spark 4.0 and @ mentions only search the current project; BigQuery improvements are available now in BigQuery notebooks and coming soon to Vertex AI.

🚀 Google expanded BigQuery ML to generate embeddings from Gemini and over 13,000 open-source text-embedding models via Hugging Face, all callable with simple SQL. The post summarizes model tiers to help teams trade off quality, cost, and scalability, and introduces Gemini's Tokens Per Minute (TPM) quota for throughput control. It shows a practical workflow to deploy OSS models to Vertex AI endpoints, run ML.GENERATE_EMBEDDING for batch jobs, and undeploy to minimize idle costs, plus a Colab tutorial and cost/scale guidance.

🔍 ODOT teamed with Google Cloud and North Highland to centralize decades of bridge inspection, location, and maintenance data into BigQuery and govern it with Dataplex, creating a single trusted source for analysis. Non-technical and technical staff can query complex datasets conversationally through Gemini in Looker, while BigQuery ML powers predictive models to flag at-risk bridges ahead of failures. Secure sharing via Analytics Hub and unified governance enables better resource allocation, improved safety, and faster, data-driven decisions across the agency.

🚀 Google Cloud and SAP announced tighter integration to unify enterprise data and accelerate intelligent automation. SAP Business Data Cloud now connects to BigQuery via Datasphere, enabling bidirectional replication and AI-ready analytics. Procurement is simplified on the Google Cloud Marketplace with SAP BTP. New agent tooling—Agentspace, the Agent Development Kit, A2A and MCP standards—and expanded M4 memory-optimized VMs certified for SAP HANA aim to speed deployments, improve data consistency, and enable autonomous process automation.

📘 Google Cloud has published a new ebook, A Practical Guide to Data Science with Google Cloud, aimed at practitioners adopting an AI-first approach across BigQuery, Vertex AI, and Serverless for Apache Spark. The guide emphasizes unified, streamlined workflows enabled by a central notebook experience that blends SQL, Python, and Spark and includes assistive features in Colab Enterprise to generate multi-step plans and code. It explains how a unified data foundation lets teams manage structured and unstructured data together and use familiar SQL to process documents and images. The ebook also offers real-world use cases with linked notebooks so practitioners can run the examples and accelerate delivery.

🚀 AlloyDB on Axion-powered C4A virtual machines is now generally available. AlloyDB on C4A offers substantial efficiency gains—up to 45% better price-performance versus N‑series VMs and up to 2× higher throughput versus Amazon Aurora on Graviton4—targeting transactional and data‑intensive workloads. C4A supports shapes from 1 to 72 vCPUs (including a new 48‑vCPU option and a cost‑effective 1‑vCPU/8GB shape for dev/sandbox). Deploy or upgrade C4A instances via the AlloyDB console in supported regions.

🚀 Rent the Runway migrated from a complex, self-managed MySQL environment to Cloud SQL, gaining managed backups, built-in observability, and simplified disaster recovery. The move removed a third-party 24/7 MySQL support vendor and cut more than $180,000 in annual operational costs. Engineers now work in IAM-controlled instances with query insights, enabling safer schema changes, CI/CD for database updates, and faster, more reliable deployments.

🚀 Cloud Trace now accepts traces via OTLP through telemetry.googleapis.com, enabling vendor-agnostic ingestion and preserving the OpenTelemetry data model. Using OTLP reduces client-side exporter complexity, improves telemetry integrity, and enables easier routing to other backends. The Trace Explorer leverages OpenTelemetry semantic conventions for improved filtering and diagnostics. Google recommends telemetry.googleapis.com as the best practice for new and high-volume trace pipelines and provides a migration guide to help users transition.

🚀 This Cloud blog post from Google Cloud Consulting presents a practical three-part framework to quantify the business value of AI initiatives. It asks teams to define success across four value-driver categories, transparently specify Total Cost of Ownership (TCO), and state an explicit ROI. A worked example — an e-commerce customer-service chatbot — shows quantified monthly benefits versus estimated managed-service costs, demonstrating rapid payback and sustained positive cash flow.

🛡️ Google Cloud's Network Connectivity Center provides a centralized, hub-and-spoke model to simplify and scale enterprise connectivity across VPCs, on-premises data centers, and other clouds. Architected with distinct management, control, and data planes, it employs a fail-static design so existing traffic continues during control-plane issues. The service supports up to 250 VPC spokes per hub and reduces operational overhead by automating full-mesh connectivity.

🔐 Google Cloud has launched the Professional Security Operations Engineer (PSOE) certification to validate hands‑on skills for detecting, investigating, and responding to cloud threats. The exam focuses on practical use of Google Security Operations, Security Command Center, and threat intelligence across domains such as detection engineering, incident response, and threat hunting. Google recommends candidates have ~three years in security with at least one year of Google Cloud security tooling experience, and provides online training, hands‑on labs, and an official exam guide to prepare.

🚀 GKE Inference Gateway and GKE Inference Quickstart are now generally available, bringing production-ready inferencing features built on AI Hypercomputer. New capabilities include prefix-aware load balancing, disaggregated serving, vLLM support on TPUs and Ironwood TPUs, and model streaming with Anywhere Cache to cut model load times. These features target faster time-to-first-token and time-per-output-token, higher throughput, and lower inference costs, while Quickstart offers data-driven accelerator and configuration recommendations.

⚡ This post announces a reproducible recipe to deploy NVIDIA Dynamo for disaggregated LLM inference on Google Cloud’s AI Hypercomputer using Google Kubernetes Engine, vLLM, and A3 Ultra (H200) GPUs. The recipe separates prefill and decode phases across dedicated GPU pools to reduce contention and lower latency. It includes single-node and multi-node examples and step-by-step deployment actions. The repository provides configuration guidance and future plans for broader GPU and engine support.

🛒 Google Cloud announced general availability of the Conversational Commerce agent on Vertex AI, a shopping-focused conversational assistant designed to guide customers from intent to purchase. The agent uses Gemini to interpret complex queries, supports context retention across sessions and devices, and offers administrative controls to boost, bury, or restrict products. Albertsons Cos. reports increased basket size in early use. Onboarding is presented as quick with minimal development effort via the Vertex AI console.

🚀 Google is previewing two Gemini CLI extensions that bring security analysis and Cloud Run deployment directly into your terminal. The security extension introduces /security:analyze to scan local git diffs for issues such as hardcoded secrets, injection flaws, broken access control, and insecure data handling, and returns clear remediation guidance or optional fixes. The Cloud Run extension adds /deploy, a one-command flow to build, containerize, push, and configure services on Cloud Run, returning a public URL and supporting terminal, VS Code agent mode, and Cloud Shell.