All news with #google cloud tag

GKE Autopilot Features Now Available to Qualified Clusters

🚀 Google Cloud has extended core Autopilot capabilities to qualified Standard GKE clusters, enabling access to the new container-optimized compute platform via built-in compute classes. Available initially to clusters in the Rapid release channel running 1.33.1-gke.1107000 or later, these features include the autopilot and autopilot-spot compute classes and a provisioning mode that supports gradual adoption. Benefits include rapid horizontal and vertical scaling, pay-for-request billing, efficient bin-packing, and support for GPUs and TPUs for AI workloads.

npm Supply-Chain Worm 'Shai-Hulud' Compromises Packages

🛡️ 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.

Protect AI Development Using Falcon Cloud Security

🔒 Falcon Cloud Security provides end-to-end protection for AI development pipelines by embedding AI detection into CI/CD workflows, scanning container images, and surfacing AI-related packages and CVEs in real time. It extends visibility to cloud model services — including AWS SageMaker and Bedrock, Azure AI, and Google Vertex AI — revealing model provenance, dependencies, and API usage. Runtime inventory ties build-time detections to live containers so teams can prioritize fixes, govern models, and maintain delivery velocity without compromising security.

Network Performance Whitepapers: Retransmits, MTU, and PPS

🔍 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.

Partnering with Google Cloud MSSPs to Modernize SecOps

🔒 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's Differentiated AI Stack Fuels Startups

🚀 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.

Securing Remote MCP Servers on Google Cloud Platform

🔒 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.

BigQuery scalability and reliability upgrades for Gen AI

🚀 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.

California Modernizes Public Services with Google Cloud

🚀 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.

Benchmarking Google Cloud C3 Machine Types for Trading

🔍 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.

Gemini and Open-Source Text Embeddings Now in BigQuery ML

🚀 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.

Google Cloud and SAP: Unified Data, AI Agents, and HANA

🚀 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.

New Practical Guide to Data Science with Google Cloud

📘 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.

OpenTelemetry (OTLP) Support Added to Cloud Trace UI

🚀 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.

Rent the Runway Boosts Developer Velocity with Cloud SQL

🚀 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.

Three-Part Framework to Measure AI Value and Impact

🚀 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 Professional SecOps Engineer Certification

🔐 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.

Resilient Networking with Google Cloud Network Connectivity

🛡️ 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.

GKE Inference Gateway and Quickstart Achieve GA Status

🚀 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.

Gemini CLI Extensions: Security and Cloud Run Tools

🚀 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.