All news with #google cloud tag

🔍 This article demonstrates a hybrid streaming pattern that pairs lightweight, CPU-based inference with downstream generative AI agents using Google Dataflow and the Agent Development Kit (ADK). It outlines an Apache Beam pipeline that filters routine events locally and routes only complex cases to a Gemini-backed agent for multi-step remediation, reducing API costs, latency, and quota exhaustion. The approach preserves a static DAG while enabling dynamic runtime branching for targeted automation.

🤖 Deutsche Bank partnered with Google Cloud to build an agentic AI-driven resilience platform that modernizes regulatory tabletop exercises and incident analysis. The platform ingests architecture, logs, data flows, and telemetry to generate context-aware scenarios, audit-ready evidence, and structured session records. Using Gemini Enterprise Agent Platform, LangGraph, and Google ADK, the bank achieves both deterministic, traceable execution and adaptive investigation. This approach supports continuous, regulator-aligned resilience across complex, distributed systems.

🔒 Google Cloud published a staged post-quantum migration roadmap on August 12, splitting work into three risk domains from its quantum threat model. The provider targets mitigating store-now-decrypt-later (SNDL) risks by end of 2027, with signature hardening and key management agility running to end of 2028. Several services already support hybrid NIST-standardized ML-KEM and related primitives, while others (Cloud VPN, Private CA, Cloud HSM) phase in through 2028. Google warns hardware replacement cycles may extend some transitions beyond 2029.

🚀 Gemini in Google Cloud's Database Migration Service streamlines conversion of stored procedures, triggers, and functions from proprietary dialects like PL/SQL and T-SQL into PostgreSQL PL/pgSQL. The service analyzes full schema context, provides side-by-side diffs and inline explanations, and enforces IAM-bound security. Teams can validate, edit, and deploy converted code within a single console to shorten migration timelines.

🔒 Google Cloud publishes an updated roadmap to migrate its infrastructure and services to post-quantum cryptography by 2029, addressing risks like Store Now, Decrypt Later and signature forgery. The plan prioritizes API endpoints, load balancers, Cloud KMS, and key management while collaborating on standards such as NIST and IETF. Google outlines domain-specific timelines through 2027–2028 and emphasizes shared responsibilities with customers for operational readiness.

📱 Google Cloud announced the public preview of Developer Device Platform (DDP), a fully managed service offering on-demand access to real physical devices and high-concurrency virtual emulators. DDP provides interactive debugging via Device Streaming and parallel CI/CD testing via Device Run, enabling faster iteration, smarter sharding, and auto-retries. The platform supports integration with coding agents and will integrate with Android Studio and CLI, charging users on a pay-per-minute public preview model.

🔍 Malachyte applies attention-based neural networks and LLM-inspired sequence modeling to address the retail "cold start" problem, updating user vectors in real time to personalize search and product pages. By streaming every interaction through Managed Service for Apache Kafka into Bigtable and combining multimodal embeddings, the platform refines predictions and privacy-friendly personalization within 100 milliseconds. Built on Google Cloud's AI stack, the solution leverages GKE, GCE, and Cloud Pub/Sub to enable continuous learning across retailers.

🔒 Google Cloud outlines its proactive, shared-fate approach to detect and contain emerging threats across AI workloads, cryptomining, credential exposure, supply chain attacks, and account takeover. The post describes detection signals, tailored containment actions like granular throttling and localized identity isolation, and escalation paths including targeted suspensions. It highlights integrations such as GitHub Secret Scanning and details observability tools like Cloud Abuse Event Logging, Cloud Audit Logging, and billing alerts.

🔒 Enterprises with strict compliance and sovereignty needs often keep data on-premises, risking missed AI advances. Recent research of over 1,400 IT leaders found 48% prioritize infrastructure with data residency and local security controls, and 52% now use hybrid cloud to combine public cloud power with local data control. Google Distributed Cloud (GDC) delivers on-premises AI, optimized infrastructure, and a choice of Gemini or open models to enable secure, sovereign AI.

🔒 Google Cloud and MLCommons’ MedPerf use Confidential Computing to benchmark medical AI on real patient data while preserving privacy. The collaboration runs evaluations inside hardware-isolated Trusted Execution Environments, extending protection across CPUs and GPUs with A3 VMs and NVIDIA H100 GPUs. This approach enables federated evaluation for initiatives like Federated Tumor Segmentation, revealing site-specific performance gaps and improving trust in clinical AI.

🔍 Mirendil will leverage Google Cloud’s AI Hypercomputer, combining TPU accelerators and NVIDIA full-stack AI infrastructure to support model pre-training and post-training workloads. Google Cloud partnered closely with Mirendil on design and deployment across compute, storage, networking, and control planes. Managed training clusters run in Gemini Enterprise Agent Platform, and Mirendil is already live with TPU v5P chips while NVIDIA systems come online soon.

🚀 UiPath re-architected its infrastructure to support agentic AI and high-scale intelligent document processing by moving from isolated clusters to a shared Google Cloud GPU fleet. The company balances A3 (NVIDIA H100) instances for training with G4 (NVIDIA RTX Pro 6000) instances for inference, using Google Cloud AI Hypercomputer and Dynamic Workload Scheduler to secure predictable capacity. This shared-fleet approach maximizes utilization, reduces costs, and lets engineering teams focus on model performance rather than infrastructure.

🚀 Filestore, Google Cloud’s first-party NFS file service, now runs on Colossus, Google’s distributed storage system, to deliver greater scalability, flexibility, and operational efficiency. The update decouples capacity from performance so IOPS can be provisioned independently, and offers deep GKE integration including CSI driver support and multishares for smaller persistent volumes. Backed by Colossus, Filestore targets high-concurrency AI and agentic workflows with NFS-based shared workspaces, improved failure recovery, and integrated security via IAM, UIDs/GIDs, and IP ACLs.

🧩 Deutsche Bank adopted Google Cloud's Apigee to transform monolithic systems into a governed, scalable API ecosystem. The platform centralizes documentation, security policies, and governance while enabling discoverability and reuse across teams. Apigee enforces least-privilege access, rate limiting, and observability, and supports resilience, auto-scaling, and caching for high performance. This API-first foundation positions the bank for AI-ready, low-latency services and emerging standards.

🔁 This article explains how Google Cloud's Database Migration Service (DMS) automates translating SQL Server stored procedures that return multiple result sets into PostgreSQL equivalents. It outlines the decision matrix that maps simple single-result procedures to PROCEDURE objects and complex multi-result or mixed-return routines to FUNCTIONs returning SETOF refcursor, and describes the testing and application integration changes required.

🤖 Google Cloud announced two AI-powered database agents — the Database Onboarding Agent for Day 0 setup and the Database Observability Agent for Day 1/2 monitoring and remediation — introduced as part of the Agentic Data Cloud at Google Cloud Next ‘26. These always-on agents integrate with Chat, CLI, the Cloud console, MCP servers, and IDEs to automate provisioning, configuration, telemetry correlation, root-cause analysis, and validated remediations. The Observability Agent leverages Gemini and multiple telemetry sources to surface fleet-level insights, in-product investigations, and actionable fixes, while the Onboarding Agent recommends appropriate database types and configurations based on application requirements. Supported services include AlloyDB, Bigtable, Cloud SQL, Firestore, Memorystore, and Spanner, and capabilities are available via Gemini Cloud Assist and select previews.

🔍 Google Cloud outlines an AI-accelerated, iterative approach to mainframe modernization that avoids risky "big bang" migrations. The strategy combines Gemini-based code reasoning with mainframe-specific tools across four pillars: assessment, modernization, de-risking, and data migration. Key capabilities include the Mainframe Assessment Tool for dependency mapping and business rule extraction, agentic modernization workflows for rewrite or deterministic modernization, Dual Run for live validation, and a Mainframe Connector for data migration.

🔍 Google Cloud announces general availability of Cortex Framework v7, designed to convert SAP transactional data into AI-ready, semantically rich data products deployed in BigQuery and registered in Knowledge Catalog. The release introduces purpose-built accelerators for SAP ERP and SAP Business Data Cloud, modular Dataform-powered deployments, and incremental, cost‑efficient processing to scale without extra infrastructure. New agent skills include an agentic data product builder to automate custom data product creation and preserve separation between vendor-delivered content and customer customizations.

🧭 Data Commons on Spanner Graph general availability and a preview of the Data Commons Platform simplify linking private enterprise data with Google's extensive public knowledge graphs. The platform consolidates standardized public datasets from over 100 providers into a unified graph with >400 billion observations and leverages Spanner Graph for native GQL support, incremental updates, and consistent snapshots. Organizations can deploy private instances to federate private and public knowledge graphs while retaining data isolation and enabling natural language query workflows.

🔔 Google Cloud summarizes recent AI infrastructure launches, enhancements, and resources across compute, storage, networking, orchestration, and developer tooling. Highlights include GA releases for Managed Lustre and C4N VMs, scaling improvements for GKE Dataplane V2, new cooperative time-slicing for llm-d, and open-sourced AI supply-chain tooling in k8s-aibom. The post also links to technical blueprints, how-to guides, benchmarks, and customer stories illustrating performance and optimization techniques.