All news with #google cloud tag

🔍 Curve partnered with Google Cloud to adopt BigQuery Graph, moving beyond relational joins to perform multi-hop network analysis across billions of connections. By modeling users and shared identifiers as a property graph, they can traverse massive datasets with GQL, combine graph traversals with standard SQL and ML workflows, and avoid costly data migrations. This integration has improved detection, operational efficiency, and enabled plans for real-time signals and visualization.

🔒 Google Cloud describes how it embeds modular AI agents across the software development lifecycle to create autonomous security guardrails. The approach includes centralized code analysis via the Mantis framework, multi-agent fuzz testing with self-reflection, and an autonomous patching pipeline that validates fixes before human review. Continuous reflection and a programmable posture management system help convert lessons into reusable skills that improve remediation speed and reduce false positives.

🔒 Google Cloud announces new VPC Service Controls features to secure agentic AI deployments by enforcing network-level perimeters and integrating agent identities. These updates let administrators add agent principals and principalSets to ingress/egress rules, apply conditional rules based on MCP attributes like mcp.toolName and mcp.method, and automatically protect the Gemini Enterprise Agent Platform from public internet access. The enhancements are designed to complement IAM and resource policies to prevent exfiltration and tool misuse in production agent fleets.

📣 Google Cloud now lets you create alerts in Observability Analytics using SQL to query logs and traces. This preview feature runs scheduled SQL queries via BigQuery on telemetry linked datasets and supports row count and boolean conditions. When conditions are met, Cloud Monitoring opens incidents and notifies configured channels. Note that BigQuery execution costs apply under your billing model.

🔒 Google Cloud announces general availability of cross-region backups for its Backup and DR Service. This release decouples backup destinations from source regions, enabling backups to be stored in distinct geographic regions to improve resilience and meet data residency requirements. The capability is available now for Compute Engine instances, Disks, and Filestore, with Cloud SQL and AlloyDB support coming soon.

🔒 Google Cloud announces expanded Confidential Computing capabilities to protect data in use for AI workloads. The update includes Confidential G4 VMs with NVIDIA RTX PRO 6000 Blackwell GPUs, open-source Prompt Encryption SDKs, Intel TDX on C4 machines, and broader Confidential Space enhancements. These innovations aim to provide verifiable attestation, end-to-end encrypted inference, and support for multi-party collaboration while preserving performance and scalability.

🛠️ Google Cloud announced enhancements to its Observability suite, rebranding Log Analytics as Observability Analytics and bringing trace data and the Observability API to general availability. The update unifies logs and traces, enables SQL queries across telemetry, and allows in-place analysis without duplicating data. Use cases include diagnosing AI agent tool failures and correlating latency with customer impact. Users can link observability buckets to BigQuery and run cross-dataset analytics directly in the Cloud console.

🔒 Unit 42 researchers describe a bucket hijacking technique that exploits globally unique storage bucket names across major cloud providers. By deleting a target bucket and recreating it under an attacker-controlled account with the same name, data streams (logs, Pub/Sub, replication, transfer jobs, etc.) can be silently rerouted to an adversary. The team validated the attack across Google Cloud, AWS and demonstrated cross-subscription scenarios in Azure, and has shared findings with the affected vendors.

🧩 Google Cloud's Starter Tier for Google AI Studio provisions a managed, limited stack (Cloud Run, Firestore, Cloud SQL for PostgreSQL, Firebase Auth) so individual Google Accounts can publish prototypes without a billing account. The environment is fully managed by Google, with region, APIs, and security policies preselected. It supports two active apps, a simplified console, and automatic agent-driven provisioning and code generation. Quotas, locked APIs, ephemeral storage, and upgrade paths to paid projects are explained.

🔍 Cloud Network Insights is now generally available as a Google Cloud-native solution, delivered in partnership with Broadcom AppNeta, to provide end-to-end visibility across multi-cloud and hybrid networks. It uses lightweight Monitoring Points and active synthetic probes to measure RTT, packet loss, jitter, and application-level metrics like DNS and page-load times. The service integrates with Cloud Monitoring, Cloud Logging, and supports OpenTelemetry, enabling proactive alerting, SLA validation, and rapid root-cause analysis.

🛠️ Siemens and Google Cloud built Knowledge Fabric, an AI system using knowledge graphs on Spanner Graph, the Google Agent Development Kit, and LLM APIs to modernize large industrial codebases. The platform models code relationships with GQL, uses embeddings and ANN for semantic search, and combines full-text search to deliver precise impact analysis. By "slicing the elephant," agentic workflows break large refactors into smaller tasks with human oversight, reducing engineering effort and preserving system integrity.

🧭 This post describes how Yahoo and Google Cloud built Seller Agent, an agentic media-buying platform that collapses multi-week manual workflows into governed campaigns executed in seconds. The architecture uses a dual-graph approach — a knowledge graph for deterministic business logic and a context graph for auditable decision traces — combined with Google Cloud services like Spanner Graph, BigQuery Graph, and Gemini. The design emphasizes explainability, regulator-grade governance, and closed-loop learning to ensure autonomous actions remain transparent and accountable.

🛡️ In his first Cloud CISO Perspectives, Chris Betz outlines four lessons guiding Google Cloud’s AI Threat Defense: Prepare, Scan and Prioritize, Remediate, and Monitor. He highlights how AI accelerates vulnerability discovery and defense, the importance of operational frameworks and harnesses, and the need for centralized tracking, risk-based patching, and continuous AI-driven monitoring. The guidance emphasizes reducing attack surface, close engineering collaboration, and building resilient systems.

📘 Today Google Cloud introduces the Open Knowledge Format (OKF), an open, vendor-neutral specification that formalizes the LLM-wiki pattern into a portable directory of markdown files with YAML frontmatter. OKF v0.1 defines a small set of conventions so different producers’ wikis can be consumed by agents without translation. The spec is intentionally minimal — one required type field per concept — and is accompanied by reference producer and consumer implementations and sample bundles.

🔒 Google Cloud announces collaboration with Apple to support Apple’s expanded Private Cloud Compute (PCC) systems on Google Cloud, built with Intel and NVIDIA. The effort leverages Google Cloud’s Titanium security architecture and Confidential Computing portfolio, including hardware Trusted Execution Environments, to protect data at rest, in transit, and in use. This layered approach aims to deliver verifiable integrity, no privileged runtime access, and enforceable privacy protections for sensitive AI workloads.

⚡ Google Cloud has announced general availability of Lightning Engine for Managed Service for Apache Spark, available in both serverless and managed cluster modes. Built on Gluten and Velox with Google-engineered enhancements, the engine compiles Spark physical plans into native C++ to accelerate vectorized operations, window functions, and sorting. It also optimizes connectors for Cloud Storage and BigQuery and adds cost-based optimizations like hash table caching, aggregation pushdown, and adaptive shuffle partitioning.

🟢 Claude Fable 5, Anthropic’s latest frontier model, is now generally available on Google Cloud. The model is designed for complex, multi-step reasoning and supports demanding use cases like advanced software development, long-horizon agents, and deep multimodal document analysis. Google Cloud highlights strong safeguards to make the model suitable for general use and positions it alongside other Anthropic offerings on the Agent Platform.

🔍 Storage Insights datasets now include activity insights that provide near-real-time visibility into object and bucket operations across your Google Cloud Storage estate. These BigQuery-linked views expose object-level writes, updates, deletes and errors, bucket-level aggregates and regional traffic patterns to support cost optimization and faster troubleshooting. The feature is generally available and customizable by org, folder, project, or specific buckets, enabling queries, Looker visualizations, and integration with other Storage Intelligence capabilities.

🔒 The article argues that sovereignty in Europe demands verifiable control, not just contractual promises. It emphasizes integrity, accountability, and transparency, and describes the Sovereign Cortex with T Security — a partnership with Deutsche Telekom and Google Cloud — as a practical response. The post underscores placing meaningful control with trusted local partners and treating sovereignty as a design principle.

🔍 Alcidion migrated its Miya Precision platform from Microsoft SQL Server to Google Cloud's AlloyDB for PostgreSQL to improve stability, performance, and operational overhead. The move used Database Migration Service and custom synchronization tools to achieve a rapid cutover, reducing transition time to about 15 minutes. The new architecture enabled dramatic speedups in JSON processing and reduced administrative burden for SREs.