Cloud Computing

How AlloyDB ScaNN scales vector search to 10 billion vectors

To satisfy the demands of enterprise-grade agentic AI applications, underlying vector databases often struggle to scale effectively as modern use cases can scale to billions of vectors. As a fully managed PostgreSQL-compatible database service, AlloyDB is engineered to handle demanding enterprise workloads. Combining Google’s infrastructure with the reliability of commercial databases, it delivers high availability, […]

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Announcing quantum-safe key import in Cloud KMS

As enterprises increasingly adopt multicloud architectures, bring your own key (BYOK) has become a fundamental pillar for maintaining data sovereignty and helping protect critical cloud workloads. At the same time, quantum computing has rapidly advanced, and security teams need to re-evaluate how they securely transfer encryption keys across networks. Following our previous announcements of quantum-safe

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Google is a Leader in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms

We are thrilled to announce that Google has been recognized as a Leader for the third year in a row in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms (CNAP). We believe this placement in the Leaders quadrant validates our commitment to providing an accessible, developer-centric platform that accelerates onboarding and supports rapid prototyping

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10 questions every startup should answer before moving to production with their AI prototype

It’s never been easier to start an AI-powered startup on Google Cloud.  You grab an API key from Google AI Studio at breakfast, paste it into Antigravity, and by lunch you’ll have a nascent prototype of your product. But it’s not all one straight line to progress. It’s common to bump into these three challenges

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Going with the Flow(s): Distinct Clusters Target Individuals of Interest to Russia

Written by: Gabby Roncone, Wesley Shields Overview  Google Threat Intelligence Group (GTIG) is tracking three distinct suspected Russian cyber espionage threat clusters abusing legitimate authentication flows to target individuals working in academia, aerospace and defense, governments and think tanks across Europe, as well as academia and think tanks within the United States. Examples of these

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From PHP to team lead of agents: rethinking judgment, review, and data with Google’s Andi Gutmans (Part 1)

Andi Gutmans, head of Agentic Data Cloud at Google and co-creator of PHP, joins Leaders of Code to talk about why agentic development feels less like a break from the past and more like the next chapter of the same story. This is part one of a two-part conversation.

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How AgentFlo built AI sales agents with Amazon Bedrock AgentCore – Part 1

In this post, you learn how AgentFlo built intelligent sales agents that convert conversations into completed purchases. We show you how AgentFlo improved revenue performance in early deployments using Amazon Bedrock AgentCore and the Strands Agents SDK. AgentFlo, the agentic commerce service by Salesflo, helps merchants deploy always-on AI sales, support, and ordering agents across

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Serverless Apache Spark on Google Cloud: Architecture Choices & AI Troubleshooting

In modern enterprise data engineering, Apache Spark remains a cornerstone framework for processing massive datasets at scale. However, managing infrastructure such as provisioning clusters, tuning YARN configurations, and avoiding costs for idle hardware often detracts from what matters most: building resilient data pipelines. Google Cloud addresses this operational overhead via its Managed Service for Apache

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How to modernize Apache Hive using Google Cloud’s Lakehouse runtime catalog

For over a decade, the Apache Hive Metastore (HMS) has served as the de facto metadata authority for big data analytics. Whether it was deployed on Hadoop clusters, self-managed Compute Engine VMs backed by MySQL or PostgreSQL, HMS provided the central schema registry that let Apache Spark, Presto, and Hive query raw .parquet and .orc

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How Clario technology detects PHI/PII in DICOM images using Amazon Bedrock

Clario, part of Thermo Fisher Scientific, uses Amazon Bedrock to automate PHI (Protected Health Information) and PII (Personally Identifiable Information) detection across thousands of DICOM (Digital Imaging and Communications in Medicine) image slices in clinical trials. Each image slice may carry PII or PHI hidden in metadata tags, in custom vendor fields, or burned directly

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