Cloud Computing

Geospatial analytics can transform rich data into actionable insights that drive sustainable business strategy and decision making. At Google Cloud Next ‘25, we announced the preview of Earth Engine in BigQuery, an extension of BigQuery’s current geospatial offering, focused on enabling data analysts to seamlessly join their existing structured data with geospatial datasets derived from […]

Additional contributors include Hossein Sarshar, Ashish Narasimham, and Chenyang Li.   Large Language Models (LLMs) are revolutionizing how we interact with technology, but serving these powerful models efficiently can be a challenge. vLLM has rapidly become the primary choice for serving open source large language models at scale, but using vLLM is not a silver

Written by: Patrick Whitsell In March 2025, Google Threat Intelligence Group (GTIG) identified a complex, multifaceted campaign attributed to the PRC-nexus threat actor UNC6384. The campaign targeted diplomats in Southeast Asia and other entities globally. GTIG assesses this was likely in support of cyber espionage operations aligned with the strategic interests of the People’s Republic

Debugging in a complex, distributed cloud environment can feel like searching for a needle in a haystack. The sheer volume of data, intertwined dependencies, and ephemeral issues make traditional troubleshooting methods time-consuming and often reactive. Just as modern software development demands more context for effective debugging, so too does cloud operations. Gemini Cloud Assist, a

Organizations face diverse challenges when it comes to managing encryption keys. While some scenarios demand strict separation, there are compelling use cases where a centralized approach can streamline operations and reduce complexity. In this post, our focus is on a software-as-a-service (SaaS) provider scenario, but the principles we discuss can be adopted by large organization

As data platforms evolve and businesses diversify their cloud ecosystems, the need to migrate SQL workloads between engines is becoming increasingly common. Recently, I had the opportunity to work on translating a set of Databricks SQL queries to BigQuery SQL — a task that is deceptively complex due to differences in syntax, functions, and execution

A little over a year ago, we published a list of generative AI use cases that has since grown to include more than 600 examples of how organizations are putting AI to work. Yet for many developers and business leaders, inspiration has given way to a more practical question: where do I start?  To help,