Cloud Computing

Cloud CISO Perspectives: New Threat Horizons details evolving risks — and defenses

Welcome to the first Cloud CISO Perspectives for August 2025. Today, our Office of the CISO’s Bob Mechler and Anton Chuvakin dive into the key trends and evolving threats that we tracked in our just-published Cloud Threat Horizons report. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to the Google […]

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How Keeta processes 11 million financial transactions per second with Spanner

Keeta Network is a layer‑1 blockchain that unifies transactions across different blockchains and payment systems, eliminating the need for costly intermediaries, reducing fees, and enabling near‑instant settlements. By facilitating cross‑chain transactions and interoperability with existing payment systems, Keeta bridges the gap between cryptocurrencies and fiat, enabling a secure, efficient, and compliant global financial ecosystem. Founded

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From legacy to cloud: How Deutsche Telekom went from PySpark to BigQuery DataFrames

In today’s hyper-competitive telecommunications landscape, understanding and maximizing the Customer Lifetime Value (CLV) metric isn’t just a nice-to-have, it’s a strategic imperative. For Deutsche Telekom, accurate CLV calculations are the bedrock of informed decisions, driving crucial initiatives in customer acquisition, retention, and targeted marketing campaigns. The ability to predict and influence long-term customer relationships directly

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How Karrot built a feature platform on AWS, Part 1: Motivation and feature serving

This post is co-written with Hyeonho Kim, Jinhyeong Seo and Minjae Kwon from Karrot. Karrot is Korea’s leading local community and a service centered on all possible connections in the neighborhood. Beyond simple flea markets, it strengthens connections between neighbors, local stores, and public institutions, and creates a warm and active neighborhood as its core

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How Karrot built a feature platform on AWS, Part 2: Feature ingestion

This post is co-written with Hyeonho Kim, Jinhyeong Seo and Minjae Kwon from Karrot. In Part 1 of this series, we discussed how Karrot developed a new feature platform, which consists of three main components: feature serving, a stream ingestion pipeline, and a batch ingestion pipeline. We discussed their requirements, the solution architecture, and feature

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Deploy LLMs on Amazon EKS using vLLM Deep Learning Containers

Organizations face significant challenges when deploying large language models (LLMs) efficiently at scale. Key challenges include optimizing GPU resource utilization, managing network infrastructure, and providing efficient access to model weights.When running distributed inference workloads, organizations often encounter complexity in orchestrating model operations across multiple nodes. Common challenges include effectively distributing model components across available GPUs,

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Uber’s modern edge: A new approach to network performance and efficiency

Picture this: You’re ordering an Uber in Lisbon, but your request takes a scenic tour through Madrid, London, and Virginia before confirming your ride. That was the case for millions of users until Uber and Google Cloud set out on an even bigger journey: redesigning how global edge networks should work. Operating across six continents,

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Designing a multi-tenant GKE platform for Yahoo Mail’s migration journey

Yahoo is in the midst of a multi-year journey to migrate its renowned Yahoo Mail application onto Google Cloud. With more than 100 services and middleware components in the application, Yahoo Mail is primarily taking a lift-and-shift approach for its on-premises infrastructure, and strategically transforming and replatforming key components and middleware to leverage cloud-native capabilities.

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Start and scale your apps faster with improved container image streaming in GKE

In today’s fast-paced cloud-native world, the speed at which your applications can start and scale is paramount. Faster pod startup times mean quicker responses to user demand, more efficient resource utilization, and a more agile development and deployment lifecycle overall. We’re continuously working to enhance the performance of Google Kubernetes Engine (GKE) to help you

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