Cloud Computing

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 […]

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,

With Windows 10 end of life on the horizon, many businesses are getting more familiar with Windows 11. While your organization might be migrating, or perhaps has already migrated, to the latest Windows OS, many of your users might still prefer the familiarity and ease of Chrome as they spend more time working on the

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,

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.

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

What guides your approach to software development? In our roles at Google, we’re constantly working to build better software, faster. Within Google, our Developer Platform team and Google Cloud have a strategic partnership and a shared strategy: together, we take our internal capabilities and engineering tools and package them up for Google Cloud customers. At

The mission of the Google Cloud Developer Experience team is simple: to help developers get from learning to launching as quickly and effectively as possible. Two of our primary tools for this are the robust hands-on documentation and the ready-to-use code samples embedded directly within it, which developers rely on every day. As Google Cloud’s