Cloud Computing

As ​​developers build AI agents with more sophisticated reasoning systems, they require higher-quality fuel–in the form of enterprise data and specialized tools–to drive real business value. To get the most out of that octane-rich mix, we offer Google-managed model context protocol (MCP) servers:  an engine purpose-built for AI agents to interact securely with Google and […]

Every dollar that you spend on model inference buys you a position on a graph of latency and throughput. On this plot is a curve of optimal configurations, where you’ve squeezed the maximum possible performance from your hardware. That curve, borrowed from portfolio theory in finance, is the efficient frontier. With the assumption that you

If you’re architecting cloud systems for AI development on AWS, you’ve likely discovered that traditional architectures create friction for AI agents. Many cloud teams are experimenting with AI coding assistants but quickly discover a gap between what these tools promise and what their architectures allow. When an AI agent generates code, it often takes minutes—or

The traveling salesman problem asks a deceptively simple question: What’s the shortest route that visits every point exactly once? It’s one of the hardest problems in computer science, and mathematicians have been working on it for nearly a century. It’s also what FM Logistic‘s warehouse operators face every day in Poland. The facility spans eight

Organizations running on-premises workloads often face a difficult choice when moving to the cloud: how to modernize without losing the architectural consistency their business depends on. If you use Red Hat OpenShift, you have a way to bridge these environments without the risk of a forced re-platforming.  Google Cloud provides a secure, reliable, and high-performance