Why your Kubernetes clusters and GPUs should live under one roof
The world remains abuzz with AI hype, but the reality is that most modern applications aren’t purely AI workloads. The average company will have web services, APIs, databases, and background jobs running alongside its machine learning inference or training components. An architecture question everyone faces: should your Kubernetes cluster and GPU compute live in the same data center, or can you split them across providers?