Kubernetes has transformed cloud infrastructure by enabling scalable, containerized applications. While it initially gained traction for managing web applications and microservices, its capabilities now extend to AI/ML workloads, making it the go-to platform for data scientists and machine learning engineers. Running AI/ML workloads on Kubernetes presents unique challenges, including: Specialized hardware requirements (e.g., GPUs, TPUs) Scalability for model training and inference Complex dat...
