Kubernetes isn't ready for AI - Let's talk about it
The shift to AI/ML workloads is challenging Kubernetes' original "cattle, not pets" philosophy. Unlike stateless microservices, a single failure in a distributed, tightly coupled AI job requiring specialized hardware can cause the entire, expensive process to collapse. This creates a reliability gap where existing observability solutions are insufficient; a new, predictive reliability solution is required to prevent these critical failures proactively.