One mental model for Kubernetes, Slurm, Ray, and Spark: a unified take on distributed compute
ArchitectingAI · reddit · 2026-09-08
Pawan Kumar Jha published a long-form article building a framework-independent mental model for distributed compute, instead of learning Kubernetes, Slurm, Ray, and Spark in isolation.
The core idea: while the four systems use different abstractions, they solve largely the same underlying problems — scheduling, resource management, worker execution, state, communication, memory, and failure recovery. The article first defines the general model, then maps each system onto it, highlighting how each draws the boundaries between cluster scheduler, runtime, and application-level scheduler. The author invites discussion on where those boundaries should sit.
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