Dag And Step Based Workflow Definition With Kubernetes Crd Abstraction

via “kubernetes-native custom resource definitions (crds) for ml workloads with declarative configuration”

ML toolkit for Kubernetes — pipelines, notebooks, training, serving, feature store.

Unique: Implements ML workloads as Kubernetes custom resources (CRDs) with declarative YAML configuration, enabling GitOps workflows and integration with Kubernetes governance (RBAC, audit logging, quotas). Each CRD has a corresponding controller that implements the desired behavior.

vs others: More Kubernetes-native than imperative APIs (no SDK required) and more portable than cloud-specific infrastructure (SageMaker, Vertex AI) because it uses standard Kubernetes conventions.