Releases

Kubeflow 26.03 is a manifests and version-alignment release for the AI Reference Platform, syncing many components (Kubernetes 1.34+, Knative 1.20, cert-manager 1.19.4, Istio 1.29.0, KFP 2.16.0, and others) while tightening pod security enforcement to baseline and hardening network policies across core namespaces. Operators running Kubeflow Pipelines under PSS restricted should check compatibility before upgrading.

• breakingPod security standard default now baseline

  Pod security enforcement across the reference platform manifests moves to the baseline profile. Review workloads that previously relied on privileged or restricted-incompatible settings before rolling this out.

• breakingNetworkpolicies tightened for core namespaces

  Network policies for cert-manager, knative-serving, istio-system, dex, and oauth2-proxy have been tightened. Confirm any custom traffic paths into or out of these namespaces still work after upgrading.

• breakingKFP v1/v2 compatibility gap under PSS restricted

  Kubeflow Pipelines v1 and v2 may not run cleanly in namespaces enforcing PSS restricted. If you run KFP under restricted pod security, test before upgrading or plan for a workaround.

v0.17.0 delivers substantial LLM-focused improvements with the new LLMInferenceService beta, enhanced storage parallelization, vLLM 0.15.1 upgrade, and important CVE fixes affecting production deployments.

• securityApply critical CVE patches immediately

  This release addresses several high-impact CVEs including path traversal (storage-initializer), HTTP parser vulnerabilities (h11, starlette), and cryptography subgroup attacks. Update to v0.17.0 promptly, especially if you're using storage-initializer or external model downloads. Review your current CVE scanning results against the patched versions.

• breakingPlan LLMInferenceService migration path

  The new LLMInferenceService CRD introduces a dedicated API for LLM workloads with different semantics than standard InferenceService. If you're running LLM models, evaluate migrating to this new resource type for better autoscaling, routing, and operational features. The CRD includes breaking changes in API structure.

• enhancementLeverage parallel storage downloads for faster deployments

  Storage-initializer now downloads blobs in parallel from S3 and Azure, dramatically reducing model loading times for large models. This is particularly beneficial for LLM workloads. No configuration changes needed - the improvement is automatic upon upgrade.