Update KubeRay tutorial with newest changes on Kuberay version#3121
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End-to-end validation on a fresh AWS-CAPI workload cluster surfaced several issues with the tutorial: - The catalog ships kuberay-operator 1.0.0 (not 1.1.0). - kubectl gs template app now prints a deprecation banner that pollutes stdout when piped to a file, producing invalid YAML. Suppress with 2>/dev/null. - The sample used apiVersion ray.io/v1alpha1; the served storage version is ray.io/v1. - The sample bundled GPU bits (nvidia runtimeClass, GPU tolerations, GPU node affinity) that prevent scheduling on non-GPU clusters. Moved to an explanatory note for GPU users. - No securityContext on pods/containers means PSS-restricted Kyverno policies reject the head and worker pods. Add runAsNonRoot, seccompProfile, drop ALL capabilities, allowPrivilegeEscalation=false. - enableInTreeAutoscaling injects an autoscaler sidecar that also needs an explicit securityContext via autoscalerOptions, or the whole pod gets rejected. - 2Gi head memory OOMs as soon as a job lands (Ray dashboard subprocesses idle at ~1.94Gi). Bumped to 4Gi. - Added a REST API alternative for users without Python/ray installed, and fixed the ray CLI working_dir so it points at the gist zip instead of "." (which only works if dt.py is in the cwd).
pipo02mix
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May 19, 2026
pipo02mix
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May 19, 2026
pipo02mix
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May 19, 2026
pipo02mix
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May 19, 2026
Co-authored-by: Fernando Ripoll <fernando@giantswarm.io>
lyind
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Didn't test the YAML and do a test install/run, but the changes look good to me, otherwise.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Towards giantswarm/kuberay#6