Hey Guys,
I used the tf code provided at https://github.com/awslabs/data-on-eks/tree/main/ai-ml/jupyterhub to deploy jupyterhub on eks.
While testing I get the below errors. Please guide how to resolve it? I am new to eks as well as jupyterhub. Based on the documentation at JupyterHub on EKS | Data on EKS, I expected to see a LB, but that does not exist either.
I am testing by port forwarding the cluter-ip.
Please guide.
The errors are as below
2023-12-03T18:48:56Z [Warning] Failed to schedule pod, incompatible with provisioner "gpu-ts", daemonset overhead={"cpu":"680m","memory":"620Mi","pods":"6"}, did not tolerate nvidia.com/gpu=:NoSchedule; incompatible with provisioner "gpu", daemonset overhead={"cpu":"680m","memory":"620Mi","pods":"6"}, did not tolerate nvidia.com/gpu=:NoSchedule; incompatible with provisioner "default", daemonset overhead={"cpu":"680m","memory":"620Mi","pods":"6"}, no instance type satisfied resources {"cpu":"2680m","memory":"8812Mi","pods":"7"} and requirements NodeGroupType In [default], hub.jupyter.org/node-purpose In [user], karpenter.k8s.aws/instance-family In [c5 m5 r5], karpenter.k8s.aws/instance-size In [16xlarge 24xlarge 2xlarge 4xlarge 8xlarge and 1 others], karpenter.sh/capacity-type In [on-demand spot], karpenter.sh/provisioner-name In [default], kubernetes.io/arch In [amd64], kubernetes.io/os In [linux], provisioner In [default] (no instance type met the scheduling requirements or had a required offering); incompatible with provisioner "trainium", daemonset overhead={"cpu":"680m","memory":"620Mi","pods":"6"}, did not tolerate aws.amazon.com/neuroncore=true:NoSchedule; did not tolerate aws.amazon.com/neuron=true:NoSchedule; incompatible with provisioner "inferentia", daemonset overhead={"cpu":"680m","memory":"620Mi","pods":"6"}, did not tolerate aws.amazon.com/neuroncore=true:NoSchedule; did not tolerate aws.amazon.com/neuron=true:NoSchedule
Second error is
2023-12-03T19:26:10Z [Warning] Failed to schedule pod, incompatible with provisioner "gpu-ts", daemonset overhead={"cpu":"680m","memory":"620Mi","pods":"6"}, no instance type satisfied resources {"cpu":"2680m","memory":"4716Mi","nvidia.com/gpu":"1","pods":"7"} and requirements NodeGroupType In [gpu-ts], hub.jupyter.org/node-purpose In [user], karpenter.k8s.aws/instance-family In [g5], karpenter.k8s.aws/instance-size In [16xlarge 24xlarge 2xlarge 4xlarge 8xlarge and 1 others], karpenter.sh/capacity-type In [on-demand spot], karpenter.sh/provisioner-name In [gpu-ts], kubernetes.io/arch In [amd64], kubernetes.io/os In [linux], provisioner In [gpu-ts] (no instance type met the scheduling requirements or had a required offering); incompatible with provisioner "gpu", daemonset overhead={"cpu":"680m","memory":"620Mi","pods":"6"}, incompatible requirements, key karpenter.sh/provisioner-name, karpenter.sh/provisioner-name In [gpu-ts] not in karpenter.sh/provisioner-name In [gpu]; incompatible with provisioner "default", daemonset overhead={"cpu":"680m","memory":"620Mi","pods":"6"}, incompatible requirements, key karpenter.sh/provisioner-name, karpenter.sh/provisioner-name In [gpu-ts] not in karpenter.sh/provisioner-name In [default]; incompatible with provisioner "trainium", daemonset overhead={"cpu":"680m","memory":"620Mi","pods":"6"}, did not tolerate aws.amazon.com/neuroncore=true:NoSchedule; did not tolerate aws.amazon.com/neuron=true:NoSchedule; incompatible with provisioner "inferentia", daemonset overhead={"cpu":"680m","memory":"620Mi","pods":"6"}, did not tolerate aws.amazon.com/neuroncore=true:NoSchedule; did not tolerate aws.amazon.com/neuron=true:NoSchedule