Comments (2)
Everything appears to work as expected, but we should observe at scale to be sure as part of the testing issues. Closing as completed.
from dandi-hub.
Heres what happens during spin up:
The hub creates a Pod with a nodeSelector
of gpu
or default
.
# We don't have enough nodes already spun up. And theres nothing we can boot either.
Warning FailedScheduling 55s jupyterhub-user-scheduler 0/4 nodes are available: 4 node(s) didn't match Pod's node affinity/selector. preemption: 0/4 nodes are available: 4 Preemption is not helpful for scheduling..
# Karpenter magic: Under the hood a nodeclaim is created, which is a Karpenter CRD.
# In response, Karpenter interacts with AWS, creates a new machine and registers it as a K8s Node
2024-03-26T15:15:17Z [Normal] Pod should schedule on: nodeclaim/default-55cwr
# Dont be fooled by this message from the cluster-autoscaler. We don't want the pod to trigger cluster-autoscaler scale-up, we are using Karpenter
2024-03-26T15:15:24Z [Normal] pod didn't trigger scale-up: 1 node(s) didn't match Pod's node affinity/selector
# Now k8s behaves normally, the pod has been assigned to a Node
2024-03-26T15:16:03.407813Z [Normal] Successfully assigned jupyterhub/jupyter-asmacdo to ip-100-64-16-100.us-west-1.compute.internalNormal
from dandi-hub.
Related Issues (20)
- Configure EFS Lifecycle
- Create maintenance policy
- Consider refactoring the DoEKS implementation with eksctl
- [do-eks] ./cleanup.sh failed HOT 2
- Docker images (GPU, MATLAB, GPU+MATLAB) are failing to build
- Migrate existing home dir data to staging HOT 6
- Push to production
- Optimize server start up time HOT 1
- Provision infrastructure with Terraform Cloud HOT 1
- Avoid "Service unavailable" HOT 4
- Minimum node count in EKS clusters in production does not reflect Terraform value set in do_eks setup HOT 1
- Save Terraform state to S3 bucket HOT 1
- [BICAN] Upgrade k8s (1.27 is EOL July 24)
- upgrade pynwb version
- FEATURE REQUEST: Configure SSH Server in dandi-hub (staging-hub) HOT 2
- Add user facing message to user-hubs
- Configure spot vs on_demand in tfvars
- Explore options for providing users with on-demand resources HOT 1
- JupyterHub intermittently *freezing* and asking to be *restart notebook* HOT 2
- Collect user-pod logs persistently
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