ryansteakley

Hey @Harikantipudi thanks for the issue do you have any links towards where there is discussion of "MLflow integration is being highly looked upon in combination with Kubeflow", so I...

Hey @TranThanh96, I responded to you on slack, can you additionally specify which deployment option you ran, was it the rds-s3?

sounds good, verify you are able to login and run any samples you wish.

looks like you have several pods in crashloop backoff. Is your instance the same size or similar to the one described in https://awslabs.github.io/kubeflow-manifests/docs/deployment/prerequisites/ Did you follow the auto-setup python script?

run kubectl describe pod -n and similarily kubectl logs -n on the pods in failure state. and share anything you find there as well

`Warning Failed 34m (x5 over 34m) kubelet Error: secret "mlpipeline-minio-artifact" not found` in ml-pipeline logs. Can you check to see if this secret exists. Run `kubectl get secrets -n kubeflow`

Can you verify that you are using v3.2.0 of kustomize? Run `kubectl delete pods -n kubeflow --all` and see if the pods come up normally.

What do you see when you login? Are any other pods still failing?

Can you verify that the s3-secret you created is following this requirement. `Configure a Secret (e.g. s3-secret) with your AWS credentials. These need to be long-term credentials from an IAM...

No way, to prove. Can you one more time describe the ml-pipeline pod. I would suggest restarting from a fresh cluster, and follow the cluster pre-req listed above.