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ml-pipeline-ui failing on metadata api #11247
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@richardburakowski I found the solution. The ui deployment ml-pipeline-ui needs to have the environment variable DISABLE_GKE_METADATA set to 'true'. This disabled the gke metadata fetch, not available outside of GKE clusters. |
Hi @luko0610, There's no trace of DISABLE_GKE_METADATA in any version of the kustomize output making this look like new behaviour of the container image in the absence of gke metadata rather than a bug in the install manifests. |
thank you this solved my issues! |
Since GKE is only one of many platforms, change the default value of `DISABLE_GKE_METADATA` to `true`. Edit the gcp manifest to override that to `false` on GCP. Fixes: kubeflow#11247 Signed-off-by: Greg Sheremeta <[email protected]>
Since GKE is only one of many platforms, change the default value of `DISABLE_GKE_METADATA` to `true`. Edit the gcp manifest to override that to `false` on GCP. Fixes: kubeflow#11247 Signed-off-by: Greg Sheremeta <[email protected]>
Environment
Not seeing this in older versions of kubeflow/manifests, e.g. 1.6.1
2.3.0
Steps to reproduce
Navigate to kubeflow dashboard pipelines
An error occurred
upstream connect error or disconnect/reset before headers. reset reason: remote connection failure, transport failure reason: delayed connect error: 111
Expected result
No dashboard error
Materials and Reference
image: gcr.io/ml-pipeline/frontend:2.3.0
kubectl -n kubeflow logs -l app=ml-pipeline-ui
As a workaround, adding
metadata
to dns as an alias for any http server seems to work. It doesn't need to return cloud metadata, just connect.Impacted by this bug? Give it a 👍.
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