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feat(backend): Upgrade Argo server image version to v2.11.6 #4693
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Original file line number | Diff line number | Diff line change |
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@@ -27,7 +27,8 @@ spec: | |
- --configmap | ||
- workflow-controller-configmap | ||
- --executor-image | ||
- gcr.io/ml-pipeline/argoexec:v2.7.5-license-compliance | ||
- gcr.io/ml-pipeline/argoexec:v2.11.6-license-compliance | ||
- --namespaced | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. This is the extra argument that I need to specifically add for my deployment. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Is there a corresponding documentation? Does omitting the argument make it cluster mode? We need to make sure it is customizable from an overlay to continue support multi-user mode. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. The cluster vs namespace install seems to start since v2.5 - this can also be found in the v2.5 release branch. In my case, it did become a cluster install if I simply replace the image version to I am not familiar with the There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Error log from when trying to launch pipelines without E1107 01:14:06.943364 1 reflector.go:153] pkg/mod/k8s.io/client-go@v0.17.8/tools/cache/reflector.go:105: Failed to list *unstructured.Unstructured: workflowtemplates.argoproj.io is forbidden: User "system:serviceaccount:kubeflow:argo" cannot list resource "workflowtemplates" in API group "argoproj.io" at the cluster scope |
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command: | ||
- workflow-controller | ||
env: | ||
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@@ -36,7 +37,7 @@ spec: | |
fieldRef: | ||
apiVersion: v1 | ||
fieldPath: metadata.namespace | ||
image: gcr.io/ml-pipeline/workflow-controller:v2.7.5-license-compliance | ||
image: gcr.io/ml-pipeline/workflow-controller:v2.11.6-license-compliance | ||
imagePullPolicy: IfNotPresent | ||
name: workflow-controller | ||
resources: {} | ||
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@@ -25,7 +25,7 @@ ACCOUNT=$(gcloud info --format='value(config.account)') | |
kubectl create clusterrolebinding PROW_BINDING --clusterrole=cluster-admin --user=$ACCOUNT --dry-run -o yaml | kubectl apply -f - | ||
kubectl create clusterrolebinding DEFAULT_BINDING --clusterrole=cluster-admin --serviceaccount=default:default --dry-run -o yaml | kubectl apply -f - | ||
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ARGO_VERSION=v2.7.5 | ||
ARGO_VERSION=v2.11.6 | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Not sure if I need to update this one There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I think this will be needed for all the test infrastructure to run with argo 2.11.6 |
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# if argo is not installed | ||
if ! which argo; then | ||
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@@ -22,7 +22,7 @@ RUN cd /python/src/github.com/kubeflow/pipelines | |
# Install argo. | ||
RUN echo "install argo" | ||
RUN mkdir -p /usr/local/bin/ | ||
#RUN ARGO_VERSION=v2.7.5 && curl -sSL -o /usr/local/bin/argo \ | ||
#RUN ARGO_VERSION=v2.11.6 && curl -sSL -o /usr/local/bin/argo \ | ||
RUN ARGO_VERSION=v2.4.3 && curl -sSL -o /usr/local/bin/argo \ | ||
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Not sure about this one either. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. This is used to kick of the ML pipeline sample e2e test, since the changes you do is only for the server side I think we should not update this to 2.11.6. But I think we should go with 2.7.7 since that is the version that is used by Kubeflow today. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. There was a bug from argo that prevented using the argo cli from a container, that's why we were stuck on 2.4.3. I'm not sure about latest status, if the latest version works, we can upgrade too. |
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"https://github.com/argoproj/argo/releases/download/$ARGO_VERSION/argo-linux-amd64" && \ | ||
chmod +x /usr/local/bin/argo | ||
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I replace all
v2.7.5
->v2.11.6
in the repo, but I am not sure if I need to update this one.There was a problem hiding this comment.
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I think we should leave this one as well since it is the Kubeflow backend which will be running 2.7.7. Argo is in this case used to validate the workflows to check if they are valid according to argo.
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It seems that we have several places that use Argo but they can be somehow independent of each other. Can you tell me how each of them is used so that I can get a clearer picture of how they work together?