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On a fresh MicroK8s cluster I can't create Seldon resources. On v1.17, for comparison, everything works as expected as far as I can see.
sudo snap install microk8s --classic --channel=1.18/stable # Download snap "microk8s" ... # microk8s (1.18/stable) v1.18.0 from Canonical✓ installed microk8s.kubectl version # Client Version: version.Info{Major:"1", Minor:"18", GitVersion:"v1.18.0", GitCommit:"9e991415386e4cf155a24b1da15becaa390438d8", GitTreeState:"clean", BuildDate:"2020-03-25T14:58:59Z", GoVersion:"go1.13.8", Compiler:"gc", Platform:"linux/amd64"} # Server Version: version.Info{Major:"1", Minor:"18", GitVersion:"v1.18.0", GitCommit:"9e991415386e4cf155a24b1da15becaa390438d8", GitTreeState:"clean", BuildDate:"2020-03-25T14:50:46Z", GoVersion:"go1.13.8", Compiler:"gc", Platform:"linux/amd64"} snap list helm # Name Version Rev Tracking Publisher Notes # helm 3.1.2 200 latest/stable snapcrafters classic microk8s.enable dns istio registry storage # Enabling DNS ... helm version # version.BuildInfo{Version:"v3.1.2", GitCommit:"d878d4d45863e42fd5cff6743294a11d28a9abce", GitTreeState:"clean", GoVersion:"go1.13.8"} microk8s.istioctl version # client version: 1.3.4 # control plane version: 1.3.4 kubectl create namespace seldon-system # namespace/seldon-system created helm install seldon-core seldon-core-operator\ --repo https://storage.googleapis.com/seldon-charts\ --set usageMetrics.enabled=true\ --namespace seldon-system\ --set istio.enabled=true # NAME: seldon-core # LAST DEPLOYED: Thu Apr 9 17:28:15 2020 # NAMESPACE: seldon-system # STATUS: deployed # REVISION: 1 # TEST SUITE: None kubectl get all -n seldon-system # NAME READY STATUS RESTARTS AGE # pod/seldon-controller-manager-5c94779c7d-vvlpb 1/1 Running 0 4m41s # # NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE # service/seldon-webhook-service ClusterIP 10.152.183.216 <none> 443/TCP 4m41s # # NAME READY UP-TO-DATE AVAILABLE AGE # deployment.apps/seldon-controller-manager 1/1 1 1 4m41s # # NAME DESIRED CURRENT READY AGE # replicaset.apps/seldon-controller-manager-5c94779c7d 1 1 1 4m41s helm install single-model helm-charts/seldon-single-model # Error: SeldonDeployment.machinelearning.seldon.io "single-model" is invalid: metadata.managedFields.fieldsType: Invalid value: "": must be `FieldsV1` kubectl apply -f - << END apiVersion: machinelearning.seldon.io/v1 kind: SeldonDeployment metadata: name: iris-model spec: name: iris predictors: - graph: implementation: SKLEARN_SERVER modelUri: gs://seldon-models/sklearn/iris name: classifier name: default replicas: 1 END # The SeldonDeployment "iris-model" is invalid: metadata.managedFields.fieldsType: Invalid value: "": must be `FieldsV1`
Fresh install of v1.17:
microk8s.stop # Stopped. sudo snap remove --purge microk8s # microk8s removed sudo snap install microk8s --classic --channel=1.17/stable # Download snap "microk8s" ... # microk8s (1.17/stable) v1.17.4 from Canonical✓ installed microk8s.kubectl version # Client Version: version.Info{Major:"1", Minor:"17", GitVersion:"v1.17.4", GitCommit:"8d8aa39598534325ad77120c120a22b3a990b5ea", GitTreeState:"clean", BuildDate:"2020-03-12T21:03:42Z", GoVersion:"go1.13.8", Compiler:"gc", Platform:"linux/amd64"} # Server Version: version.Info{Major:"1", Minor:"17", GitVersion:"v1.17.4", GitCommit:"8d8aa39598534325ad77120c120a22b3a990b5ea", GitTreeState:"clean", BuildDate:"2020-03-12T20:55:23Z", GoVersion:"go1.13.8", Compiler:"gc", Platform:"linux/amd64"} kubectl create namespace seldon-system # namespace/seldon-system created helm install seldon-core seldon-core-operator\ --repo https://storage.googleapis.com/seldon-charts\ --set usageMetrics.enabled=true\ --namespace seldon-system\ --set istio.enabled=true # NAME: seldon-core # LAST DEPLOYED: Thu Apr 9 17:48:00 2020 # NAMESPACE: seldon-system # STATUS: deployed # REVISION: 1 # TEST SUITE: None kubectl get all -n seldon-system # NAME READY STATUS RESTARTS AGE # pod/seldon-controller-manager-c8d5f9448-67ltg 1/1 Running 0 3m27s # # NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE # service/seldon-webhook-service ClusterIP 10.152.183.205 <none> 443/TCP 3m27s # # NAME READY UP-TO-DATE AVAILABLE AGE # deployment.apps/seldon-controller-manager 1/1 1 1 3m27s # # NAME DESIRED CURRENT READY AGE # replicaset.apps/seldon-controller-manager-c8d5f9448 1 1 1 3m27s helm install single-model helm-charts/seldon-single-model # NAME: single-model # LAST DEPLOYED: Thu Apr 9 17:52:23 2020 # NAMESPACE: default # STATUS: deployed # REVISION: 1 # TEST SUITE: None kubectl apply -f - << END apiVersion: machinelearning.seldon.io/v1 kind: SeldonDeployment metadata: name: iris-model spec: name: iris predictors: - graph: implementation: SKLEARN_SERVER modelUri: gs://seldon-models/sklearn/iris name: classifier name: default replicas: 1 END # seldondeployment.machinelearning.seldon.io/iris-model created kubectl get all # NAME READY STATUS RESTARTS AGE # pod/iris-default-4903e3c-794fcfff5-shzjh 0/2 Running 0 5m34s # pod/single-model-default-de240ba-588969bfd6-psn6m 2/2 Running 0 6m24s # # NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE # service/iris-default-classifier-seldonio-sklearnserver-rest-0-2 ClusterIP 10.152.183.143 <none> 9000/TCP 5m34s # service/kubernetes ClusterIP 10.152.183.1 <none> 443/TCP 16m # service/seldon-903f456dbf43f52893de88f49d3f8964 ClusterIP 10.152.183.122 <none> 9000/TCP 6m24s # service/single-model-single-model-default ClusterIP 10.152.183.62 <none> 8000/TCP,5001/TCP 2m20s # # NAME READY UP-TO-DATE AVAILABLE AGE # deployment.apps/iris-default-4903e3c 0/1 1 0 5m34s # deployment.apps/single-model-default-de240ba 1/1 1 1 6m24s # # NAME DESIRED CURRENT READY AGE # replicaset.apps/iris-default-4903e3c-794fcfff5 1 1 0 5m34s # replicaset.apps/single-model-default-de240ba-588969bfd6 1 1 1 6m24s
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Reference: https://github.com/kubedb/issues/issues/739
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Duplicate of #1675
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On a fresh MicroK8s cluster I can't create Seldon resources. On v1.17, for comparison, everything works as expected as far as I can see.
Fresh install of v1.17:
The text was updated successfully, but these errors were encountered: