Testing 1.9.0-rc.2
Closed this issue · 6 comments
tarilabs commented
Installation
Used:
kubectl apply -k "https://github.com/kubeflow/model-registry/manifests/kustomize/overlays/db?ref=v0.2.2-alpha"
kubectl apply -k "https://github.com/kubeflow/model-registry/manifests/kustomize/options/istio?ref=v0.2.2-alpha"
kubectl wait --for=condition=available -n kubeflow deployment/model-registry-deployment --timeout=1m
kubectl logs -n kubeflow deployment/model-registry-deployment
kubectl port-forward svc/model-registry-service -n kubeflow 8081:8080
curl -X 'GET' 'http://localhost:8081/api/model_registry/v1alpha3/registered_models?pageSize=100&orderBy=ID&sortOrder=DESC' -H 'accept: application/json' | jq
NOTE:
- in installation, use 0.2.2
Getting Started: Indexing a Model
- #90 (comment)
- https://github.com/kubeflow/model-registry/pull/116/files#diff-6b074bce6a463d7cd6b69e5b1901d4d48c6ff2cd150a40ce849f7a99cb68bce4R105
NOTE:
should add:
- version of model-registry
is_secure=False
to client
Getting Started: integration with KServe example
Note:
- consider adding is_secure
- consider changing lookup_version
tarilabs commented
Working with KServe python SDK 0.12.1:
Then:
kubectl describe isvc -A
Name: mnist
Namespace: kubeflow-user-example-com
Labels: modelregistry/model-version-id=2
modelregistry/registered-model-id=1
Annotations: <none>
API Version: serving.kserve.io/v1beta1
Kind: InferenceService
Metadata:
Creation Timestamp: 2024-07-01T15:24:31Z
Finalizers:
inferenceservice.finalizers
Generation: 1
Resource Version: 82582
UID: 228c1c03-8763-40f5-a5bb-b18742df0868
Spec:
Predictor:
Model:
Model Format:
Name: onnx
Version: 1
Name:
Protocol Version: v2
Resources:
Runtime: kserve-ovms
Storage Uri: https://github.com/tarilabs/demo20231212/raw/main/v1.nb20231206162408/mnist.onnx
Status:
Model Status:
Last Failure Info:
Message: Waiting for runtime to become available
Reason: RuntimeNotRecognized
States:
Active Model State:
Target Model State: FailedToLoad
Transition Status: InvalidSpec
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Warning InternalError 23s (x15 over 105s) v1beta1Controllers No ServingRuntimes or ClusterServingRuntimes with the name: kserve-ovms
Which is expected because I didn't install OpenVINO in this test cluster for this ONNX file, but that is beyond the scope of the tutorial.
tarilabs commented
NOTE add for troubleshooting from withing notebook:
wget -nv -O- model-registry-service.kubeflow.svc.cluster.local:8080/api/model_registry/v1alpha3/registered_models
curl model-registry-service.kubeflow.svc.cluster.local:8080/api/model_registry/v1alpha3/registered_models
tarilabs commented
Note:
retested specifically the failure when KServe SDK uses Ray and Ray fails.
worked using image jupyter-tensorflow-full:v1.9.0-rc.0
and pinning transitive as:
!pip install kserve=="0.13.0" ray=="2.10.0" attrs=="21.4.0" jsonschema=="4.17.3"
proof: test20240702.zip
(one reason more for the REST rebase 😄 )
tarilabs commented
The following related changes:
were tested out with a local minikube and 1.9.0-rc.2
from KF/manifest
tarilabs commented
Relevant test of Model Registry 0.2.3 with KF 1.9rc2