| 2 Jun 2022 |
 Rachit Chauhan | yeah, so the problem was a missing Destination Rule(DR). Everything was working fine at my local but the way my org manages certificates is diff from how istio’s default auth.
istiod will configure each proxy with a TLS context it expects will work in istio’s default installation.
Had to add a DR resource for my setup to work. | 17:33:34 |
 Dan Sun | Not this field directly you need to use the timeout field on inference service yaml | 17:53:52 |
 Vivian Pan | Hi KServe team, our team tested out the new inference graph alpha features and it works great. We are wondering if there’s a roadmap for implementing an SDK for this, if there’s any help needed for this. We’d love to contribute | 17:59:03 |
|  _slack_kubeflow_U03J0LZFTL5 joined the room. | 22:12:38 |
| Dan Sun | It should be pretty straight forward to do, will write up an issue and instruction for you to contribute | 23:08:15 |
| 3 Jun 2022 |
 Shri Javadekar | Vivian Pan: How did you test the functionality? Did you download the patch and build the components yourself and deploy them before testing it? What components had to be built and deployed? | 03:36:58 |
|  HEM VATS joined the room. | 06:39:10 |
 zorba(손주형) | is it possible in go client??
there is only terminationGracePeriodSeconds in InferenceServiceSpec.PredictorSpec.PodSpec | 07:19:05 |
|  Christian Lehre joined the room. | 07:20:40 |
| Christian Lehre changed their display name from _slack_kubeflow_U03HW39JNLV to Christian Lehre. | 07:27:07 |
| Christian Lehre set a profile picture. | 07:27:08 |
| Christian Lehre | 
Download Skjermbilde 2022-06-03 kl. 09.26.09.png | 07:27:10 |
| Christian Lehre | Hello! I have deployed Kubeflow v1.5 to GCP, and trying to apply a simple manifest for deploying an xgboost model that I have uploaded to the kubeflow-managed Cloud Storage. When i deploy to the kubeflow namespace that comes with the kubeflow deployment, the init container of the InferenceService that mounts the model to the volume of the pod is not running. However, when i deploy to another namespace the init container runs, but now the caller does not have access to mount the model. Any ideas what can be the problem? Another problem I have is that the models page in the Kubeflow UI simply renders a blank page. I inspect the page and see the following error messages in the console | 07:27:10 |
 Benjamin Tan | Don't deploy in the kubeflow namespace | 08:01:44 |
| Benjamin Tan | You can create some other namespace and deploy it there | 08:02:01 |
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+1 (2297781881 | 08:03:28 |
| Christian Lehre | Benjamin Tan Thanks for the reply! How would i then make sure that i have access to the storage? Im very new in the k8s world, so it might be a stupid question. | 08:03:48 |
|  Sebastian Lehrig joined the room. | 08:04:27 |
| Benjamin Tan | lol not stupid. sooo if u get logs from storage-initializer , you usually will get some hints. | 08:11:24 |
| Benjamin Tan | Where is your Kubeflow installation on? | 08:11:54 |
| Benjamin Tan | GCP? | 08:11:56 |
| Benjamin Tan | https://kserve.github.io/website/get_started/first_isvc/ | 08:14:00 |
| Christian Lehre | GCP, correct 🙂 I get the following Traceback in the storage-intializer container:
Traceback (most recent call last):
File "/storage-initializer/scripts/initializer-entrypoint", line 14, in module
kserve.Storage.download(src_uri, dest_path)
File "/usr/local/lib/python3.7/site-packages/kserve/storage.py", line 67, in download
Storage._download_gcs(uri, out_dir)
File "/usr/local/lib/python3.7/site-packages/kserve/storage.py", line 152, in _download_gcs
for blob in blobs:
File "/usr/local/lib/python3.7/site-packages/google/api_core/page_iterator.py", line 212, in _items_iter
for page in self._page_iter(increment=False):
File "/usr/local/lib/python3.7/site-packages/google/api_core/page_iterator.py", line 243, in _page_iter
page = self._next_page()
File "/usr/local/lib/python3.7/site-packages/google/api_core/page_iterator.py", line 372, in _next_page
response = self._get_next_page_response()
File "/usr/local/lib/python3.7/site-packages/google/api_core/page_iterator.py", line 432, in _get_next_page_response
method=self._HTTP_METHOD, path=self.path, query_params=params
File "/usr/local/lib/python3.7/site-packages/google/cloud/storage/_http.py", line 78, in api_request
return call()
File "/usr/local/lib/python3.7/site-packages/google/api_core/retry.py", line 290, in retry_wrapped_func
on_error=on_error,
File "/usr/local/lib/python3.7/site-packages/google/api_core/retry.py", line 188, in retry_target
return target()
File "/usr/local/lib/python3.7/site-packages/google/cloud/_http.py", line 479, in api_request
raise exceptions.from_http_response(response)
google.api_core.exceptions.Forbidden: 403 GET https://storage.googleapis.com/storage/v1/b/akerbp-kubeflow-core-kfp/o?projection=noAcl&prefix=models%2Fxgboost_lithology%2Fmodel.bst%2F&prettyPrint=false: Caller does not have storage.objects.list access to the Google Cloud Storage bucket. | 08:15:02 |
| Benjamin Tan | Beautiful | 08:15:30 |
| Benjamin Tan | So you need a few things. | 08:16:40 |
| Benjamin Tan | 1. Set up another namespace to deploy your model (kubctl create ns kserve-test) | 08:17:09 |
| Benjamin Tan | 2. Give permissions for the service account in the kfserve-test namespace to access the GCS bucket | 08:18:06 |
| Benjamin Tan | You might need your K8s admin to help u do this | 08:18:56 |
| Benjamin Tan | For the namespace:
kind: Namespace
apiVersion: v1
metadata:
name: kfserving-test
labels:
serving.kubeflow.org/inferenceservice: "enabled" | 08:21:16 |
| Benjamin Tan | gcloud iam service-accounts add-iam-policy-binding google-service-account-that-can-access-gcs-buckets \
--role roles/iam.workloadIdentityUser \ (or storage list role)
--member "serviceAccount: GOOGLE PROJECT NAME .svc.id.goog[kfserving-test/default]" | 08:23:28 |
