Fix Profile-controller README file & sample files (#7244)

Signed-off-by: diana <difince@gmail.com>
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Diana Atanasova 2023-08-22 21:44:09 +03:00 коммит произвёл GitHub
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@ -38,16 +38,16 @@ So profile owner can access services in above namespace via Istio (browser).
Cluster admin can manage access management for cluster users:
**To create an isolated namespace `kubeflow-user1` for user `user1@abcd.com`**
- Admin can create a [profile](config/samples/profile_v1beta1_profile.yaml) via kubectl:
**To create an isolated namespace `test-user-profile` for user `test-user@kubeflow.org`**
- Admin can create a [profile](config/samples/_v1_profile.yaml) via kubectl:
```
kubectl create -f /path/to/profile/config
```
**To revoke access to namespace `kubeflow-user1` from user `user1@abcd.com` and delete namespace `kubeflow-user1`**
- Admin can delete profile kubeflow-user1:
**To revoke access to namespace `test-user-profile` from user `test-user@kubeflow.org` and delete namespace `test-user-profile`**
- Admin can delete profile test-user-profile:
```
kubectl delete profile kubeflow-user1
kubectl delete profile test-user-profile
```
### Self-serve kfam UI
@ -63,7 +63,7 @@ Users with access to cluster API server should be able to register and use kubef
Profile now support configuring `ResourceQuotaSpec` as part of profile CR.
- `ResourceQuotaSpec` field will accept standard [k8s ResourceQuotaSpec](https://godoc.org/k8s.io/api/core/v1#ResourceQuotaSpec)
- A resource quota will be created in target namespace.
- [Example](config/samples/profile_v1beta1_profile.yaml)
- [Example](config/samples/_v1beta1_profile.yaml)
### Plugins
Plugins field is introduced to support customized actions based on k8s cluster's surrounding platform.

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@ -1,6 +1,15 @@
apiVersion: kubeflow.org/v1beta1
kind: Profile
metadata:
name: profile-sample
name: test-user-profile #replace with the name of profile you want, this will be user's namespace name
spec:
# TODO(user): Add fields here
owner:
kind: User
name: test-user@kubeflow.org
resourceQuotaSpec: # resource quota can be set optionally
hard:
cpu: "2"
memory: 2Gi
requests.nvidia.com/gpu: "1"
persistentvolumeclaims: "1"
requests.storage: "5Gi"