kfctl updates for v0.7 - GCP docs only (#1234)

* WIP v0.7 updates to kfctl init

* More updates to deployment; updated customization; added interim URIs for config files.

* Updated section on accessing UI in CLI deployment.

* Updated kfctl commands in remaining GCP deployment docs.

* Updated the guide to securing clusters for kfctl v0.7.

* Updated the troubleshooting guide for kfctl v0.7.

* Fixed list formatting throughout the guide to securing clusters.

* Addressed review comments and set KF latest version.

* WIP updating for change in config file name.

* Further clarifications to the deployment and deletion guides.

* Updated the customization guide for change in config name and delete.

* Updated for new config file name in the guide to monitoring IAP.

* Changed KFAPP variable in auth guide.

* Updated Filestore guide.

* A few tweaks.

* Updated cluster security guide.

* Updated the troubleshooting guide.

* Standardised CONFIG_FILE to contain full path.

* Updated guide to custom domains.

* Added GPU info and clarified KF-NAME/KF_DIR.

* Updated to latest RC and config URLs.

content/docs/gke/authentication.md

@@ -9,7 +9,7 @@ weight = 4
 
 When you [set up Kubeflow for GCP](/docs/gke/deploy), it will automatically
 [provision three service accounts](https://www.kubeflow.org/docs/gke/deploy/deploy-cli/#gcp-service-accounts)
-with different privileges in the `kubeflow` namespace. In particular, the `${KFAPP}-user` service account is
+with different privileges in the `kubeflow` namespace. In particular, the `${KF_NAME}-user` service account is
 meant to grant your user services access to GCP. The credentials to this service account can be accessed within
 the cluster as a [Kubernetes secret](https://kubernetes.io/docs/concepts/configuration/secret/) called `user-gcp-sa`.
 
@@ -104,7 +104,7 @@ so be careful which Pods you grant access to.
 1. **Set the `GOOGLE_APPLICATION_CREDENTIALS` environment variable** to point to the service account.
 GCP libraries will use this environment variable to find the service account and authenticate with GCP.
 
-The following YAML describes a Pod that has access to the `${KFAPP}-user` service account:
+The following YAML describes a Pod that has access to the `${KF_NAME}-user` service account:
 ```
 apiVersion: v1
 kind: Pod

content/docs/gke/cloud-filestore.md

@@ -17,11 +17,54 @@ Cloud Filestore is very useful for creating a shared filesystem that can be moun
 This guide assumes you have already set up Kubeflow on GCP. If you haven't done
 so, follow the guide to [deploying Kubeflow on GCP](/docs/gke/deploy/).
 
-The instructions below assume that the `${KFAPP}` environment variable contains 
-the *name* (not the full path) of the directory containing your Kubeflow 
-configurations. See the
-[Kubeflow deployment guide](/docs/gke/deploy/deploy-cli/) for details of this
-directory.
+This guide assumes the following settings: 
+
+* The `${KF_DIR}` environment variable contains the path to
+  your Kubeflow application directory, which holds your Kubeflow configuration 
+  files. For example, `/opt/my-kubeflow/`.
+
+  ```
+  export KF_DIR=<path to your Kubeflow application directory>
+  ``` 
+
+* The `${CONFIG_FILE}` environment variable contains the path to your 
+  Kubeflow configuration file.
+
+  ```
+  export CONFIG_FILE=${KF_DIR}/kfctl_gcp_iap.yaml
+  ```
+
+    Or:
+
+  ```
+  export CONFIG_FILE=${KF_DIR}/kfctl_gcp_basic_auth.yaml
+  ```
+
+* The `${KF_NAME}` environment variable contains the name of your Kubeflow 
+  deployment. You can find the name in your `${CONFIG_FILE}` 
+  configuration file, as the value for the `metadata.name` key.
+
+  ```
+  export KF_NAME=<the name of your Kubeflow deployment>
+  ```
+
+* The `${PROJECT}` environment variable contains the ID of your GCP project. 
+  You can find the project ID in 
+  your `${CONFIG_FILE}` configuraiton file, as the value for the `project` key.
+
+  ```
+  export PROJECT=<your GCP project ID>
+  ```
+
+* The `${ZONE}` environment variable contains the GCP zone where your
+  Kubeflow resources are deployed.
+
+  ```
+  export ZONE=<your GCP zone>
+  ```
+
+* For further background about the above settings, see the guide to
+  [deploying Kubeflow with the CLI](/docs/gke/deploy/deploy-cli).
 
 ## Create a Cloud Filestore instance
 
@@ -31,7 +74,7 @@ use you can skip this section.
 Copy the Cloud Filestore deployment manager configs to the `gcp_config` directory:
 
 ```
-cd /<path-to-kubeflow-deployment>/${KFAPP}
+cd ${KF_DIR}
 cp .cache/${VERSION}/deployment/gke/deployment_manager_configs/gcfs.yaml \
    ./gcp_config/
 ```
@@ -49,9 +92,9 @@ Edit `gcfs.yaml` to match your desired configuration:
 Using [yq](https://github.com/kislyuk/yq):
 
 ```
-cd /<path-to-kubeflow-deployment>/${KFAPP}
+cd ${KF_DIR}
 . env.sh
-yq -r ".resources[0].properties.instanceId=\"${DEPLOYMENT_NAME}\"" gcp_config/gcfs.yaml > gcp_config/gcfs.yaml.new
+yq -r ".resources[0].properties.instanceId=\"${KF_NAME}\"" gcp_config/gcfs.yaml > gcp_config/gcfs.yaml.new
 mv gcp_config/gcfs.yaml.new gcp_config/gcfs.yaml
 ```
 
@@ -63,8 +106,8 @@ Apply the changes:
 -->
 
 ```
-cd /<path-to-kubeflow-deployment>/${KFAPP}/gcp_config
-gcloud --project=${PROJECT} deployment-manager deployments create ${KFAPP-NAME}-nfs --config=gcfs.yaml
+cd ${KF_DIR}/gcp_config
+gcloud --project=${PROJECT} deployment-manager deployments create ${KF_NAME}-nfs --config=gcfs.yaml
 ```
 
 If you get an error **legacy networks are not supported** follow the instructions

content/docs/gke/custom-domain.md

@@ -15,19 +15,19 @@ so, follow the guide to
 
 ## Using your own domain
 
-If you want to use your own domain instead of **${name}.endpoints.${project}.cloud.goog**, follow these instructions:
+If you want to use your own domain instead of **${KF_NAME}.endpoints.${PROJECT}.cloud.goog**, follow these instructions:
 
 1. Remove the `cloud-endpoints` component:
 
     ```
-    cd ${KFAPP}/kustomize
+    cd ${KF_DIR}/kustomize
     kubectl delete -f cloud-endpoints.yaml
     ```
 
 1. Set the domain for your ingress to be the fully qualified domain name:
 
     ```
-    cd ${KFAPP}/kustomize
+    cd ${KF_DIR}/kustomize
     gvim iap-ingress.yaml    # Or basic-auth-ingress.yaml
     ```
 
@@ -47,7 +47,7 @@ If you want to use your own domain instead of **${name}.endpoints.${project}.clo
 1. Get the address of the static IP address created:
 
     ```
-    IPNAME=${DEPLOYMENT_NAME}-ip
+    IPNAME=${KF_NAME}-ip
     gcloud --project=${PROJECT} compute addresses describe --global ${IPNAME}
     ```
 

content/docs/gke/customizing-gke.md

@@ -7,56 +7,109 @@ weight = 2
 This guide describes how to customize your deployment of Kubeflow on Google 
 Kubernetes Engine (GKE) in Google Cloud Platform (GCP).
 
+## Customizing Kubeflow before deployment
+
+The Kubeflow deployment process is divided into two steps, **build** and 
+**apply**, so that you can modify your configuration before deploying your 
+Kubeflow cluster.
+
+Follow the guide to [deploying Kubeflow on GCP](/docs/gke/deploy/deploy-cli/).
+When you reach the 
+[setup and deploy step](/docs/gke/deploy/deploy-cli/#set-up-and-deploy),
+**skip the `kfctl apply` command** and run the **`kfctl build`** command 
+instead, as  described in that step. Now you can edit the configuration files 
+before deploying Kubeflow.
+
+## Customizing an existing deployment
+
+You can also customize an existing Kubeflow deployment. In that case, this 
+guide assumes that you have already followed the guide to 
+[deploying Kubeflow on GCP](/docs/gke/deploy/deploy-cli/) and have deployed
+Kubeflow to a GKE cluster.
+
 ## Before you start
 
-This guide assumes you have already set up Kubeflow with GKE. If you haven't done
-so, follow the guide to [deploying Kubeflow on GCP](/docs/gke/deploy/).
+This guide assumes the following settings: 
 
-## Customizing Kubeflow
+* The `${KF_DIR}` environment variable contains the path to
+  your Kubeflow application directory, which holds your Kubeflow configuration 
+  files. For example, `/opt/my-kubeflow/`.
 
-You can use [kustomize](https://kustomize.io/) to customize Kubeflow.
+  ```
+  export KF_DIR=<path to your Kubeflow application directory>
+  ``` 
+
+* The `${CONFIG_FILE}` environment variable contains the path to your 
+  Kubeflow configuration file.
+
+  ```
+  export CONFIG_FILE=${KF_DIR}/kfctl_gcp_iap.yaml
+  ```
+
+    Or:
+
+  ```
+  export CONFIG_FILE=${KF_DIR}/kfctl_gcp_basic_auth.yaml
+  ```
+
+* The `${KF_NAME}` environment variable contains the name of your Kubeflow 
+  deployment. You can find the name in your
+  `${CONFIG_FILE}` configuration file, as the value for the `metadata.name` key.
+
+  ```
+  export KF_NAME=<the name of your Kubeflow deployment>
+  ```
+
+* The `${PROJECT}` environment variable contains the ID of your GCP project. 
+  You can find the project ID in your
+  `${CONFIG_FILE}` configuration file, as the value for the `project` key.
+
+  ```
+  export PROJECT=<your GCP project ID>
+  ```
 
-The deployment process is divided into two steps, **generate** and **apply**, so that you can
-modify your deployment before actually deploying.
+* For further background about the above settings, see the guide to
+  [deploying Kubeflow with the CLI](/docs/gke/deploy/deploy-cli).
 
-To customize GCP resources (such as your Kubernetes Engine cluster), you can modify the deployment manager configs in **${KFAPP}/gcp_config**.
+## Customizing GCP resources
 
-Many changes can be applied to an existing configuration in which case you can run:
+To customize GCP resources, such as your Kubernetes Engine cluster, you can 
+modify the Deployment Manager configuration settings in `${KF_DIR}/gcp_config`.
+
+After modifying your existing configuration, run the following command to apply
+the changes:
 
 ```
-cd ${KFAPP}
-kfctl apply platform
+cd ${KF_DIR}
+kfctl apply -V -f ${CONFIG_FILE}
 ```
 
-or using Deployment Manager directly:
+Alternatively, you can use Deployment Manager directly:
 
 ```
-cd ${KFAPP}/gcp_config
-gcloud deployment-manager --project=${PROJECT} deployments update ${DEPLOYMENT_NAME} --config=cluster-kubeflow.yaml
+cd ${KF_DIR}/gcp_config
+gcloud deployment-manager --project=${PROJECT} deployments update ${KF_NAME} --config=cluster-kubeflow.yaml
 ```
 
-  * **PROJECT** Name of your GCP project. You could find it in `${KFAPP}/app.yaml`.
-  * **DEPLOYMENT_NAME** Name of your Kubeflow app. You could also find it in `${KFAPP}/app.yaml`. 
-    In specific, `.metadata.name`
-
 Some changes (such as the VM service account for Kubernetes Engine) can only be set at creation time; in this case you need
 to tear down your deployment before recreating it:
 
 ```
-cd ${KFAPP}
-kfctl delete all
-kfctl apply all
+cd ${KF_DIR}
+kfctl delete -f ${CONFIG_FILE}
+kfctl apply -V -f ${CONFIG_FILE}
 ```
 
-To customize the Kubeflow resources running within the cluster you can modify the kustomize manifests in **${KFAPP}/kustomize**.
-For example, to modify settings for the Jupyter web app:
+## Customizing Kubernetes resources
 
-```
-cd ${KFAPP}/kustomize
-gvim jupyter-web-app.yaml
-```
+You can use [kustomize](https://kustomize.io/) to customize Kubeflow.
+To customize the Kubernetes resources running within the cluster, you can modify 
+the kustomize manifests in `${KF_DIR}/kustomize`.
 
-Find and replace the parameter values:
+For example, to modify settings for the Jupyter web app:
+
+1. Open `${KF_DIR}/kustomize/jupyter-web-app.yaml` in a text editor.
+1. Find and replace the parameter values:
 ```
 apiVersion: v1
 data:
@@ -74,30 +127,61 @@ metadata:
   namespace: kubeflow
   ```
 
-You can then redeploy using `kfctl`:
+1. Redeploy Kubeflow using kfctl:
 
-```
-cd ${KFAPP}
-kfctl apply k8s
-```
+  ```
+  cd ${KF_DIR}
+  kfctl apply -V -f ${CONFIG_FILE}
+  ```
+
+    Or use kubectl directly:
+  ```
+  cd ${KF_DIR}/kustomize
+  kubectl apply -f jupyter-web-app.yaml
+  ```
+
+## Common customizations
+
+<a id="gpu-config"></a>
+### Add GPU nodes to your cluster
+
+To add GPU accelerators to your Kubeflow cluster, you have the following
+options:
+
+* Pick a GCP zone that provides NVIDIA Tesla K80 Accelerators 
+  (`nvidia-tesla-k80`).
+* Or disable node-autoprovisioning in your Kubeflow cluster.
+* Or change your node-autoprovisioning configuration.
+
+To see which accelerators are available in each zone, run the following
+command:
 
-or using kubectl directly:
 ```
-cd ${KFAPP}/kustomize
-kubectl apply -f jupyter-web-app.yaml
+gcloud compute accelerator-types list
 ```
  
-## Common customizations
+To disable node-autoprovisioning, run `kfctl build` as described above.
+Then edit `${KF_DIR}/gcp_config/cluster-kubeflow.yaml` and set 
+[`enabled`](https://github.com/kubeflow/manifests/blob/4d2939d6c1a5fd862610382fde130cad33bfef75/gcp/deployment_manager_configs/cluster-kubeflow.yaml#L73) 
+to `false`:
 
-Add GPU nodes to your cluster:
+```
+    ...
+    gpu-type: nvidia-tesla-k80
+    autoprovisioning-config:
+      enabled: false
+    ...
+```
 
-  * Set gpu-pool-initialNodeCount [here](https://github.com/kubeflow/kubeflow/blob/{{< params "githubbranch" >}}/deployment/gke/deployment_manager_configs/cluster-kubeflow.yaml#L56).
+You must also set 
+[`gpu-pool-initialNodeCount`](https://github.com/kubeflow/manifests/blob/4d2939d6c1a5fd862610382fde130cad33bfef75/gcp/deployment_manager_configs/cluster-kubeflow.yaml#L58).
 
-Add Cloud TPUs to your cluster:
+### Add Cloud TPUs to your cluster
 
-  * Set `enable_tpu:true` [here](https://github.com/kubeflow/kubeflow/blob/{{< params "githubbranch" >}}/deployment/gke/deployment_manager_configs/cluster-kubeflow.yaml#L78).
+Set [`enable_tpu:true`](https://github.com/kubeflow/manifests/blob/4d2939d6c1a5fd862610382fde130cad33bfef75/gcp/deployment_manager_configs/cluster-kubeflow.yaml#L80)
+in `${KF_DIR}/gcp_config/cluster-kubeflow.yaml`.
 
-Add VMs with more CPUs or RAM:
+### Add VMs with more CPUs or RAM
 
   * Change the machineType.
   * There are two node pools:
@@ -105,7 +189,7 @@ Add VMs with more CPUs or RAM:
       * one for GPU machines [here](https://github.com/kubeflow/kubeflow/blob/{{< params "githubbranch" >}}/scripts/gke/deployment_manager_configs/cluster.jinja#L149).
   * When making changes to the node pools you also need to bump the pool-version [here](https://github.com/kubeflow/kubeflow/blob/{{< params "githubbranch" >}}/scripts/gke/deployment_manager_configs/cluster-kubeflow.yaml#L37) before you update the deployment.
 
-Add users to Kubeflow:
+### Add users to Kubeflow
 
   * To grant users access to Kubeflow, add the “IAP-secured Web App User” role on the [IAM page in the GCP console](https://console.cloud.google.com/iam-admin/iam). Make sure you are in the same project as your Kubeflow deployment.
 

content/docs/gke/deploy/delete-cli.md

@@ -7,26 +7,47 @@ weight = 6
 This page shows you how to use the CLI to delete a Kubeflow deployment on
 Google Cloud Platform (GCP).
 
+## Before you start
+
+This guide assumes the following settings: 
+
+* The `${KF_DIR}` environment variable contains the path to
+  your Kubeflow application directory, which holds your Kubeflow configuration 
+  files. For example, `/opt/my-kubeflow/`.
+
+  ```
+  export KF_DIR=<path to your Kubeflow application directory>
+  ``` 
+
+* The `${CONFIG_FILE}` environment variable contains the path to your 
+  Kubeflow configuration file.
+
+  ```
+  export CONFIG_FILE=${KF_DIR}/kfctl_gcp_iap.yaml
+  ```
+
+    Or:
+
+  ```
+  export CONFIG_FILE=${KF_DIR}/kfctl_gcp_basic_auth.yaml
+  ```
+
+For further background about the above settings, see the guide to
+[deploying Kubeflow with the CLI](/docs/gke/deploy/deploy-cli).
+
+## Deleting your deployment
+
 Run the following commands to delete your deployment and reclaim all GCP
 resources:
 
 ```
-cd ${KFAPP}
 # If you want to delete all the resources, including storage:
-kfctl delete all --delete_storage
+kfctl delete -f ${CONFIG_FILE} --delete_storage
+
 # If you want to preserve storage, which contains metadata and information
 # from Kubeflow Pipelines:
-kfctl delete all
+kfctl delete -f ${CONFIG_FILE}
 ```
-The environment variable `${KFAPP}` must contain the _name_ of the directory 
-that contains your Kubeflow configurations. This directory was created when you
-deployed Kubeflow.
-
-* The name of the directory is the same as the name of your Kubeflow deployment.
-  If you deployed Kubeflow [using the UI](/docs/gke/deploy/deploy-ui/), the 
-  value of `${KFAPP}` is the value of the **Deployment name** field on the UI.
-* If you deployed Kubeflow [using the CLI](/docs/gke/deploy/deploy-cli/), use 
-  the same value as you used when you ran `kfctl init`.
 
 You should consider preserving storage if you may want to relaunch
 Kubeflow in the future and restore the data from your 

content/docs/gke/deploy/deploy-cli.md

@@ -32,9 +32,21 @@ Before installing Kubeflow on the command line:
   access to sensitive data. Alternatively, you can use basic authentication 
   with a username and password.
 
-## Deploy Kubeflow
+<a id="prepare-environment"></a>
+## Prepare your environment
 
-Follow these steps to deploy Kubeflow:
+Follow these steps to download the kfctl binary for the Kubeflow CLI and set
+some handy environment variables:
+
+1. Download the kfctl {{% kf-latest-version %}} release from the
+  [Kubeflow releases 
+  page](https://github.com/kubeflow/kubeflow/releases/tag/{{% kf-latest-version %}}).
+
+1. Unpack the tar ball:
+
+    ```
+    tar -xvf kfctl_{{% kf-latest-version %}}_<platform>.tar.gz
+    ```
 
 1. Create user credentials. You only need to run this command once:
    
@@ -42,94 +54,152 @@ Follow these steps to deploy Kubeflow:
     gcloud auth application-default login
     ```
 
-1. Create environment variables for your access control services:
+1. Create environment variables to make the deployment process easier:
+
+    ```
+    # Set your GCP project ID and the zone where you want to create 
+    # the Kubeflow deployment:
+    export PROJECT=<your GCP project ID>
+    gcloud config set project ${PROJECT}
+    export ZONE=<your GCP zone>
+    gcloud config set compute/zone ${ZONE}
 
-    ```bash
-    # If using Cloud IAP, create environment variables from the
-    # OAuth client ID and secret that you obtained earlier:
+    # Use the following kfctl configuration file for authentication with 
+    # Cloud IAP (recommended):
+    export CONFIG_URI="{{% config-uri-gcp-iap %}}"
+
+    # If using Cloud IAP for authentication, create environment variables
+    # from the OAuth client ID and secret that you obtained earlier:
     export CLIENT_ID=<CLIENT_ID from OAuth page>
     export CLIENT_SECRET=<CLIENT_SECRET from OAuth page>
 
-    # If using basic authentication, create environment variables for
-    # username and password:
+    # Alternatively, use the following kfctl configuration if you want to use 
+    # basic authentication:
+    export CONFIG_URI="{{% config-uri-gcp-basic-auth %}}"
+
+    # If using basic authentication, create environment variables
+    # for username and password:
     export KUBEFLOW_USERNAME=<your username>
     export KUBEFLOW_PASSWORD=<your password>
+
+    # Set KF_NAME to the name of your Kubeflow deployment. You also use this
+    # value as directory name when creating your configuration directory. 
+    # See the detailed description in the text below this code snippet.
+    # For example, your deployment name can be 'my-kubeflow' or 'kf-test'.
+    export KF_NAME=<your choice of name for the Kubeflow deployment>
+
+    # Set the path to the base directory where you want to store one or more 
+    # Kubeflow deployments. For example, /opt/.
+    # Then set the Kubeflow application directory for this deployment.
+    export BASE_DIR=<path to a base directory>
+    export KF_DIR=${BASE_DIR}/${KF_NAME}
+
+    # The following command is optional. It adds the kfctl binary to your path.
+    # If you don't add kfctl to your path, you must use the full path
+    # each time you run kfctl.
+    export PATH=$PATH:<path to your kfctl file>
     ```
 
-1. Download a `kfctl` release from the 
-  [Kubeflow releases page](https://github.com/kubeflow/kubeflow/releases/).
+Notes:
 
-1. Unpack the tar ball:
+* **${PROJECT}** - The project ID of the GCP project where you want Kubeflow 
+  deployed.
+* **${ZONE}** - The GCP zone where you want to create the Kubeflow deployment.
+  You can see a list of zones in the 
+  [Compute Engine documentation](https://cloud.google.com/compute/docs/regions-zones/#available).
+  If you plan to use accelerators, you must choose a zone that supports the
+  type you want. See the guide to 
+  [customizing your Kubeflow deployment](/docs/gke/customizing-gke/#gpu-config).
+* **${CONFIG_URI}** - The GitHub address of the configuration YAML file that
+  you want to use to deploy Kubeflow. For GCP deployments, the following
+  configurations are available:
+
+  * `{{% config-uri-gcp-iap %}}` 
+  * `{{% config-uri-gcp-basic-auth %}}`
+
+    When you run `kfctl apply` or `kfctl build` (see the next step), kfctl creates
+    a local version of the configuration YAML file which you can further
+    customize if necessary.
+
+* **${KF_NAME}** - The name of your Kubeflow deployment.
+  If you want a custom deployment name, specify that name here.
+  For example,  `my-kubeflow` or `kf-test`.
+  The value of KF_NAME must consist of lower case alphanumeric characters or
+  '-', and must start and end with an alphanumeric character.
+  The value of this variable cannot be greater than 25 characters. It must
+  contain just a name, not a directory path.
+  You also use this value as directory name when creating the directory where 
+  your Kubeflow  configurations are stored, that is, the Kubeflow application 
+  directory. 
+  
+* **${KF_DIR}** - The full path to your Kubeflow application directory.
+
+<a id="set-up-and-deploy"></a>
+## Set up and deploy Kubeflow
+
+To set up and deploy Kubeflow using the **default settings**,
+run the `kfctl apply` command:
+
+```
+mkdir -p ${KF_DIR}
+cd ${KF_DIR}
+kfctl apply -V -f ${CONFIG_URI}
+```
+
+## Alternatively, set up your configuration for later deployment
+
+If you want to customize your configuration before deploying Kubeflow, you can 
+set up your configuration files first, then edit the configuration, then
+deploy Kubeflow:
+
+1. Run the `kfctl build` command to set up your configuration:
 
   ```
-    tar -xvf kfctl_<release tag>_<platform>.tar.gz
+  mkdir -p ${KF_DIR}
+  cd ${KF_DIR}
+  kfctl build -V -f ${CONFIG_URI}
   ```
 
-1. Run the following commands to set up and deploy Kubeflow. The code below
-  includes an optional command to add the binary `kfctl` to your path. If you 
-  don't add the binary to your path, you must use the full path to the `kfctl` 
-  binary each time you run it.
+1. Edit the configuration files, as described in the guide to
+  [customizing your Kubeflow deployment](/docs/gke/customizing-gke/).
 
-    ```bash
-    # The following command is optional, to make kfctl binary easier to use.
-    export PATH=$PATH:<path to your kfctl file>
+1. Set an environment variable for your local configuration file:
 
-    # Set KFAPP to the name of your Kubeflow application. See detailed
-    # description in the text below this code snippet.
-    # For example,  'kubeflow-test' or 'kfw-test'.
-    export KFAPP=<your choice of application directory name>
+  ```
+  export CONFIG_FILE=${KF_DIR}/kfctl_gcp_iap.yaml
+  ```
 
-    export ZONE=<your target GCP zone> # where the deployment will be created
-    export PROJECT=<your GCP project ID>
+    Or:
 
-    # Run the following commands for the default installation which uses Cloud IAP:
-    export CONFIG="{{% config-uri-gcp-iap %}}"
-    kfctl init ${KFAPP} --project=${PROJECT} --config=${CONFIG} -V
-    # Alternatively, run these commands if you want to use basic authentication:
-    export CONFIG="{{% config-uri-gcp-basic-auth %}}"
-    kfctl init ${KFAPP} --project=${PROJECT} --config=${CONFIG} -V --use_basic_auth
-
-    cd ${KFAPP}
-    kfctl generate all -V --zone ${ZONE}
-    kfctl apply all -V
-    ```
-   * **${KFAPP}** - the _name_ of a directory where you want Kubeflow 
-     configurations to be stored. This directory is created when you run
-     `kfctl init`. If you want a custom deployment name, specify that name here.
-     The value of this variable becomes the name of your deployment.
-     The value of KFAPP must consist of lower case alphanumeric characters or
-     '-', and must start and end with an alphanumeric character.
-     For example,  'kubeflow-test' or 'kfw-test'.
-     The value of this variable cannot be greater than 25 characters. It must
-     contain just the directory name, not the full path to the directory.
-     The content of this directory is described in the next section.
-   * **${PROJECT}** - the project ID of the GCP project where you want Kubeflow 
-     deployed.
-   * **${ZONE}** - You can see a list of zones [here](https://cloud.google.com/compute/docs/regions-zones/#available).
-     If you plan to use accelerators, make sure to pick a zone that supports the type you want.
-   * When you run `kfctl init` you need to choose to use either IAP or basic 
-     authentication, as described above.
-   * `kfctl generate all` attempts to fetch your email address from your 
-     credential. If it can't find a valid email address, you need to pass a
-     valid email address with flag `--email <your email address>`. This email 
-     address becomes an administrator in the configuration of your Kubeflow 
-     deployment.
+  ```
+  export CONFIG_FILE=${KF_DIR}/kfctl_gcp_basic_auth.yaml
+  ```
+
+1. Run the `kfctl apply` command to deploy Kubeflow:
+
+  ```
+  kfctl apply -V -f ${CONFIG_FILE}
+  ```
 
+## Check your deployment
+
+Follow these steps to verify the deployment:
 
 1. The deployment process creates a separate deployment for your data storage. 
-   After running `kfctl apply` you should notice two new [deployments](https://console.cloud.google.com/dm/deployments):
-   * **{KFAPP}-storage**: This deployment has persistent volumes for your
+   After running `kfctl apply` you should notice two new 
+   [deployments](https://console.cloud.google.com/dm/deployments):
+   * **{KF_NAME}-storage**: This deployment has persistent volumes for your
      pipelines.
-   * **{KFAPP}**: This deployment has all the components of Kubeflow, including 
+   * **{KF_NAME}**: This deployment has all the components of Kubeflow, including 
      a [GKE cluster](https://console.cloud.google.com/kubernetes/list) 
-     named **${KFAPP}** with Kubeflow installed.
+     named **${KF_NAME}** with Kubeflow installed.
 
 1. When the deployment finishes, check the resources installed in the namespace
    `kubeflow` in your new cluster.  To do this from the command line, first set 
    your `kubectl` credentials to point to the new cluster:
 
     ```
-    gcloud container clusters get-credentials ${KFAPP} --zone ${ZONE} --project ${PROJECT}
+    gcloud container clusters get-credentials ${KF_NAME} --zone ${ZONE} --project ${PROJECT}
     ```
 
     Then see what's installed in the `kubeflow` namespace of your GKE cluster:
@@ -138,80 +208,149 @@ Follow these steps to deploy Kubeflow:
     kubectl -n kubeflow get all
     ```
 
-1. Access the Kubeflow central dashboard at the following URI when it becomes
-  available:
+## Access the Kubeflow user interface (UI)
+
+Follow these steps to access the Kubeflow central dashboard:
+
+1. Enter the following URI into your browser address bar. It can take 20
+  minutes for the URI to become available:
 
   ```
-    https://<KFAPP>.endpoints.<project-id>.cloud.goog/
+  https://<KF_NAME>.endpoints.<project-id>.cloud.goog/
   ```
-   * It can take 20 minutes for the URI to become available.
+
+    You can run the following command to get the URI for your deployment:
+
+  ```
+  kubectl -n istio-system get ingress
+  NAME            HOSTS                                                      ADDRESS         PORTS   AGE
+  envoy-ingress   your-kubeflow-name.endpoints.your-gcp-project.cloud.goog   34.102.232.34   80      5d13h
+  ```
+
+    The following command sets an environment variable named `HOST` to the URI:
+
+  ```
+  export HOST=$(kubectl -n istio-system get ingress envoy-ingress -o=jsonpath={.spec.rules[0].host})
+  ```
+
+1. Follow the instructions on the UI to create a namespace. See the guide to 
+  [creation of profiles](/docs/other-guides/multi-user-overview/#automatic-creation-of-profiles).
+
+Notes:
+
+* It can take 20 minutes for the URI to become available.
   Kubeflow needs to provision a signed SSL certificate and register a DNS 
   name.
-   * If you own/manage the domain or a subdomain with 
+* If you own or manage the domain or a subdomain with 
   [Cloud DNS](https://cloud.google.com/dns/docs/)
   then you can configure this process to be much faster.
   See [kubeflow/kubeflow#731](https://github.com/kubeflow/kubeflow/issues/731).
 
-1. We recommend that you check in the contents of your **${KFAPP}** directory
-  into source control.
-
 ## Understanding the deployment process
 
-The `kfctl` deployment process includes by the following commands:
+This section gives you more details about the kfctl configuration and 
+deployment process, so that you can customize your Kubeflow deployment if
+necessary.
+
+### kfctl process and configuration
+
+The kfctl deployment process includes the following commands:
+
+* `kfctl build` - (Optional) Creates configuration files defining the various 
+  resources in your deployment. You only need to run `kfctl build` if you want 
+  to edit the resources before running `kfctl apply`. See the guide to
+  [customizing your Kubeflow deployment](/docs/gke/customizing-gke/).
+* `kfctl apply` - Creates or updates the resources.
+* `kfctl delete` - Deletes the resources.
+
+The kfctl deployment process applies default values to certain properties
+as follows:
+
+* **Email address:** kfctl attempts to fetch your email address from your
+  Cloud SDK configuration. You can run `gcloud config list` to see the default 
+  email address, which the command output lists as the **account**.
+  If kfctl can't find a valid email address, you must use the
+  flag `--email <your email address>` to pass a valid email address. This email 
+  address becomes an administrator in the configuration of your Kubeflow 
+  deployment.
+
+* **GCP project ID:** kfctl attempts to fetch your project ID from your
+  Cloud SDK configuration. You can run `gcloud config list` to see your 
+  active project ID.
+
+* **GCP zone:** kfctl attempts to fetch the zone from your Cloud SDK
+  configuration. You can run `gcloud config list` to see your active zone.
 
-* **init** - performs a one-time setup.
-* **generate** - creates configuration files defining the various resources.
-* **apply** - creates or updates the resources.
-* **delete** - deletes the resources.
+* **Kubeflow deployment name:** kfctl defaults to the name of the directory
+  where you run the `kfctl build` or `kfctl apply` command.
 
-With the exception of `init`, all commands take an argument which describes the
-set of resources to apply the command to. This argument can be one of the
-following:
+You can also explicitly set the following values in your `${CONFIG_FILE}`
+configuration file:
 
-* **platform** - all GCP resources; that is, anything that doesn't run on 
-  Kubernetes.
-* **k8s** - all resources that run on Kubernetes.
-* **all** - all GCP and Kubernetes resources.
+* Kubeflow deployment name
+* GCP project
+* GCP zone
+* Email address
 
-### App layout
 
-Your Kubeflow app directory **${KFAPP}** contains the following files and directories:
+The following snippet shows you how to set values in the configuration file
+using [yq](https://github.com/mikefarah/yq/releases):
 
-* **app.yaml** defines configurations related to your Kubeflow deployment.
+```
+yq w -i ${CONFIG_FILE} spec.plugins[0].spec.project ${PROJECT}
+yq w -i ${CONFIG_FILE} spec.plugins[0].spec.zone ${ZONE}
+yq w -i ${CONFIG_FILE} metadata.name ${KF_NAME}
+```
 
-  * The values are set when you run `kfctl init`.
-  * The values are snapshotted inside **app.yaml** to make your app 
-    self contained.
+### Application layout
+
+Your Kubeflow application directory **${KF_DIR}** contains the following files and 
+directories:
+
+* **${CONFIG_FILE}** is a YAML file that defines configurations related to your 
+  Kubeflow deployment.
+
+  * This file is a copy of the GitHub-based configuration YAML file that
+    you used when deploying Kubeflow: 
+      * either `{{% config-uri-gcp-iap %}}`
+      * or `{{% config-uri-gcp-basic-auth %}}`.
+  * When you run `kfctl apply` or `kfctl build`, kfctl creates
+    a local version of the configuration file, **${CONFIG_FILE}**,
+    which you can further customize if necessary.
 
 * **gcp_config** is a directory that contains 
   [Deployment Manager configuration files](https://cloud.google.com/deployment-manager/docs/configuration/) 
   defining your GCP infrastructure.
 
-  * The directory is created when you run `kfctl generate platform`.
+  * The directory is created when you run `kfctl build` or `kfctl apply`.
   * You can modify these configurations to customize your GCP infrastructure.
+    After modifying a configuration, run `kfctl apply` again.
 
 * **kustomize** is a directory that contains the kustomize packages for Kubeflow 
   applications. See 
   [how Kubeflow uses kustomize](/docs/other-guides/kustomize/).
 
-  * The directory is created when you run `kfctl generate`.
+  * The directory is created when you run `kfctl build` or `kfctl apply`.
   * You can customize the Kubernetes resources by modifying the manifests and 
     running `kfctl apply` again.
 
+We recommend that you check in the contents of your **${KF_DIR}** directory
+into source control.
+
 ### GCP service accounts
 
-Creating a deployment using `kfctl` creates three service accounts in your 
-GCP project. These service accounts are created using the [principle of least 
+The kfctl deployment process creates three service accounts in your 
+GCP project. These service accounts follow the [principle of least 
 privilege](https://en.wikipedia.org/wiki/Principle_of_least_privilege). 
-The three service accounts are:
+The service accounts are:
 
-* `${KFAPP}-admin` is used for some admin tasks like configuring the load 
+* `${KF_NAME}-admin` is used for some admin tasks like configuring the load 
   balancers. The principle is that this account is needed to deploy Kubeflow but 
   not needed to actually run jobs.
-* `${KFAPP}-user` is intended to be used by training jobs and models to access 
+* `${KF_NAME}-user` is intended to be used by training jobs and models to access 
   GCP resources (Cloud Storage, BigQuery, etc.). This account has a much smaller 
   set of privileges compared to `admin`.
-* `${KFAPP}-vm` is used only for the virtual machine (VM) service account. This
+* `${KF_NAME}-vm` is used only for the virtual machine (VM) service account. This
   account has the minimal permissions needed to send metrics and logs to 
   [Stackdriver](https://cloud.google.com/stackdriver/).
 
@@ -221,12 +360,12 @@ The three service accounts are:
   [end-to-end MNIST tutorial](/docs/gke/gcp-e2e/) or the
   [GitHub issue summarization 
   example](https://github.com/kubeflow/examples/tree/master/github_issue_summarization).
-* See how to [delete](/docs/gke/deploy/delete-cli) your Kubeflow deployment 
+* See how to [delete](/docs/gke/deploy/delete-cli/) your Kubeflow deployment 
   using the CLI.
-* See how to [customize](/docs/gke/customizing-gke) your Kubeflow 
+* See how to [customize](/docs/gke/customizing-gke/) your Kubeflow 
   deployment.
 * See how to [upgrade Kubeflow](/docs/upgrading/upgrade/) and how to 
   [upgrade or reinstall a Kubeflow Pipelines 
   deployment](/docs/pipelines/upgrade/).
-* [Troubleshoot](/docs/gke/troubleshooting-gke) any issues you may
+* [Troubleshoot](/docs/gke/troubleshooting-gke/) any issues you may
   find.

content/docs/gke/deploy/monitor-iap-setup.md

@@ -133,17 +133,27 @@ problems:
     recreating and redeploying Kubeflow with a different
     name. 
 
-    For example if you originally ran the following `kfctl init` command:
+    For example if you originally ran the following commands to deploy Kubeflow:
 
     ```
-    kfctl init myapp --project=myproject --config=myconfig -V
+    export KF_NAME=my-app
+    export BASE_DIR=<path to a base directory>
+    export KF_DIR=${BASE_DIR}/${KF_NAME}
+    mkdir -p ${KF_DIR}
+    cd ${KF_DIR}
+    kfctl apply -V -f ${CONFIG_FILE}
     ```
 
-    Then rerun `kfctl init` with a different name that you haven't used
+    Then rerun the commands with a different name that you haven't used
     before:
 
     ```
-    kfctl init myapp-unique --project=myproject --config=myconfig -V
+    export KF_NAME=my-app-unique
+    export BASE_DIR=<path to a base directory>
+    export KF_DIR=${BASE_DIR}/${KF_NAME}
+    mkdir -p ${KF_DIR}
+    cd ${KF_DIR}
+    kfctl apply -V -f ${CONFIG_FILE}
     ```
 
 1. Wait for the load balancer to report the back ends as healthy:

content/docs/gke/private-clusters.md

@@ -231,60 +231,15 @@ export PROJECT_NUMBER=$(gcloud projects describe ${PROJECT} --format='value(proj
 
       * You can use the Cloud console to monitor your GCB job.
 
+1. Follow the guide to [deploying Kubeflow on GCP](/docs/gke/deploy/deploy-cli/).
+  When you reach the 
+  [setup and deploy step](/docs/gke/deploy/deploy-cli/#set-up-and-deploy), 
+  **skip the `kfctl apply` command** and run the **`kfctl build`** command 
+  instead, as described in that step. Now you can edit the configuration files
+  before deploying Kubeflow. Retain the environment variables that you set
+  during the setup, including `${KF_NAME}`, `${KF_DIR}`, and `${CONFIG_FILE}`.
 
-1. Follow the [instructions](https://www.kubeflow.org/docs/gke/deploy/oauth-setup/) for creating an OAuth client
-
-1. Create environment variables for IAP OAuth access
-
-    ```bash
-     export CLIENT_ID=<CLIENT_ID from OAuth page>
-     export CLIENT_SECRET=<CLIENT_SECRET from OAuth page>
-    ```
-
-1. Download a `kfctl` release from the 
-  [Kubeflow releases page](https://github.com/kubeflow/kubeflow/releases/).
-
-1. Unpack the tar ball:
-
-    ```
-    tar -xvf kfctl_<release tag>_<platform>.tar.gz
-    ```
-   
-   * **Optional** Add the kfctl binary to your path. 
-   * If you don't add the kfctl binary to your path then in all subsequent
-     steps you will need to replace `kfctl` with the full path to the binary.
-
-1. Initialize the directory containing your Kubeflow deployment config files
-    
-    ```bash
-    export PROJECT=<your GCP project ID>
-    export KFAPP=<your choice of application directory name>
-    # Run the following commands for the default installation which uses Cloud IAP:
-    export CONFIG="{{% config-uri-gcp-iap %}}"
-    kfctl init ${KFAPP} --project=${PROJECT} --config=${CONFIG} -V
-    # Alternatively, run these commands if you want to use basic authentication:
-    export CONFIG="{{% config-uri-gcp-basic-auth %}}"
-    kfctl init ${KFAPP} --project=${PROJECT} --config=${CONFIG} -V --use_basic_auth
-
-    cd ${KFAPP}
-    kfctl generate all -V
-    ```
-   * **${KFAPP}** - the _name_ of a directory where you want Kubeflow 
-     configurations to be stored. This directory is created when you run
-     `kfctl init`. If you want a custom deployment name, specify that name here.
-     The value of this variable becomes the name of your deployment.
-     The value of this variable cannot be greater than 25 characters. It must
-     contain just the directory name, not the full path to the directory.
-     The content of this directory is described in the next section.
-   * **${PROJECT}** - the ID of the GCP project where you want Kubeflow 
-     deployed.
-   * `kfctl generate all` attempts to fetch your email address from your 
-     credential. If it can't find a valid email address, you need to pass a
-     valid email address with flag `--email <your email address>`. This email 
-     address becomes an administrator in the configuration of your Kubeflow 
-     deployment.
-
-1. Enable private clusters by editing `${KFAPP}/gcp_configs/cluster-kubeflow.yaml` and updating the following two parameters:
+1. Enable private clusters by editing `${KF_DIR}/gcp_config/cluster-kubeflow.yaml` and updating the following two parameters:
 
     ```
     privatecluster: true
@@ -293,14 +248,14 @@ export PROJECT_NUMBER=$(gcloud projects describe ${PROJECT} --format='value(proj
 1. Remove components which are not useful in private clusters:
 
     ```
-    cd ${KFAPP}/kustomize
+    cd ${KF_DIR}/kustomize
     kubectl delete -f cert-manager.yaml
     ```
 1. Create the deployment:
 
     ```
-    cd ${KFAPP}
-    kfctl apply platform
+    cd ${KF_DIR}
+    kfctl apply -V -f ${CONFIG_FILE}
     ```
 
       * If you get an error **legacy networks not supported**, follow the 
@@ -309,11 +264,11 @@ export PROJECT_NUMBER=$(gcloud projects describe ${PROJECT} --format='value(proj
         * You will need to manually create the network as a work around for [kubeflow/kubeflow#3071](https://github.com/kubeflow/kubeflow/issues/3071)
 
             ```
-        cd ${KFAPP}/gcp_configs
-        gcloud --project=${PROJECT} deployment-manager deployments create ${KFAPP}-network --config=network.yaml
+            cd ${KF_DIR}/gcp_config
+            gcloud --project=${PROJECT} deployment-manager deployments create ${KF_NAME}-network --config=network.yaml
             ```
 
-     * Then edit **gcp_config/cluster.jinja** to add a field **network** in your cluster
+        * Then edit `${KF_DIR}/gcp_config/cluster.jinja` to add a field **network** in your cluster
         
             ```
             cluster:
@@ -327,12 +282,12 @@ export PROJECT_NUMBER=$(gcloud projects describe ${PROJECT} --format='value(proj
             gcloud --project=${PROJECT} compute networks list
             ``` 
 
-       * The name will contain the value ${KFAPP}
+          * The name will contain the value ${KF_NAME}
 
 1. Update iap-ingress component parameters:
 
     ```
-    cd ${KFAPP}/kustomize
+    cd ${KF_DIR}/kustomize
     gvim basic-auth-ingress.yaml  # Or iap-ingress.yaml if you are using IAP
     ```
 
@@ -360,7 +315,7 @@ export PROJECT_NUMBER=$(gcloud projects describe ${PROJECT} --format='value(proj
             you can get it by running
 
             ```
-        cd ${KFAPP}/kustomize
+            cd ${KF_DIR}/kustomize
             grep hostname: basic-auth-ingress.yaml
             ```
 
@@ -380,8 +335,8 @@ export PROJECT_NUMBER=$(gcloud projects describe ${PROJECT} --format='value(proj
 1. Apply all the Kubernetes resources:
 
     ```
-    cd ${KFAPP}
-    kfctl apply k8s
+    cd ${KF_DIR}
+    kfctl apply -V -f ${CONFIG_FILE}
     ```
 1. Wait for Kubeflow to become accessible and then access it at
 

content/docs/gke/troubleshooting-gke.md

@@ -15,6 +15,55 @@ This guide covers troubleshooting specifically for
 For more help, try the 
 [general Kubeflow troubleshooting guide](/docs/other-guides/troubleshooting).
 
+This guide assumes the following settings: 
+
+* The `${KF_DIR}` environment variable contains the path to
+  your Kubeflow application directory, which holds your Kubeflow configuration 
+  files. For example, `/opt/my-kubeflow/`.
+
+  ```
+  export KF_DIR=<path to your Kubeflow application directory>
+  ``` 
+
+* The `${CONFIG_FILE}` environment variable contains the path to your 
+  Kubeflow configuration file.
+
+  ```
+  export CONFIG_FILE=${KF_DIR}/kfctl_gcp_iap.yaml
+  ```
+
+    Or:
+
+  ```
+  export CONFIG_FILE=${KF_DIR}/kfctl_gcp_basic_auth.yaml
+  ```
+
+* The `${KF_NAME}` environment variable contains the name of your Kubeflow 
+  deployment. You can find the name in your `${CONFIG_FILE}` 
+  configuration file, as the value for the `metadata.name` key.
+
+  ```
+  export KF_NAME=<the name of your Kubeflow deployment>
+  ```
+
+* The `${PROJECT}` environment variable contains the ID of your GCP project. 
+  You can find the project ID in 
+  your `${CONFIG_FILE}` configuration file, as the value for the `project` key.
+
+  ```
+  export PROJECT=<your GCP project ID>
+  ```
+
+* The `${ZONE}` environment variable contains the GCP zone where your
+  Kubeflow resources are deployed.
+
+  ```
+  export ZONE=<your GCP zone>
+  ```
+
+* For further background about the above settings, see the guide to
+  [deploying Kubeflow with the CLI](/docs/gke/deploy/deploy-cli).
+
 ## Troubleshooting kubeflow deployment on GCP
 
 Here are some tips for troubleshooting Cloud IAP.
@@ -43,7 +92,7 @@ the cluster. This section assumes
 you are using [Cloud Endpoints](https://cloud.google.com/endpoints/) and a DNS name of the following pattern
 
 ```
-https://${DEPLOYMENT_NAME}.endpoints.${PROJECT}.cloud.goog
+https://${KF_NAME}.endpoints.${PROJECT}.cloud.goog
 ```
 
 Symptoms:
@@ -52,11 +101,11 @@ Symptoms:
   * nslookup for the domain name doesn't return the IP address associated with the ingress
 
     ```
-    nslookup ${DEPLOYMENT_NAME}.endpoints.${PROJECT}.cloud.goog
+    nslookup ${KF_NAME}.endpoints.${PROJECT}.cloud.goog
     Server:   127.0.0.1
     Address:  127.0.0.1#53
 
-    ** server can't find ${DEPLOYMENT_NAME}.endpoints.${PROJECT}.cloud.goog: NXDOMAIN
+    ** server can't find ${KF_NAME}.endpoints.${PROJECT}.cloud.goog: NXDOMAIN
     ```
 
 Troubleshooting
@@ -64,8 +113,8 @@ Troubleshooting
 1. Check the `cloudendpoints` resource
 
    ```
-   kubectl get cloudendpoints -o yaml ${DEPLOYMENT_NAME}
-   kubectl describe cloudendpoints ${DEPLOYMENT_NAME}
+   kubectl get cloudendpoints -o yaml ${KF_NAME}
+   kubectl describe cloudendpoints ${KF_NAME}
    ```
 
    * Check if there are errors indicating problems creating the endpoint
@@ -329,7 +378,7 @@ ERROR: (gcloud.deployment-manager.deployments.update) Error in Operation [operat
 To fix this we can create a new network:
 
 ```
-cd ${KFAPP}
+cd ${KF_DIR}
 cp .cache/master/deployment/gke/deployment_manager_configs/network.* \
    ./gcp_config/
 ```
@@ -341,8 +390,8 @@ Edit `gcfs.yaml` to use the name of the newly created network.
 Apply the changes.
 
 ```
-cd ${KFAPP}
-kfctl apply platform
+cd ${KF_DIR}
+kfctl apply -V -f ${CONFIG}
 ```
 
 ## CPU platform unavailable in requested zone

layouts/shortcodes/config-uri-gcp-basic-auth.html

-https://raw.githubusercontent.com/kubeflow/kubeflow/cfb336b7/bootstrap/config/kfctl_gcp_basic_auth.0.6.2.yaml
\ No newline at end of file
+https://raw.githubusercontent.com/kubeflow/manifests/v0.7-branch/kfdef/kfctl_gcp_basic_auth.0.7.0.yaml
\ No newline at end of file

layouts/shortcodes/config-uri-gcp-iap.html

-https://raw.githubusercontent.com/kubeflow/kubeflow/cfb336b7/bootstrap/config/kfctl_gcp_iap.0.6.2.yaml
\ No newline at end of file
+https://raw.githubusercontent.com/kubeflow/manifests/v0.7-branch/kfdef/kfctl_gcp_iap.0.7.0.yaml
\ No newline at end of file

layouts/shortcodes/kf-latest-version.html

-v0.6.2
\ No newline at end of file
+v0.7.0-rc.5
\ No newline at end of file