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Refactoring the left-hand navigation panel. (#406)

* In progress: Refactoring the left-hand navigation panel.

* Added .description to section index pages.

* Removed the redundant Components Overview as the new index page of the components section does a better job.

* Added redirects for the files I've moved/deleted.

* Fixed the URLs in all doc links.
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sarahmaddox authored and k8s-ci-robot committed Jan 18, 2019
1 parent fe236ea commit 8a79c998c91d42bfe8cf666fa69c60a366fce676
Showing with 70 additions and 74 deletions.
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@@ -132,7 +132,7 @@ A `weight` property in the _front matter_ of each page determines the position
of the page relative to the others in the same directory. The lower the weight,
the earlier the page appears in the section. A weight of 1 appears before a
a weight of 2, and so on. For example, see the front matter of the
[requirements](https://github.com/kubeflow/website/blob/master/content/docs/guides/requirements.md)
[requirements](https://github.com/kubeflow/website/blob/master/content/docs/started/requirements.md)
page in the guides section. The page front matter looks like this:

```
@@ -12,4 +12,8 @@
/blog/kaggle_on_kubeflow/ https://medium.com/kubeflow/kaggle-on-kubeflow-185a29e27c53
/blog/announcing_kubeflow_0.2/ https://medium.com/kubeflow/kubeflow-0-2-offers-new-components-and-simplified-setup-735e4c56988d

/docs/guides/pipelines/deploy-pipelines-service/ /docs/guides/pipelines/pipelines-quickstart/
/docs/guides/components/components /docs/components/
/docs/guides/pipelines/deploy-pipelines-service/ /docs/pipelines/pipelines-quickstart/

# Removed the "guides" section from the doc URLs.
/docs/guides/* /docs/:splat
@@ -1,5 +1,5 @@
+++
title = "Components of Kubeflow"
description = "Logical components that make up Kubeflow"
weight = 2
weight = 7
+++
@@ -6,7 +6,7 @@ weight = 10

## Bringing up a Jupyter Notebook

1. To connect to Jupyter follow the [instructions](/docs/guides/accessing-uis)
1. To connect to Jupyter follow the [instructions](/docs/other-guides/accessing-uis)
to access the Kubeflow UI. From there you will be able to navigate to JupyterHub
![JupyterHub Link](/docs/images/jupyterlink.png)
1. Sign in
@@ -77,7 +77,7 @@ ks apply default

## Upgrading ksonnet

See the guide to [upgrading Kubeflow](/docs/guides/upgrade/).
See the guide to [upgrading Kubeflow](/docs/other-guides/upgrade/).

## Why Kubeflow uses ksonnet

@@ -17,5 +17,5 @@ The Kubeflow Pipelines platform has the following goals:
cobble together end-to-end solutions, without having to rebuild each time.

Read more in the
[pipelines section](/docs/guides/pipelines/pipelines-overview)
[pipelines section](/docs/pipelines/pipelines-overview)
of the documentation.
@@ -7,7 +7,7 @@ This guide walks you through serving a PyTorch trained model in Kubeflow.

## Serving a model

We use [seldon-core](https://github.com/SeldonIO/seldon-core) component deployed following [these](/docs/guides/components/seldon/) instructions to serve the model.
We use [seldon-core](https://github.com/SeldonIO/seldon-core) component deployed following [these](/docs/components/seldon/) instructions to serve the model.

See also this [Example module](https://github.com/kubeflow/examples/blob/master/pytorch_mnist/serving/seldon-wrapper/mnistddpserving.py) which contains the code to wrap the model with Seldon.

@@ -153,8 +153,8 @@ python iap_request.py https://YOUR_HOST/tfserving/models/mnist IAP_CLIENT_ID --i

## Telemetry and Rolling out model using Istio

Please look at the [Istio guide](/docs/guides/components/istio/).
Please look at the [Istio guide](/docs/components/istio/).

## Logs and metrics with Stackdriver
See [here](/docs/guides/monitoring/) for instructions to get logs and metrics
See [here](/docs/other-guides/monitoring/) for instructions to get logs and metrics
using Stackdriver.
@@ -238,7 +238,7 @@ The TFJob dashboard is available at `<path>/tfjobs/ui/`. Specifically:
http://localhost:8080/tfjobs/ui/
```

See more details about [accessing the Kubeflow UIs](/docs/guides/accessing-uis).
See more details about [accessing the Kubeflow UIs](/docs/other-guides/accessing-uis).

## Using GPUs

@@ -577,9 +577,9 @@ further analysis.

### Stackdriver on GKE

See [here](/docs/guides/monitoring/) for instructions to get logs using Stackdriver.
See [here](/docs/other-guides/monitoring/) for instructions to get logs using Stackdriver.

As described [here](https://www.kubeflow.org/docs/guides/monitoring/#filter-with-labels) its possible
As described [here](https://www.kubeflow.org/docs/other-guides/monitoring/#filter-with-labels) its possible
to fetch the logs for a particular replica based on pod labels.

Using the Stackdriver UI you can use a query like
@@ -685,4 +685,4 @@ Events:
in the previous section.

## More information
* See how to [run a job with gang-scheduling](/docs/guides/job-scheduling).
* See how to [run a job with gang-scheduling](/docs/other-guides/job-scheduling).
@@ -1,5 +1,5 @@
+++
title = "Kubeflow on GKE"
description = "Running Kubeflow on Kubernetes Engine and GCP"
weight = 4
weight = 5
+++
@@ -57,7 +57,7 @@ ${KUBEFLOW_SRC}/scripts/kfctl.sh apply platform
```

If you get an error **legacy networks are not supported** follow the instructions
in the [troubleshooting guide](/docs/guides/troubleshooting).
in the [troubleshooting guide](/docs/other-guides/troubleshooting).

## Configure Kubeflow to mount the Cloud Filestore volume

@@ -104,5 +104,5 @@ For more information please refer to the [Deployment Manager docs](https://cloud
## More customizations

Refer to the navigation panel on the left of these docs for more customizations,
including [using your own domain](/docs/guides/gke/custom-domain),
[setting up Cloud Filestore](/docs/guides/gke/cloud-filestore), and more.
including [using your own domain](/docs/gke/custom-domain),
[setting up Cloud Filestore](/docs/gke/cloud-filestore), and more.
@@ -207,7 +207,7 @@ ksonnet components as standard Kubernetes YAML files with `ks show`, or you can
deploy (_apply_) the components directly to the cluster with `ks apply`.

Make sure you have the version of ksonnet specified in the
[Kubeflow requirements](/docs/guides/requirements).
[Kubeflow requirements](/docs/started/requirements).

Follow the steps below to install ksonnet:

@@ -1029,10 +1029,10 @@ gsutil rm -r gs://${BUCKET_NAME}
[kubeflow-core]: https://github.com/kubeflow/kubeflow/tree/master/kubeflow/core
[tf-job-prototype]: https://github.com/kubeflow/kubeflow/blob/master/kubeflow/examples/prototypes/tf-job-simple.jsonnet
[tf-serving-prototype]: https://github.com/kubeflow/kubeflow/tree/master/kubeflow/tf-serving
[tf-training]: /docs/guides/components/tftraining/
[tf-training]: /docs/components/tftraining/

[deploy-script]: https://github.com/kubeflow/kubeflow/blob/master/scripts/gke/deploy.sh

[jupyterhub]: http://jupyter.org/hub
[kubeflow-jupyter]: /docs/guides/components/jupyter/
[kubeflow-jupyter]: /docs/components/jupyter/
[jupyter-nbviewer]: https://jupyter-notebook.readthedocs.io/en/latest/notebook.html#notebook-user-interface
@@ -13,7 +13,7 @@ This guide covers troubleshooting specifically for
[Kubeflow deployments on GKE](/docs/started/getting-started-gke).

For more help, try the
[general Kubeflow troubleshooting guide](/docs/guides/troubleshooting).
[general Kubeflow troubleshooting guide](/docs/other-guides/troubleshooting).

## Troubleshooting Cloud IAP

@@ -268,7 +268,7 @@ ${KUBEFLOW_SRC}/scripts/kfctl.sh apply platform
## CPU platform unavailable in requested zone

By default we set minCpuPlatform to `Intel Haswell` to make sure AVX2 is supported.
See [troubleshooting](/docs/guides/troubleshooting/) for more details.
See [troubleshooting](/docs/other-guides/troubleshooting/) for more details.

If you encounter this `CPU platform unavailable` error (might manifest as
`Cluster is currently being created, deleted, updated or repaired and cannot be updated.`),

This file was deleted.

Oops, something went wrong.

This file was deleted.

Oops, something went wrong.
@@ -0,0 +1,5 @@
+++
title = "Other Guides"
description = "Various instructions on how to use Kubeflow"
weight = 8
+++
@@ -151,7 +151,7 @@ export GITHUB_TOKEN=<< token >>

## ks apply produces error "Unknown variable: env"

Kubeflow requires a [specific version of ksonnet](/docs/guides/requirements).
Kubeflow requires a [specific version of ksonnet](/docs/started/requirements).
If you run `ks apply` with an older version of ksonnet you will likely get the error `Unknown variable: env` as illustrated below:

```shell
@@ -167,7 +167,7 @@ You can check the ksonnet version as follows:
ks version
```
If your ksonnet version is lower than what is specified in the [requirements](/docs/guides/requirements), please upgrade it and follow the [guide](/docs/guides/components/ksonnet) to recreate the app.
If your ksonnet version is lower than what is specified in the [requirements](/docs/started/requirements), please upgrade it and follow the [guide](/docs/components/ksonnet) to recreate the app.
## ksonnet on Windows
There are some known issues with ksonnet and Windows. You might consider
@@ -1,5 +1,5 @@
+++
title = "Pipelines"
description = "Documentation for Kubeflow Pipelines."
weight = 3
weight = 4
+++
@@ -6,15 +6,15 @@ weight = 6

This page is for advanced users. It describes how to build your own pipeline
components. For an easier start, try
[building a pipeline with the provided samples](/docs/guides/pipelines/build-pipeline).
[building a pipeline with the provided samples](/docs/pipelines/build-pipeline).

## Overview of pipeline components

Kubeflow Pipelines components are implementations of pipeline tasks. Each task
takes one or more
[artifacts](/docs/guides/pipelines/pipelines-concepts#step-output-artifacts) as
[artifacts](/docs/pipelines/pipelines-concepts#step-output-artifacts) as
input and may produce one or more
[artifacts](/docs/guides/pipelines/pipelines-concepts#step-output-artifacts) as
[artifacts](/docs/pipelines/pipelines-concepts#step-output-artifacts) as
output.

Each task usually includes two parts:
@@ -44,7 +44,7 @@ There are multiple ways to author components:
* Wrap an existing Docker container image using `ContainerOp`, as described
below.
* Create a
[lightweight python component](/docs/guides/pipelines/lightweight-python-components)
[lightweight python component](/docs/pipelines/lightweight-python-components)
from a Python function
* Build a new Docker container image from a Python function.

@@ -167,8 +167,8 @@ See [an example](https://github.com/kubeflow/pipelines/blob/master/samples/xgboo

You can also build lightweight components from Python functions. See the guide
to
[lightweight python components](/docs/guides/pipelines/lightweight-python-components).
[lightweight python components](/docs/pipelines/lightweight-python-components).

## Export metrics

See the guide to [pipeline metrics](/docs/guides/pipelines/pipelines-metrics).
See the guide to [pipeline metrics](/docs/pipelines/pipelines-metrics).
@@ -138,4 +138,4 @@ Upload the generated `.tar.gz` file through the Kubeflow Pipelines UI.
## Advanced: Build your own components

See how to
[build your own pipeline components](/docs/guides/pipelines/build-component).
[build your own pipeline components](/docs/pipelines/build-component).
@@ -23,7 +23,7 @@ A building block in the pipeline template; self-contained user code that
performs one step in the pipeline, such as preprocessing, transformation,
training, etc. A component must be packaged as a
[Docker image](https://docs.docker.com/get-started/). See the guide to
[building your own components](/docs/guides/pipelines/build-component).
[building your own components](/docs/pipelines/build-component).

## Experiment

@@ -3,7 +3,7 @@ title = "Pipeline metrics"
description = "Export and visualize pipeline metrics."
weight = 9
+++
This page shows you how to export metrics from the component. For details about how to build a component, see the guide to [building your own component](/docs/guides/pipelines/build-component).
This page shows you how to export metrics from the component. For details about how to build a component, see the guide to [building your own component](/docs/pipelines/build-component).

## Overview of metrics

@@ -162,4 +162,5 @@ Receiver operating characteristics (ROC) curve:
deploy Kubeflow and run a sample pipeline directly from the
Kubeflow Pipelines UI.
* Follow the full guide to
[building a pipeline](/docs/guides/pipelines/build-pipeline).
[building a pipeline](/docs/guides/pipelines/build-pipeline).

@@ -6,7 +6,7 @@ weight = 1

Use this guide if you want to get a simple pipeline running quickly in
Kubeflow Pipelines. If you need a more in-depth guide, see how to
[build a pipeline](/docs/guides/pipelines/build-pipeline/).
[build a pipeline](/docs/pipelines/build-pipeline/).

## Deploy Kubeflow and open the pipelines UI

@@ -160,9 +160,9 @@ finished with them:
## Next steps

* Learn more about the
[important concepts](/docs/guides/pipelines/pipelines-concepts) in Kubeflow
[important concepts](/docs/pipelines/pipelines-concepts) in Kubeflow
Pipelines.
* This page showed you how to run some of the examples supplied in the Kubeflow
Pipelines UI. Next, you may want to run a pipeline from a notebook, or compile
and run a sample from the code. See the guide to
[building a pipeline](/docs/guides/pipelines/build-pipeline/).
[building a pipeline](/docs/pipelines/build-pipeline/).
@@ -142,4 +142,4 @@ Upload the generated `.tar.gz` file through the Kubeflow Pipelines UI.
## Advanced: Build your own components

See how to
[build your own pipeline components](/docs/guides/pipelines/build-component).
[build your own pipeline components](/docs/pipelines/build-component).
@@ -118,7 +118,7 @@ the page displaying the name of the run and containing its own three tabs:
### Artifacts

Artifacts are any
[viewers](/docs/guides/pipelines/output-viewer) associated with a given
[viewers](/docs/pipelines/output-viewer) associated with a given
component. There are many kinds of viewers including:

* TensorBoard instances (accessible via link)
@@ -280,10 +280,10 @@ privilege. The three service accounts are:
## Next steps

* Run a full ML workflow on Kubeflow, using the
[end-to-end MNIST tutorial](/docs/guides/gke/gcp-e2e/) or the
[end-to-end MNIST tutorial](/docs/gke/gcp-e2e/) or the
[GitHub issue sumarization
example](https://github.com/kubeflow/examples/tree/master/github_issue_summarization).
* See how to [customize](/docs/guides/gke/customizing-gke) your Kubeflow
* See how to [customize](/docs/gke/customizing-gke) your Kubeflow
deployment on GKE.
* [Troubleshoot](/docs/guides/gke/troubleshooting-gke) any issues you may
* [Troubleshoot](/docs/gke/troubleshooting-gke) any issues you may
find.
@@ -249,6 +249,6 @@ For JupyterHub, you'll be landing on a login page.
- You should be redirected to a page that waits while the server is starting.

If the page doesn't refresh, please see
[troubleshooting](/docs/guides/troubleshooting/#problems-spawning-jupyter-pods).
[troubleshooting](/docs/other-guides/troubleshooting/#problems-spawning-jupyter-pods).

For further exploration refer to the [guide](/docs/guides/).
For further exploration refer to the [documentation](/docs/).
@@ -122,6 +122,6 @@ Point browser to either:

### Where to go next

* Refer to the [user guide](/docs/guides/)
* Refer to the [components](/docs/guides/components/)
* Refer to the [JupyterHub guide](/docs/guides/components/jupyter)
* Refer to the [user guide](/docs/)
* Refer to the [components](/docs/components/)
* Refer to the [JupyterHub guide](/docs/components/jupyter)
@@ -76,14 +76,14 @@ Download, set up, and deploy (If you prefer to work from source code, feel free
* (optional) For GPU support, make sure your cluster is in a [zone that has GPUs](https://cloud.google.com/compute/docs/regions-zones/). To set the zone explicitly, append `--zone ${ZONE}` to the `init` command.

**Important**: The commands above will enable collection of **anonymous** user data to help us improve Kubeflow; for more information including instructions for explicitly
disabling it please refer to the [usage reporting guide](/docs/guides/usage-reporting/).
disabling it please refer to the [usage reporting guide](/docs/other-guides/usage-reporting/).

## Troubleshooting
For detailed troubleshooting instructions, please refer to the [troubleshooting guide](/docs/guides/troubleshooting/).
For detailed troubleshooting instructions, please refer to the [troubleshooting guide](/docs/other-guides/troubleshooting/).

## Resources

* The [guides section](/docs/guides/) provides in-depth instructions for using Kubeflow
* The [documentation](/docs/) provides in-depth instructions for using Kubeflow
* Self-paced scenarios for learning and trying out Kubeflow:
* [Codelabs](https://codelabs.developers.google.com/?cat=tensorflow)
* [Introduction to Kubeflow on Google Kubernetes Engine](https://codelabs.developers.google.com/codelabs/kubeflow-introduction/index.html)
@@ -1,7 +1,7 @@
+++
title = "Requirements"
description = "Requirements for Kubeflow"
weight = 1
weight = 5
+++

The guides in this section give detailed information about using Kubeflow and
@@ -16,7 +16,7 @@ the following systems:

## Kubeflow requirements

* ksonnet version {{% ksonnet-min-version %}} or later. See the [ksonnet component page](/docs/guides/components/ksonnet/) for an explanation of why we use ksonnet.
* ksonnet version {{% ksonnet-min-version %}} or later. See the [ksonnet component page](/docs/components/ksonnet/) for an explanation of why we use ksonnet.
* An existing Kubernetes cluster using Kubernetes {{% kubernetes-min-version %}} or later:
* A minimum of 0.6 CPU in cluster (Reserved for 3 replicated ambassador pods and according to your need add additional CPUs)
* Node with storage >= 10 GB (Due to the ML libraries and third party packages being bundled in Kubeflow Docker images)
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