Moved GCP Pipelines tutorial to GCP section of docs (kubeflow#1004)

* Moved GCP Pipelines tutorial to GCP section of docs.

* Addressed review comments.

Author: sarahmaddox

content/_redirects

@@ -32,7 +32,8 @@
 /docs/pipelines/install-sdk/                   /docs/pipelines/sdk/install-sdk/
 /docs/pipelines/lightweight-python-components/ /docs/pipelines/sdk/lightweight-python-components/
 /docs/pipelines/build-pipeline/                /docs/pipelines/tutorials/build-pipeline/
-/docs/pipelines/pipelines-tutorial/            /docs/pipelines/tutorials/pipelines-tutorial/
+/docs/pipelines/pipelines-tutorial/            /docs/gke/pipelines-tutorial/
+/docs/pipelines/tutorials/pipelines-tutorial/  /docs/gke/pipelines-tutorial/
 
 /docs/pipelines/metrics/                       /docs/pipelines/sdk/pipelines-metrics/
 /docs/pipelines/metrics/pipelines-metrics/     /docs/pipelines/sdk/pipelines-metrics/

content/docs/pipelines/tutorials/pipelines-tutorial.md content/docs/gke/pipelines-tutorial.md

@@ -1,14 +1,18 @@
 +++
 title = "Pipelines End-to-end on GCP"
 description = "An end-to-end tutorial for Kubeflow Pipelines on GCP"
-weight = 2
+weight = 15
 +++
 
 This guide walks you through a Kubeflow Pipelines sample that runs an MNIST
 machine learning (ML) model on Google Cloud Platform (GCP).
 
 ## Introductions
 
+[Kubeflow Pipelines](/docs/pipelines/) is a platform for building and 
+deploying portable, scalable ML workflows based on 
+Docker containers. When you install Kubeflow, you get Kubeflow Pipelines too.
+
 By working through this tutorial, you learn how to deploy Kubeflow on 
 Kubernetes Engine (GKE) and run a pipeline supplied as a Python script. 
 The pipeline trains an MNIST model for image classification and serves the model

content/docs/pipelines/pipelines-quickstart.md

@@ -6,7 +6,7 @@ weight = 10
 
 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 the
-[end-to-end tutorial](/docs/pipelines/tutorials/pipelines-tutorial/).
+[end-to-end tutorial](/docs/gke/pipelines-tutorial/).
 
 * This quickstart guide shows you how to use one of the samples that come with 
   the Kubeflow Pipelines installation and are visible on the Kubeflow Pipelines
@@ -181,7 +181,7 @@ finished with them:
 * Learn more about the 
   [important concepts](/docs/pipelines/concepts/) in Kubeflow
   Pipelines.
-* Follow the [end-to-end tutorial](/docs/pipelines/tutorials/pipelines-tutorial/) 
+* Follow the [end-to-end tutorial](/docs/gke/pipelines-tutorial/) 
   using an MNIST machine-learning model.
 * 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 

content/docs/pipelines/tutorials/cloud-tutorials.md

@@ -0,0 +1,15 @@
++++
+title = "Run a Cloud-specific Pipelines Tutorial"
+description = "Choose the Kubeflow Pipelines tutorial to suit your deployment"
+weight = 1
++++
+
+{{% alert title="Opportunity to add cloud tutorials" color="info" %}}
+<p>We currently have only a GCP tutorial for Kubeflow Pipelines. A tutorial for
+Microsoft Azure is on its way (see 
+<a href="https://github.com/kubeflow/website/pull/956">PR #956</a>).</p>
+<p><b>Invitation:</b> Create a cloud-specific tutorial and link it here.
+See the <a href="/docs/about/docs/">guide to the Kubeflow docs</a>.</p>
+{{% /alert %}}
+
+* [Pipelines End-to-end on GCP](/docs/gke/pipelines-tutorial/): An end-to-end tutorial for Kubeflow Pipelines on Google Cloud Platform (GCP).