Add metadata API reference doc (kubeflow#1058)

* add metadata API spec

* add link to metadata doc page

* address comments

* remove metadata.md

Author: zhenghuiwang

content/docs/components/misc/metadata.md

@@ -38,7 +38,7 @@ You can find an example of how to use the logging API in this [notebook](https:/
 
 ## Backend
 
-The backend uses [ML-Metadata](https://github.com/google/ml-metadata/blob/master/g3doc/get_started.md) to manage all the metadata and relations. It exposes a [REST API](https://github.com/kubeflow/metadata/blob/master/api/service.swagger.json).
+The backend uses [ML-Metadata](https://github.com/google/ml-metadata/blob/master/g3doc/get_started.md) to manage all the metadata and relations. It exposes a [REST API](/docs/reference/metadata/v1alpha1/kubeflow-metadata-api-spec/).
 
 ## UI
 

content/docs/reference/metadata/v1alpha1/kubeflow-metadata-api-spec.html

@@ -8,7 +8,7 @@ weight = 1
 <a id="tfjob">
 ## TFJob
 
-TFJob is a Kubernetes 
+TFJob is a Kubernetes
 [custom resource](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/)
 that you can use to run TensorFlow training jobs on Kubernetes. For help with
 using TFJob with Kubeflow, see the [user guide](/docs/components/tftraining/).
@@ -30,3 +30,12 @@ API references:
 
   * [v1](/docs/reference/pytorchjob/v1/pytorch/)
   * [v1beta2](/docs/reference/pytorchjob/v1beta2/pytorch/)
+
+<a id="metadata">
+## Metadata
+
+The goal of the [Metadata](https://github.com/kubeflow/metadata) project is to help Kubeflow users understand and manage their machine learning workflows by tracking and managing the metadata of workflows.
+
+API references:
+
+  * [v1alpha1](/docs/reference/metadata/v1alpha1/kubeflow-metadata-api-spec/)