Deleted the page about Istio for TF Serving (#1523)

* Deleted the page about Istio for TFServing.

* Updated references to Istio.

content/_index.html

@@ -134,7 +134,7 @@ <h5 class="card-title text-light section-head">Multi-framework</h5>
 			<a target='_blank' class='text-light' href="/docs/components/training/mxnet/"> MXNet</a>, 
 			<a target='_blank' class='text-light' href="/docs/components/training/chainer/"> Chainer</a>, and more. We
 			also integrate with 
-			<a target='_blank' class='text-light' href="/docs/components/serving/istio/">Istio</a> and 
+			<a target='_blank' class='text-light' href="https://istio.io/">Istio</a> and 
 			<a target='_blank' class='text-light' href="https://www.getambassador.io/">Ambassador</a> for ingress, 
 			<a target='_blank' class='text-light' href="/docs/components/misc/nuclio/">Nuclio</a> as a
             fast multi-purpose serverless framework, and <a target='_blank' class='text-light' href="https://www.pachyderm.io/">Pachyderm</a> for managing

content/_redirects

@@ -70,7 +70,6 @@ docs/started/requirements/                    /docs/started/getting-started/
 # Created a new components layout
 /docs/components/hyperparameter                /docs/components/hyperparameter-tuning/hyperparameter
 /docs/components/chainer                       /docs/components/training/chainer
-/docs/components/istio                         /docs/components/serving/istio
 /docs/components/modeldb                       /docs/components/misc/modeldb
 /docs/components/mpi                           /docs/components/training/mpi
 /docs/components/mxnet                         /docs/components/training/mxnet

content/docs/components/serving/overview.md

@@ -156,7 +156,7 @@ KFServing and Seldon Core. A check mark (**✓**) indicates that the system
       </tr>
 
       <tr>
-        <td>istio</td>
+        <td>Istio</td>
         <td></td>
         <td><b>&check;</b></td>
         <td><b>&check;</b></td>
@@ -191,10 +191,8 @@ Further information:
 
 ## TensorFlow Serving
 
-For TensorFlow models you can use TensorFlow Serving for both 
-[real-time](/docs/components/serving/tfserving_new) and 
-[batch](/docs/components/serving/tfbatchpredict) prediction. Kubeflow also
-supports [TensorFlow serving via Istio](/docs/components/serving/istio). 
+For TensorFlow models you can use TensorFlow Serving for 
+[real-time prediction](/docs/components/serving/tfserving_new).
 However, if you plan to use multiple frameworks, you should consider KFServing
 or Seldon Core as described above.