docs: Knative doc updates
-Deploying to KNative
+Deploying to Knative
====================
-Knative is kubernetes based platform to deploy and manage serverless workloads. It is a
+Knative components build on top of Kubernetes to simplify deploying and managing serverless workloads. It is a
solution for deploying ML workload that requires more computing power that abstracts away
infrastructure management and without worry about vendor lock.
+For more information see the Knative documentation: https://knative.dev/docs/
+
This guide demonstrates how to serve a scikit-learn based iris classifier model with
-BentoML on a KNative cluster. The same deployment steps are also applicable for models
+BentoML on a Knative cluster. The same deployment steps are also applicable for models
trained with other machine learning frameworks, see more BentoML examples :doc:`here <../examples>`.
Prerequisites
-------------
-* A kubernetes cluster.
+* A kubernetes cluster:
* `minikube` is the recommended way to run Kubernetes locally:: https://kubernetes.io/docs/tasks/tools/install-minikube/
* Kubernetes guide: https://kubernetes.io/docs/setup/
-* Knative with istio as network layer
+* Knative with Istio as a networking layer:
- * Knative install instruction: https://knative.dev/docs/install/any-kubernetes-cluster/
+ * Knative installation instructions: https://knative.dev/docs/admin/install/
- * Install istio for knative: https://knative.dev/docs/install/installing-istio/
+ * Installing Istio for knative: https://knative.dev/docs/admin/install/installing-istio/
* Python 3.6 or above and install required packages: `bentoml` and `scikit-learn`
- * .. code-block:: bash
+ .. code-block:: bash
pip install bentoml scikit-learn
@@ -105,7 +107,7 @@ BentoService and available for sending test request:
======================================
-Deploy BentoML model server to KNative
+Deploy BentoML model server to Knative
======================================
BentoML provides a convenient way to containerize the model API server with Docker:
@@ -126,7 +128,7 @@ BentoML provides a convenient way to containerize the model API server with Dock
docker push {docker_username}/iris-classifier
-Make sure Knative serving components are running.
+Make sure Knative Serving components are running.
.. code-block:: bash
@@ -176,7 +178,7 @@ readyinessProbe to the /healthz endpoint on BentoService.
-Create bentoml namespace and then deploy BentoService to Knative with kubectl apply command.
+Create bentoml namespace and then deploy BentoService to Knative by using the kubectl apply command.
.. code-block:: bash
