OpenShift Install Instrcutions + AIX360 in main samples (kubeflow#1227)

* add pointer to OpenShift * add AIX 360 in main sample directory * add reference to LIME * update containers UID 0 section
magdalenakuhn17 · Nov 23, 2020 · 49fb942 · 49fb942
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diff --git a/README.md b/README.md
@@ -55,6 +55,11 @@ As of KFServing 0.4 release [object selector](https://kubernetes.io/docs/referen
 ```bash
 kubectl patch mutatingwebhookconfiguration inferenceservice.serving.kubeflow.org --patch '{"webhooks":[{"name": "inferenceservice.kfserving-webhook-server.pod-mutator","objectSelector":{"matchExpressions":[{"key":"serving.kubeflow.org/inferenceservice", "operator": "Exists"}]}}]}'
 ```
+
+#### Standalone KFServing on OpenShift
+
+To install standalone KFServing on [OpenShift Container Platform](https://www.openshift.com/products/container-platform), please follow the [instructions here](docs/OPENSHIFT_GUIDE.md).
+
 #### KFServing with Kubeflow Installation
 KFServing is installed by default as part of Kubeflow installation using [Kubeflow manifests](https://github.com/kubeflow/manifests/tree/master/kfserving) and KFServing controller is deployed in `kubeflow` namespace.
 Since Kubeflow Kubernetes minimal requirement is 1.14 which does not support object selector, `ENABLE_WEBHOOK_NAMESPACE_SELECTOR` is enabled in Kubeflow installation by default.

diff --git a/docs/OPENSHIFT_GUIDE.md b/docs/OPENSHIFT_GUIDE.md
@@ -14,9 +14,7 @@ git clone https://github.com/kubeflow/kfserving
 
 ## Add Security Context Constraint (SCC)
 
-Run the following to enable containers to run with UID 0 for Istio’s service accounts. As we make further progress,
-we will be revisiting these instructions to enable it to work without having to run containers with UID 0.
-
+Run the following to enable containers to run with UID 0 for Istio’s service accounts, as recommended on [Istio's installation instructions for OpenShift](https://istio.io/latest/docs/setup/platform-setup/openshift/)
 
 ```bash
 oc adm policy add-scc-to-group anyuid system:serviceaccounts:istio-system

diff --git a/docs/samples/README.md b/docs/samples/README.md
@@ -60,12 +60,15 @@ Model explainability answers the question: "Why did my model make this predictio
 integrates with [Alibi Explainer](https://github.com/SeldonIO/alibi) which implements a black-box algorithm by generating a lot of similar looking intances 
 for a given instance and send out to the model server to produce an explanation.
 
+Additionally KFServing also integrates with The [AI Explainability 360 (AIX360)](https://ai-explainability-360.org/) toolkit, an LF AI Foundation incubation project, which is an open-source library that supports the interpretability and explainability of datasets and machine learning models. The AI Explainability 360 Python package includes a comprehensive set of algorithms that cover different dimensions of explanations along with proxy explainability metrics. In addition to native algorithms, AIX360 also provides algorithms from LIME and Shap.
 
 | Features  | Examples |
 | ------------- | ------------- |
 | Deploy Alibi Image Explainer| [Imagenet Explainer](./explanation/alibi/imagenet)  |
 | Deploy Alibi Income Explainer| [Income Explainer](./explanation/alibi/income)  |
 | Deploy Alibi Text Explainer| [Alibi Text Explainer](./explanation/alibi/moviesentiment) |
+| Deploy AIX360 Image Explainer| [AIX360 Image Explainer](./explanation/aix/mnist/README.md) |
+
 
 ### Deploy InferenceService with Outlier/Drift Detector
 In order to trust and reliably act on model predictions, it is crucial to monitor the distribution of the incoming