Merge pull request intel#260 from chaitanya1731/readme-fix

Documentation: Updated Readmes to fix broken links

docs/releases.md

@@ -12,7 +12,7 @@
 ## Reference Links
 - [Intel Device Plugins Operator](https://catalog.redhat.com/software/container-stacks/detail/61e9f2d7b9cdd99018fc5736)
 - [Kernel Module Management Operator](https://catalog.redhat.com/software/container-stacks/detail/6524b0876df0b7666fb33cfa)
-- [NFD Operator]()
+- [NFD Operator](https://docs.openshift.com/container-platform/4.15/hardware_enablement/psap-node-feature-discovery-operator.html)
 - [OpenVINO Operator](https://catalog.redhat.com/software/container-stacks/detail/60649a56209af65d24b7ca9e)
 - [Red Hat OpenShift AI Operator](https://catalog.redhat.com/software/container-stacks/detail/63b85b573112fe5a95ee9a3a)
 - Intel Data Center GPU Drivers for OpenShift - [Red Hat Container Catalog](https://catalog.redhat.com/software/containers/intel/intel-data-center-gpu-driver-container/6495ee55c8b2461e35fb8264)

e2e/inference/README.md

@@ -13,47 +13,48 @@ Intel AI inference end-to-end solution with RHOCP is based on the Intel® Data C
 ## Install RHOAI
 The Red Hat certified RHOAI operator is published at [Red Hat Ecosystem Catalog](https://catalog.redhat.com/software/container-stacks/detail/63b85b573112fe5a95ee9a3a). You can use the command line interface (CLI) or web console to install it.
 ### Install using CLI (To be added)
-### Install using web console
+### Install using Web Console
 1.	On the RHOCP web console, click Operators → OperatorHub.
-2.	Search RedHat OpenShift AI Operator and click Install. The operator is installed in the namespace redhat-ods-operator.
+2.	Search RedHat OpenShift AI Operator and click Install. The operator is installed in the namespace `redhat-ods-operator`.
 ### Verification
 1.	Navigate to Operators → Installed Operators page.
 2.	Ensure that in the redhat-ods-operator namespace, RedHat OpenShift AI status is InstallSucceeded 
-3.	Click on ```Search -> Routes -> rhods-dashboard``` from the web console and access the RHOAI UI link.
-Note: When installing the operator, the default ```kfdef``` Custom Resource (CR) is created. This CR enables the dashboard for users to browse and launch Jupyter Notebooks projects on an RHOCP cluster. Please refer to this [link](https://github.com/red-hat-data-services/odh-deployer) for more details about kfdef.
-## Install OpenVINO operator
+3.	Click on `Search` -> `Routes` -> `rhods-dashboard` from the web console and access the RHOAI UI link.  
+**Note:** When installing the operator, the default `kfdef` Custom Resource (CR) is created. This CR enables the dashboard for users to browse and launch Jupyter Notebooks projects on an RHOCP cluster. Please refer to this [link](https://github.com/red-hat-data-services/odh-deployer) for more details about `kfdef`.
+## Install OpenVINO Operator
 The OpenVINO operator is published at [Red Hat Ecosystem Catalog](https://catalog.redhat.com/software/container-stacks/detail/60649a56209af65d24b7ca9e). You can use the CLI or web console to install it.
 ### Install using CLI (To be added)
-### Install using web console
-Follow this [link](https://github.com/openvinotoolkit/operator/blob/v1.1.0/docs/operator_installation.md)  to install the operator via the web console. 
-## Work with interactive mode
+### Install using Web Console
+Follow this [link](https://github.com/openvinotoolkit/operator/blob/v1.1.0/docs/operator_installation.md#operator-instalation)  to install the operator via the web console. 
+## Work with Interactive Mode
 To enable the interactive mode, the OpenVINO notebook CR needs to be created and integrated with RHOAI.  
-1.	Click on the ```create Notebook``` option from the web console and follow these [steps](https://github.com/openvinotoolkit/operator/blob/main/docs/notebook_in_rhods.md) to create the notebook CR.
+1.	Click on the `create Notebook` option from the web console and follow these [steps](https://github.com/openvinotoolkit/operator/blob/main/docs/notebook_in_rhods.md#integration-with-openshift-data-science-and-open-data-hub) to create the notebook CR.
 2.	Enable Intel Data Center GPU on RHOAI Dashboard- **Technical Preview feature**
 
-Create AcceleratoProfile in the ```redhat-ods-applications``` namespace 
+Create `AcceleratorProfile` in the `redhat-ods-applications` namespace 
+```
+$ oc apply -f https://raw.githubusercontent.com/intel/intel-technology-enabling-for-openshift/main/e2e/inference/accelerator_profile.yaml
+```
 
-```$ oc apply -f https://raw.githubusercontent.com/intel/intel-technology-enabling-for-openshift/main/e2e/inference/accelerator_profile.yaml```
-
-3. Navigate to ```openvino-notebooks``` ImageStream and add the above created ```AcceleratorProfile``` key to the annotation field, as shown in the image below:
+1. Navigate to `openvino-notebooks` ImageStream and add the above created `AcceleratorProfile` key to the annotation field, as shown in the image below:
 
 ![Alt text](/docs/images/openvino-accelerator-field.png)
 
-4. Navigate to ```Search -> Networking -> Routes``` from the web console and access ```rhods-dashboard``` route in the ```redhat-ods-applications``` namespace, as in the image below. Click on the location link to launch RHOAI dashboard. 
+4. Navigate to `Search` -> `Networking` -> `Routes` from the web console and access `rhods-dashboard` route in the `redhat-ods-applications` namespace, as in the image below. Click on the location link to launch RHOAI dashboard. 
 
 ![Alt text](/docs/images/rhods-dashboard-route.png)
 
 5. If step 2 is successful, ```Intel® Data Center GPU Flex Series 140 ``` is shown in the accelerator dropdown menu in ```rhods-dashboard```. Users can run OpenVINO notebook image with Intel® Data Center GPU Flex Series 140 card. 
 
 ![Alt text](/docs/images/accelerator-profile-dropdown.png)
 
-Follow the [link](https://github.com/openvinotoolkit/operator/blob/main/docs/notebook_in_rhods.md) for more details on the available Jupyter Notebooks.
+Follow the [link](https://github.com/openvinotoolkit/operator/blob/main/docs/notebook_in_rhods.md#integration-with-openshift-data-science-and-open-data-hub) for more details on the available Jupyter Notebooks.
 
-## Work with deployment mode
-1.	From the web console, click on the ModelServer option in this [link](https://github.com/openvinotoolkit/operator/blob/v1.1.0/docs/operator_installation.md) and follow the [steps](https://github.com/openvinotoolkit/operator/blob/v1.1.0/docs/modelserver.md) to start the OVMS instance.  
+## Work with Deployment Mode
+1.	From the web console, click on the ModelServer option in this [link](https://github.com/openvinotoolkit/operator/blob/v1.1.0/docs/operator_installation.md#operator-instalation) and follow the [steps](https://github.com/openvinotoolkit/operator/blob/v1.1.0/docs/modelserver.md#managing-model-servers-via-operator) to start the OVMS instance.  
 2.	To enable the Intel Data Center GPU, make sure to modify the OVMS instance options according to the screenshot below.
 
-* Below images show gpu.intel.com/i915 resource requests and limits for OVMS
+* Below images show `gpu.intel.com/i915` resource requests and limits for OVMS
 
 ![Alt text](/docs/images/Ovms-Gpu-resource-limit.png)