[DOC] Misc fix on helm installation description

Author: yansun1996

docs/installation/kubernetes-helm.md

@@ -118,19 +118,21 @@ To install the latest version of the GPU Operator run the following Helm install
 ```bash
 helm install amd-gpu-operator rocm/gpu-operator-charts \
   --namespace kube-amd-gpu \
-  --create-namespace
+  --create-namespace \
   --version=v1.3.0
 ```
 
 ```{note}
 Installation Options
   - Skip NFD installation: `--set node-feature-discovery.enabled=false`
-  - Skip KMM installation: `--set kmm.enabled=false`
+  - Skip KMM installation: `--set kmm.enabled=false`. <br> Although KMM is a [Kubernetes-SIGs](https://github.com/kubernetes-sigs) maintained project, it is strongly recommended to use AMD optimized and published KMM images included in each operator release.
   - Disable default DeviceConfig installation: `--set crds.defaultCR.install=false`
 ```
 
-```{warning}
-  It is strongly recommended to use AMD-optimized KMM images included in the operator release.
+```{tip}
+1. Before v1.3.0 the gpu operator helm chart won't provide a default ```DeviceConfig```, you need to take extra step to create a ```DeviceConfig```.
+
+2. Starting from v1.3.0 the ```helm install``` command would support one-step installation + configuration, which would create a default ```DeviceConfig``` with default values, which may not work for all the users with different the deployment scenarios, please refer to {ref}`typical-deployment-scenarios` for more information and get corresponding ```helm install``` commands. 
 ```
 
 ### 3. Helm Chart Customization Parameters
@@ -471,7 +473,7 @@ kubectl get modules -n kube-amd-gpu
 - Check NFD status:
 
 ```bash
-kubectl get nodefeatures -n kube-amd-gpu
+kubectl get nodefeaturerules -n kube-amd-gpu
 ```
 
 For more detailed troubleshooting steps, see our [Troubleshooting Guide](../troubleshooting).

docs/slinky/slinky-example.md

@@ -11,6 +11,14 @@ cd example/slinky
 
 ## Installing Slinky Prerequisites
 
+Install AMD GPU Operator, configure the `DeviceConfig` and make sure that the device plugin is advertising the AMD GPU devices as allocatable resources
+
+```bash
+$ kubectl get node -oyaml | grep -i allocatable -A 10 | grep amd.com
+
+amd.com/gpu: "8"
+```
+
 The following steps for installing pre-requisites and installing Slinky have been taking from the SlinkProject/slinky-operator repo [quick-start guide](https://github.com/SlinkyProject/slurm-operator/blob/main/docs/quickstart.md)
 
 ```bash

docs/troubleshooting.md

@@ -18,6 +18,21 @@ To collect logs from the AMD GPU Operator:
 kubectl logs -n kube-amd-gpu <pod-name>
 ```
 
+
+## Potential Issues with default ``DeviceConfig``
+
+* Please refer to [Typical Deployment Scenarios](../usage.html#typical-deployment-scenarios) for more information and get corresponding ```helm install``` commands and configs that fits your specific use case.
+
+* If operand pods (e.g. device plugin, metrics exporter) are stuck in ``Init:0/1`` state, it means your GPU worker doesn't have GPU driver loaded or driver was not loaded properly. 
+
+    * If you try to use inbox or pre-installed driver please check the node ``dmesg`` to see why the driver was not loaded properly. 
+    
+    * If you want to deploy out-of-tree driver, we suggest check the `Driver Installation Guide <./drivers/installation.html>`_ then modify the default ``DeviceConfig`` to ask Operator to install the out-of-tree GPU driver for your worker nodes.
+
+```bash
+kubectl edit deviceconfigs -n kube-amd-gpu default
+```
+
 ## Debugging Driver Installation
 
 If the AMD GPU driver build fails:
@@ -42,7 +57,7 @@ kubectl get events -n kube-amd-gpu
 
 ## Using Techsupport-dump Tool
 
-The techsupport-dump tool can be used to collect system state and logs for debugging:
+The [techsupport-dump script](https://github.com/ROCm/gpu-operator/blob/main/tools/techsupport_dump.sh) can be used to collect system state and logs for debugging:
 
 ```bash
 ./tools/techsupport_dump.sh [-w] [-o yaml/json] [-k kubeconfig] <node-name/all>
@@ -53,3 +68,5 @@ Options:
 - `-w`: wide option
 - `-o yaml/json`: output format (default: json)
 - `-k kubeconfig`: path to kubeconfig (default: ~/.kube/config)
+
+Please file an issue with collected techsupport bundle on our [GitHub Issues](https://github.com/ROCm/gpu-operator/issues) page