fix grammar bug
@@ -24,7 +24,7 @@ kubectl get events -n azureml --sort-by='.lastTimestamp'
helm history -n azureml --debug <extension-name>
```
### 2. Do health check for extension
-If the installation fails, you can use the built-in health check job to make a comprehensive check on the extension, and the check will also produce a report. This report can facilitate us to better locate the problem. We recommend that you send us these reports when you need our help to solve the installation problems. The report is saved in configmap named "amlarc-healthcheck" under azureml namespace.
+If the installation fails, you can use the built-in health check job to make a comprehensive check on the extension, and the check will also produce a report. This report can facilitate us to better locate the problem. We recommend that you send us these reports when you need our help to solve the installation problems. The report is saved in configmap named "arcml-healthcheck" under azureml namespace.
```bash
# trigger the built-in test to generate a health report of the extension
helm test -n azureml <extension-name> --logs
@@ -39,7 +39,7 @@ kubectl get configmap -n azureml amlarc-healthcheck --output="jsonpath={.data.re
```
> Note: When running "helm test" command, Error like "unable to get pod logs for healthcheck-config: pods 'healthcheck-config' not found" should be ignored.
### 3. Inference HA(High availability)
-For inference azureml-fe agent, HA feature is enabled by default. So, by default, the inference feature requires at least 3 nodes to run. The phenomenon that this kind of issue may lead to is that some azureml-fe pods are pending on scheduling and error message of the pod could be like "0/1 nodes are available: 1 node(s) didn't match pod anti-affinity rules".
+For inference azureml-fe agent, HA feature is enabled by default. So, by default, the inference feature requires at least 3 nodes to run. The phenomenon that this kind of issue may lead to is that some ```azureml-fe``` pods are pending on scheduling and error message of the pod could be like **"0/1 nodes are available: 1 node(s) didn't match pod anti-affinity rules"**.
### 4. Inference scoring endpoint
It's very important for inference to expose scoring endpoint. According to the cluster configuration and testing scenarios, we have three ways to expose scoring services: **public loadbalancer, private endpoint and nodeport**. Public loadbalancer is used by default. ```privateEndpointNodeport``` and ```privateEndpointILB``` flags are used for the rest two scenarios. For detailed flag usage, please refer to [doc](./deploy-extension.md#review-azureml-deployment-configuration-settings). Many customers got problems in setting up loadbalancer, so we strongly recommend reading the relevant documents and doing some checks before the installation. If you find that inference-operator pod is crashed and azureml-fe service is in pending or unhealthy state, it is likely that endpoint flags are not set properly.
### 5. Error: resources cannot be imported into the current release: invalid ownership metadata
