fix link change

Author: jiaochenlu

articles/machine-learning/how-to-deploy-kubernetes-extension.md

@@ -59,7 +59,7 @@ You can use Azure Machine Learning CLI command `k8s-extension create` to deploy
    | `allowInsecureConnections` |`True` or `False`, default `False`. **Can** be set to `True` to use inference HTTP endpoints for development or test purposes. |N/A| Optional |  Optional |
    | `inferenceRouterServiceType` |`loadBalancer`, `nodePort` or `clusterIP`.  **Required** if `enableInference=True`. | N/A| **✓** |   **✓** |
    | `internalLoadBalancerProvider` | This config is only applicable for Azure Kubernetes Service(AKS) cluster now. Set to `azure` to allow the inference router using internal load balancer.  | N/A| Optional |  Optional |
-   |`sslSecret`| The name of the Kubernetes secret in the `azureml` namespace. This config is used to store `cert.pem` (PEM-encoded TLS/SSL cert) and `key.pem` (PEM-encoded TLS/SSL key), which are required for inference HTTPS endpoint support when ``allowInsecureConnections`` is set to `False`. For a sample YAML definition of `sslSecret`, see [Configure sslSecret](./how-to-secure-kubernetes-online-endpoint.md#configure-sslsecret). Use this config or a combination of `sslCertPemFile` and `sslKeyPemFile` protected config settings. |N/A| Optional |  Optional |
+   |`sslSecret`| The name of the Kubernetes secret in the `azureml` namespace. This config is used to store `cert.pem` (PEM-encoded TLS/SSL cert) and `key.pem` (PEM-encoded TLS/SSL key), which are required for inference HTTPS endpoint support when ``allowInsecureConnections`` is set to `False`. For a sample YAML definition of `sslSecret`, see [Configure sslSecret](./how-to-secure-kubernetes-online-endpoint.md). Use this config or a combination of `sslCertPemFile` and `sslKeyPemFile` protected config settings. |N/A| Optional |  Optional |
    |`sslCname` |An TLS/SSL CNAME is used by inference HTTPS endpoint. **Required** if `allowInsecureConnections=False`  |  N/A | Optional | Optional|
    | `inferenceRouterHA` |`True` or `False`, default `True`. By default, Azure Machine Learning extension will deploy three inference router replicas for high availability, which requires at least three worker nodes in a cluster. Set to `False` if your cluster has fewer than three worker nodes, in this case only one inference router service is deployed. | N/A| Optional |  Optional |
    |`nodeSelector` | By default, the deployed kubernetes resources and your machine learning workloads are randomly deployed to one or more nodes of the cluster, and DaemonSet resources are deployed to ALL nodes. If you want to restrict the extension deployment and your training/inference workloads to specific nodes with label `key1=value1` and `key2=value2`, use `nodeSelector.key1=value1`, `nodeSelector.key2=value2` correspondingly. | Optional| Optional |  Optional |

articles/machine-learning/configure-a-secure-online-endpoint-with-tls-ssl.md renamed to articles/machine-learning/how-to-secure-kubernetes-online-endpoint.md

@@ -495,7 +495,7 @@
           href: how-to-secure-kubernetes-inferencing-environment.md
         - name: Configure a secure online endpoint with TLS/SSL
           displayName: AKS, Arc Kubernetes, HTTPS, TSL, SSL, Cname, DNS, Certificate, inference
-          href: configure-a-secure-online-endpoint-with-tls-ssl.md
+          href: how-to-secure-kubernetes-online-endpoint.md
         - name: Troubleshoot Azure Machine Learning extension
           displayName: AKS, Arc Kubernetes, Azure Machine Learning extension, troubleshoot
           href: how-to-troubleshoot-kubernetes-extension.md