Merge pull request #10549 from rothja/bdcmssqlclustername

Updating notes about default mssql-cluster name

Author: rothja

docs/big-data-cluster/big-data-cluster-create-apps.md

@@ -75,7 +75,7 @@ If you are using AKS, you need to run the following command to get the IP addres
 
 
 ```bash
-kubectl get svc mgmtproxy-svc-external -n <name of your cluster>
+kubectl get svc mgmtproxy-svc-external -n <name of your big data cluster>
 ```
 
 ## Kubeadm or Minikube

docs/big-data-cluster/connect-to-big-data-cluster.md

@@ -32,9 +32,12 @@ To connect to a big data cluster with Azure Data Studio, make a new connection t
 1. From the command line, find the IP of your master instance with the following command:
 
    ```
-   kubectl get svc master-svc-external -n <your-cluster-name>
+   kubectl get svc master-svc-external -n <your-big-data-cluster-name>
    ```
 
+   > [!TIP]
+   > The big data cluster name defaults to **mssql-cluster** unless you customized the name in a deployment configuration file. For more information, see [Configure deployment settings for big data clusters](deployment-custom-configuration.md#clustername).
+
 1. In Azure Data Studio, press **F1** > **New Connection**.
 
 1. In **Connection type**, select **Microsoft SQL Server**.

docs/big-data-cluster/data-ingestion-curl.md

@@ -20,14 +20,14 @@ This article explains how to use **curl** to load data into HDFS on SQL Server 2
 
 ## Obtain the service external IP
 
-WebHDFS is started when deployment is completed, and its access goes through Knox. The Knox endpoint is exposed through a Kubernetes service called **gateway-svc-external**.  To create the necessary WebHDFS URL to upload/download files, you need the **gateway-svc-external** service external IP address and the name of your cluster. You can get the **gateway-svc-external** service external IP address by running the following command:
+WebHDFS is started when deployment is completed, and its access goes through Knox. The Knox endpoint is exposed through a Kubernetes service called **gateway-svc-external**.  To create the necessary WebHDFS URL to upload/download files, you need the **gateway-svc-external** service external IP address and the name of your big data cluster. You can get the **gateway-svc-external** service external IP address by running the following command:
 
 ```bash
-kubectl get service gateway-svc-external -n <cluster name> -o json | jq -r .status.loadBalancer.ingress[0].ip
+kubectl get service gateway-svc-external -n <big data cluster name> -o json | jq -r .status.loadBalancer.ingress[0].ip
 ```
 
 > [!NOTE]
-> The `<cluster name>` here is the name of the cluster that you specified in the deployment configuration file. The default name is `mssql-cluster`.
+> The `<big data cluster name>` here is the name of the cluster that you specified in the deployment configuration file. The default name is `mssql-cluster`.
 
 ## Construct the URL to access WebHDFS
 

docs/big-data-cluster/data-ingestion-restore-database.md

@@ -32,7 +32,7 @@ This article shows how to restore the AdventureWorks database, but you can use a
 Copy the backup file to the SQL Server container in the master instance pod of the Kubernetes cluster.
 
 ```bash
-kubectl cp <path to .bak file> mssql-master-pool-0:/tmp -c mssql-server -n <name of your cluster>
+kubectl cp <path to .bak file> mssql-master-pool-0:/tmp -c mssql-server -n <name of your big data cluster>
 ```
 
 Example:
@@ -44,7 +44,7 @@ kubectl cp ~/Downloads/AdventureWorks2016CTP3.bak mssql-master-pool-0:/tmp -c ms
 Then, verify that the backup file was copied to the pod container.
 
 ```bash
-kubectl exec -it mssql-master-pool-0 -n <name of your cluster> -c mssql-server -- bin/bash
+kubectl exec -it mssql-master-pool-0 -n <name of your big data cluster> -c mssql-server -- bin/bash
 cd /var/
 ls /tmp
 exit

docs/big-data-cluster/deploy-get-started.md

@@ -46,7 +46,7 @@ After configuring Kubernetes, you deploy a big data cluster with the `mssqlctl c
 
 - If you are deploying to a dev-test environment, you can choose to use one of the [default configurations](deployment-guidance.md#deploy) provided by **mssqlctl**.
 
-- To customize your deployment, you can create and use your own [deployment configuration files](deployment-guidance.md#configfile). 
+- To customize your deployment, you can create and use your own [deployment configuration files](deployment-guidance.md#configfile).
 
 - For a completely unattended installation, you can pass all other settings in  environment variables. For more information, see [unattended deployments](deployment-guidance.md#unattended).
 

docs/big-data-cluster/deployment-custom-configuration.md

@@ -45,7 +45,7 @@ mssqlctl cluster config section set -c custom.json -j ".metadata.name=test-clust
 ```
 
 > [!IMPORTANT]
-> The name of your cluster must be only lower case alpha-numeric characters, no spaces. All Kubernetes artifacts (containers, pods, statefull sets, services) for the cluster will be created in a namespace with same name as the cluster name specified.
+> The name of your big data cluster must be only lower case alpha-numeric characters, no spaces. All Kubernetes artifacts (containers, pods, statefull sets, services) for the cluster will be created in a namespace with same name as the cluster name specified.
 
 ## <a id="ports"></a> Update endpoint ports
 

docs/big-data-cluster/deployment-guidance.md

@@ -87,8 +87,10 @@ You can deploy a big data cluster by running **mssqlctl cluster create**. This p
 mssqlctl cluster create
 ```
 
-> [!TIP]
-> In this example, you are prompted for any settings that are not part of the default configuration, such as passwords. Note that the Docker information is provided to you by Microsoft as part of the SQL Server 2019 [Early Adoption Program](https://aka.ms/eapsignup).
+In this scenario, you are prompted for any settings that are not part of the default configuration, such as passwords. Note that the Docker information is provided to you by Microsoft as part of the SQL Server 2019 [Early Adoption Program](https://aka.ms/eapsignup).
+
+> [!IMPORTANT]
+> The default name of the big data cluster is **mssql-cluster**. This is important to know in order to run any of the **kubectl** commands that specify the Kubernetes namespace with the `-n` parameter.
 
 ## <a id="customconfig"></a> Custom configurations
 
@@ -215,9 +217,12 @@ After the deployment script has completed successfully, you can obtain the IP ad
 1. After the deployment, find the IP address of the controller endpoint by looking at the EXTERNAL-IP output of the following **kubectl** command:
 
    ```bash
-   kubectl get svc controller-svc-external -n <your-cluster-name>
+   kubectl get svc controller-svc-external -n <your-big-data-cluster-name>
    ```
 
+   > [!TIP]
+   > If you did not change the default name during deployment, use `-n mssql-cluster` in the previous command. **mssql-cluster** is the default name for the big data cluster.
+
 1. Log in to the big data cluster with **mssqlctl login**. Set the **--controller-endpoint** parameter to the external IP address of the controller endpoint.
 
    ```bash
@@ -262,7 +267,7 @@ minikube ip
 Irrespective of the platform you are running your Kubernetes cluster on, to get all the service endpoints deployed for the cluster, run following command:
 
 ```bash
-kubectl get svc -n <your-cluster-name>
+kubectl get svc -n <your-big-data-cluster-name>
 ```
 
 ## <a id="connect"></a> Connect to the cluster

docs/big-data-cluster/hdfs-tiering-mount-adlsgen2.md

@@ -98,7 +98,7 @@ Now that you have prepared a credential file with either access keys or using OA
 1. Use **kubectl** to find the IP Address for the endpoint **controller-svc-external** service in your big data cluster. Look for the **External-IP**.
 
    ```bash
-   kubectl get svc controller-svc-external -n <your-cluster-name>
+   kubectl get svc controller-svc-external -n <your-big-data-cluster-name>
    ```
 
 1. Log in with **mssqlctl** using the external IP address of the controller endpoint with your cluster username and password:

docs/big-data-cluster/hdfs-tiering-mount-s3.md

@@ -46,7 +46,7 @@ Now that you have prepared a credential file with access keys, you can start mou
 1. Use **kubectl** to find the IP Address for the endpoint **controller-svc-external** service in your big data cluster. Look for the **External-IP**.
 
    ```bash
-   kubectl get svc controller-svc-external -n <your-cluster-name>
+   kubectl get svc controller-svc-external -n <your-big-data-cluster-name>
    ```
 
 1. Log in with **mssqlctl** using the external IP address of the controller endpoint with your cluster username and password:

docs/big-data-cluster/quickstart-big-data-cluster-deploy.md

@@ -77,7 +77,7 @@ Use the following steps to run the deployment script. This script will create an
    | **Azure region** | The Azure region for the new AKS cluster (default **westus**). |
    | **Machine size** | The [machine size](https://docs.microsoft.com/azure/virtual-machines/windows/sizes) to use for nodes in the AKS cluster (default **Standard_L8s**). |
    | **Worker nodes** | The number of worker nodes in the AKS cluster (default **1**). |
-   | **Cluster name** | The name of both the AKS cluster and the big data cluster. The name of your cluster must be only lower case alpha-numeric characters, and no spaces. (default **sqlbigdata**). |
+   | **Cluster name** | The name of both the AKS cluster and the big data cluster. The name of your big data cluster must be only lower case alpha-numeric characters, and no spaces. (default **sqlbigdata**). |
    | **Password** | Password for the controller, HDFS/Spark gateway, and master instance (default **MySQLBigData2019**). |
    | **Controller user** | Username for the controller user (default: **admin**). |
 
@@ -113,7 +113,7 @@ After 10 to 20 minutes, you should be notified that the controller pod is runnin
 
 ## Inspect the cluster
 
-At any time during deployment, you can use kubectl or the Cluster Administration Portal to inspect the status and details about the running big data cluster.
+At any time during deployment, you can use **kubectl** or **mssqlctl** to inspect the status and details about the running big data cluster.
 
 ### Use kubectl
 
@@ -122,43 +122,33 @@ Open a new command window to use **kubectl** during the deployment process.
 1. Run the following command to get a summary of the status of the whole cluster:
 
    ```
-   kubectl get all -n <your-cluster-name>
+   kubectl get all -n <your-big-data-cluster-name>
    ```
 
+   > [!TIP]
+   > If you did not change the big data cluster name, the script defaults to **sqlbigdata**.
+
 1. Inspect the kubernetes services and their internal and external endpoints with the following **kubectl** command:
 
    ```
-   kubectl get svc -n <your-cluster-name>
+   kubectl get svc -n <your-big-data-cluster-name>
    ```
 
 1. You can also inspect the status of the kubernetes pods with the following command:
 
    ```
-   kubectl get pods -n <your-cluster-name>
+   kubectl get pods -n <your-big-data-cluster-name>
    ```
 
 1. Find out more information about a specific pod with the following command:
 
    ```
-   kubectl describe pod <pod name> -n <your-cluster-name>
+   kubectl describe pod <pod name> -n <your-big-data-cluster-name>
    ```
 
 > [!TIP]
 > For more details about how to monitor and troubleshoot a deployment, see [Monitoring and troubleshoot SQL Server big data clusters](cluster-troubleshooting-commands.md).
 
-### Use the Cluster Administration Portal
-
-Once the Controller pod is running, you can also use the Cluster Administration Portal to monitor the deployment. You can access the portal using the external IP address and port number for the `mgmtproxy-svc-external` (for example: **https://\<ip-address\>:30777/portal**). The credentials used to log into the portal match the values for **Controller user** and **Password** that you specified in the deployment script.
-
-You can get the IP address of the **mgmtproxy-svc-external** service by running this command in a bash or cmd window:
-
-```bash
-kubectl get svc mgmtproxy-svc-external -n <your-cluster-name>
-```
-
-> [!NOTE]
-> In CTP 3.0, you will see a security warning when accessing the web page, because big data clusters is currently using auto-generated SSL certificates.
-
 ## Connect to the cluster
 
 When the deployment script finishes, the output notifies you of success: