updated login endpoint to controller-svc-external

samples/features/sql-big-data-cluster/app-deploy/RollDice/README.md

@@ -41,10 +41,10 @@ To run this sample, you need the following prerequisites.
 ## Run this sample
 
 1. Clone or download this sample on your computer.
-2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
+2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
 
     ```bash
-    azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
+    azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name> -p <password>
     ```
 3. Deploy the application by running the following command, specifying the folder where your `spec.yaml` and `roll-dice.R` files are located:
     ```bash

samples/features/sql-big-data-cluster/app-deploy/SSIS/README.md

@@ -32,10 +32,10 @@ To run this sample, you need the following prerequisites.
 ## Run this sample
 
 1. Clone or download this sample on your computer.
-2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
+2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
 
     ```bash
-    azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
+    azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
     ```
 3. Replace `[SA_PASSWORD]` in the `spec.yaml` file with the password for SQL user `sa`.
 4. Deploy the application by running the following command, specifying the folder where your `spec.yaml` and `back-up-db.dtsx` files are located:

samples/features/sql-big-data-cluster/app-deploy/addpy/README.md

@@ -42,10 +42,10 @@ To run this sample, you need the following prerequisites.
 ## Run this sample
 
 1. Clone or download this sample on your computer.
-2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
+2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
 
     ```bash
-    azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
+    azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
     ```
 3. Deploy the application by running the following command, specifying the folder where your `spec.yaml` and `add.py` files are located:
     ```bash

samples/features/sql-big-data-cluster/app-deploy/magic8ball/README.md

@@ -41,10 +41,10 @@ To run this sample, you need the following prerequisites.
 ## Run this sample
 
 1. Clone or download this sample on your computer.
-2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
+2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
 
     ```bash
-    azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
+    azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
     ```
 3. Deploy the application by running the following command, specifying the folder where your `spec.yaml` and `magic8ball.py` files are located:
     ```bash

samples/features/sql-big-data-cluster/app-deploy/mleap/README.md

@@ -38,10 +38,10 @@ To run this sample, you need the following prerequisites.
 ## Run this sample
 
 1. Clone or download this sample on your computer.
-2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
+2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
 
    ```bash
-   azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
+   azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
    ```
 3. This example uses a TensorFlow Machine Learning Model that uses public US Census data predict income. [More details and information on the example are here](https://docs.microsoft.com/en-us/sql/big-data-cluster/train-and-create-machinelearning-models-with-spark?view=sqlallproducts-allversions). The application you will be deploying as part of this sample is a Random Forest Model that was built in Spark and has been [serialized as an MLeap bundle](https://docs.microsoft.com/en-us/sql/big-data-cluster/export-model-with-spark-mleap?view=sqlallproducts-allversions).
 

samples/features/sql-big-data-cluster/app-deploy/sentiment-analysis/README.md

@@ -42,10 +42,10 @@ To run this sample, you need the following prerequisites.
 ## Run this sample
 
 1. Clone or download this sample on your computer.
-2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
+2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
 
     ```bash
-    azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
+    azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
     ```
 3. Deploy the application by running the following command, specifying the folder where your `spec.yaml`, `sentiment.rds` and `sentiment.R` files are located:
     ```bash

samples/features/sql-big-data-cluster/app-deploy/sumofsq/README.md

@@ -42,10 +42,10 @@ To run this sample, you need the following prerequisites.
 ## Run this sample
 
 1. Clone or download this sample on your computer.
-2. Log in to the SQL Server big data cluster using the command below using the IP address of the `mgmtproxy-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
+2. Log in to the SQL Server big data cluster using the command below using the IP address of the `controller-svc-external` in your cluster. If you are not familiar with `mssqltctl` you can refer to the [documentation](https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-create-apps?view=sqlallproducts-allversions) and then return to this sample.
 
     ```bash
-    azdata login -e https://<ip-address-of-mgmtproxy-svc-external>:30777 -u <user-name> -p <password>
+    azdata login -e https://<ip-address-of-controller-svc-external>:30080 -u <user-name>
     ```
 3. Deploy the application by running the following command, specifying the folder where your `spec.yaml` and `sum_of_squares.R` files are located:
     ```bash