Deploy MSSQL in the Kyma Runtime

1. Go to the kyma-runtime-extension-samples repository. This repository contains a collection of Kyma sample applications which will be used during the tutorial.

2. Download the code by choosing the green Code button, and then choosing one of the options to download the code locally.

   You can instead run the following command using your CLI at your desired folder location:

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   git clone https://github.com/SAP-samples/kyma-runtime-extension-samples
   

1. Open the database-mssql directory in your desired editor.

2. Explore the content of the sample.

3. Within the app folder you can find the configuration files for setting up the sample DemoDB database within the Docker image.

   The process includes defining the database password as well as the creation of the Orders table with sample data.

4. Within the docker folder you can find the Dockerfile, which is a text-based set of instructions that is used to create a container image. Notice how the last command references the entrypoint.sh script defined within the app directory which is used to call the commands to configure the sample database.

5. Within the k8s folder you can find the resource definitions that will be used to deploy the sample to the Kyma runtime. This includes the deployment.yaml which specifies the microservice definition of the MSSQL database and also a service definition which exposes the microservice to other resources within the cluster. The pvc.yaml specifies a persistent volume claim which is used to request a storage location for the data of the database. The secret.yaml contains the database user and password.

A Docker container image is a lightweight, standalone, executable package of software that includes everything needed to run an application: code, runtime, system tools, system libraries and settings. In this step, you will build a mssql image according to the Dockerfile definition contained in the docker folder. Make sure to run the following commands from the database-mssql directory using your CLI, and also replace the value of <your-docker-id> with your Docker account ID.

1. To build the Docker image, run this command:

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   docker build -t <your-docker-id>/mssql -f docker/Dockerfile .
   

2. To push the Docker image to your Docker repository, run this command:

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   docker push <your-docker-id>/mssql
   

Make sure to replace the value of <your-docker-id> with your Docker account ID.

1. Start the image locally by running the following command. The start up will take about two minutes due to the scripts that run to initialize the database.

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   docker run -e ACCEPT_EULA=Y -e SA_PASSWORD=Yukon900 -p 1433:1433 --name sql1 -d <your-docker-id>/mssql
   

2. Open a bash shell within the image by running this command:

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   docker exec -it sql1 "bash"
   

3. Start the sqlcmd tool, which allows you to run queries against the database, by running this command:

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   /opt/mssql-tools/bin/sqlcmd -S localhost -U SA -P Yukon900
   

4. Enter a query by entering this command:

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   USE DemoDB SELECT * FROM ORDERS
   

5. The query can now be executed by entering this command:

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   GO
   

6. End the sqlcmd session by running:

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   exit
   

7. End the bash session by running:

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   exit
   

8. Shutdown the Docker container by running this command:

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   docker stop sql1
   

9. Here are some additional commands that can be used:

   To start the container again, run:

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   docker start sql1
   

   The container can be removed by running:

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   docker rm sql1
   

   To list all local containers existing:

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   docker container ls -a
   

   To list out all local images existing

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   docker images
   

You can find the resource definitions in the k8s folder. If you performed any changes in the database configuration, these files may also need to be updated. The folder contains the following files:

• secret.yaml: defines the database password and user which is base64-encoded.
• pvc.yaml: defines a PersistentVolume used to store the data of the database.
• deployment.yaml: defines the Deployment definition for the MSSQL database as well as a Service used for communication. This definition references both the secret.yaml and pvc.yaml by name.

Run the following commands from the database-mssql directory using your CLI.

1. Start by creating the dev Namespace if it doesn’t already exist:

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   kubectl create namespace dev
   

   Namespaces separate objects inside a Kubernetes cluster. Choosing a different namespace will require adjustments to the provided samples.

2. Apply the PersistentVolumeClaim:

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   kubectl -n dev apply -f ./k8s/pvc.yaml
   

3. Apply the Secret:

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   kubectl -n dev apply -f ./k8s/secret.yaml
   

4. Within the deployment.yaml, adjust the value of spec.template.spec.containers.image, commented with #change it to your image, to use your Docker image. Apply the Deployment:

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   kubectl -n dev apply -f ./k8s/deployment.yaml
   

5. Verify the Pod is up and running:

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   kubectl -n dev get po
   

   This command results in a table similar to the one below, showing a Pod with the name mssql- ending with a random hash. The STATUS will display Running when the Pod is up and running.

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   NAME                                     READY   STATUS    RESTARTS   AGE
   mssql-6df65c689d-qdj4r        2/2     Running   0          93s
   

Kubernetes provides a port-forward functionality that allows you to connect to resources running in the Kyma runtime locally. This can be useful for development and debugging tasks. Make sure to adjust the name of the Pod in the following commands to match your own.

1. Confirm the port on which the Pod is listening:

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   kubectl get pod mssql-6df65c689d-qdj4r -n dev -o jsonpath="{.spec.containers[*].ports}"
   

   This command should return the ports of two containers existing within the pod:

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   [{"containerPort":15090,"name":"http-envoy-prom","protocol":"TCP"}] [{"containerPort":1433,"protocol":"TCP"}]
   

2. Apply the port-forward to the Pod using the port 1433 used by the MSQL Deployment:

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   kubectl port-forward mssql-6df65c689d-qdj4r -n dev 1433:1433
   

   This command should return:

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   Forwarding from 127.0.0.1:1433 -> 1433
   Forwarding from [::1]:1433 -> 1433
   

3. At this point, a tool such as sqlcmd or a development project running on your computer can access the database running in the Kyma runtime using localhost:1433.

4. To end the process, use CTRL+C.

Similarly to how the Docker image can be accessed locally, you can perform the same on the Deployment running in the Kyma runtime. Make sure to adjust the name of the Pod in the following commands to match your own.

1. By default, a Pod includes the denoted Deployments defined in the yaml definition as well as the istio-proxy. For the mssql Deployment, this means there will be two containers in the Pod.

   The describe command can be used to view this information.

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   kubectl describe pod mssql-6df65c689d-qdj4r -n dev
   

2. Run the following command to obtain a bash shell.

   If any adjustments where made to the name of the MSSQL deployment, adjust the name of the container denoted by the -c option.

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   kubectl exec -it mssql-6df65c689d-qdj4r -n dev -c mssql -- bash
   

   This may output the following message which can be ignored: groups: cannot find name for group ID 1337

3. To run the sqlcmd tool, which allows you to run queries against the database, run this command:

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   /opt/mssql-tools/bin/sqlcmd -S 127.0.0.1 -U SA -P Yukon900
   

4. The commands performed in [Step 4: ](Use the Docker image locally) to query the database can now be used in the same fashion.