Deploy a Python To-Do App with Flask, Kubernetes, and CockroachDB Cloud

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This tutorial shows you how to run a sample To-Do app in Kubernetes with CockroachDB Dedicated as the datastore. The app is written in Python with Flask as the web framework and SQLAlchemy for working with SQL data, and the code is open-source and forkable.

Before you begin

1. If you haven't already, sign up for a CockroachDB Cloud account.

2. Install the following tools, if you do not already have them:

   Tool	Purpose
   pip	You'll need pip to install SQLAlchemy and a CockroachDB Python package that accounts for some differences between CockroachDB and PostgreSQL.
   Docker	You'll dockerize your application for running in Kubernetes.
   minikube	This is the tool you'll use to run Kubernetes locally, for your OS. This includes installing a hypervisor and kubectl, the command-line tool used to manage Kubernetes from your local workstation.

3. If you haven't already, create a CockroachDB Dedicated cluster.

Prepare your cluster

• Step 1. Authorize your local workstation's network
• Step 2. Create a SQL user
• Step 3. Connect to the cluster
• Step 4. Create the CockroachDB Dedicated database
• Step 5. Generate the application connection string

Step 1. Authorize your local workstation's network

Before you connect to your CockroachDB Dedicated cluster, you need to authorize your network (i.e., add the public IP address of the workstation to the allowlist). Otherwise, connections from this workstation will be rejected.

Once you are logged in, you can use the Console to authorize your network:

1. In the left navigation bar, click Networking.
2. Click the Add Network button in the right corner. The Add Network dialog displays.
3. (Optional) Enter a descriptive name for the network.
4. From the Network dropdown, select Current Network. Your local machine's IP address will be auto-populated in the box.

5. Select both networks: DB Console to monitor the cluster and CockroachDB Client to access the databases.

   The DB Console refers to the cluster's DB Console, where you can observe your cluster's health and performance. For more information, see DB Console Overview.

6. Click Apply.

Step 2. Create a SQL user

1. In the left navigation bar, click SQL Users.
2. Click Add User. The Add User dialog displays.
3. Enter a username and click Generate & Save Password.
4. Copy the generated password to a secure location, such as a password manager.

5. Click Close.

   Currently, all new SQL users are created with admin privileges. For more information and to change the default settings, see Managing SQL users on a cluster.

Step 3. Connect to the cluster

In this step, you connect both your application and your local system to the cluster.

1. In the top right corner of the CockroachDB Cloud Console, click the Connect button.

   The Setup page of the Connect to cluster dialog displays.

2. Select the SQL User you created in Step 2. Create a SQL user.

3. For Database, select defaultdb. You will change this after you follow the instructions in Step 4. Create the database.

4. Click Next.

   The Connect page of the Connection info dialog displays.

5. Select the Command Line tab.

6. If CockroachDB is not installed locally, copy the command to download and install it. In your terminal, run the command.

7. Select the Connection string tab.

8. If the CA certificate for the cluster is not downloaded locally, copy the command to download it. In your terminal, run the command.

9. Copy the connection string, which begins with postgresql://. This will be used to connect your application to CockroachDB Dedicated.

10. Click Close.

11. Use the connection string to connect to the cluster using cockroach sql:

    cockroach sql --url 'postgresql://<user>@<cluster-name>-<short-id>.<region>.cockroachlabs.cloud:26257/<database>?sslmode=verify-full&sslrootcert='$HOME'/Library/CockroachCloud/certs/<cluster-name>-ca.crt'
    

    cockroach sql --url 'postgresql://<user>@<cluster-name>-<short-id>.<region>.cockroachlabs.cloud:26257/<database>?sslmode=verify-full&sslrootcert='$HOME'/Library/CockroachCloud/certs/<cluster-name>-ca.crt'
    

    cockroach sql --url "postgresql://<user>@<cluster-name>-<short-id>.<region>.cockroachlabs.cloud:26257/<database>?sslmode=verify-full&sslrootcert=$env:appdata\CockroachCloud\certs\$<cluster-name>-ca.crt"
    

    Where:

    • <user> is the SQL user. By default, this is your CockroachDB Cloud account username.
    • <cluster-name>-<short-id> is the short name of your cluster plus the short ID. For example, funny-skunk-3ab.
    • <cluster-id> is a unique string used to identify your cluster when downloading the CA certificate. For example, 12a3bcde-4fa5-6789-1234-56bc7890d123.
    • <region> is the region in which your cluster is running. If you have a multi-region cluster, you can choose any of the regions in which your cluster is running. For example, aws-us-east-1.
    • <database> is the name for your database. For example, defaultdb.

    You can find these settings in the Connection parameters tab of the Connection info dialog.

Step 4. Create the database

On your local workstation's terminal:

1. Use the cockroach sql from Step 3. Connect to the cluster to connect to the cluster using the binary you just configured.

2. Create a database todos:

   > CREATE DATABASE todos;
   

3. Use database todos:

   > USE todos;
   

4. Create a table todos:

   > CREATE TABLE todos (
       todo_id INT8 NOT NULL DEFAULT unique_rowid(),
       title VARCHAR(60) NULL,
       text VARCHAR NULL,
       done BOOL NULL,
       pub_date TIMESTAMP NULL,
       CONSTRAINT "primary" PRIMARY KEY (todo_id ASC),
       FAMILY "primary" (todo_id, title, text, done, pub_date)
     );
   

Step 5. Generate the application connection string

1. In the top right corner of the Console, click the Connect button.

   The Connect dialog displays.

2. From the User dropdown, select the SQL user you created in Step 2.

3. Select a Region to connect to.

4. From the Database dropdown, select todos.

5. On the Connection String tab, click Copy connection string.

   Copy the application connection string to an accessible location. You will update the password and certificate path in the next step.

Build the app

• Step 1. Configure the sample Python app
• Step 2. Test the application locally

Step 1. Configure the sample Python app

In a new terminal:

1. Clone the examples-python repository to your local machine:

   $ git clone https://github.com/cockroachdb/examples-python
   

2. Navigate to the flask-alchemy folder:

   $ cd examples-python/flask-sqlalchemy
   

3. In the hello.cfg file, replace the value for the SQLALCHEMY_DATABASE_URI with the application connection string you generated in Step 5. Generate the application connection string and save the file.

   SQLALCHEMY_DATABASE_URI = 'cockroachdb://<username>@<host>:26257/todos?sslmode=verify-full&sslrootcert=$Home/Library/CockroachCloud/certs/<cluster-name>-ca.crt'
   

   Note:

   You must use the cockroachdb:// prefix in the URL passed to sqlalchemy.create_engine to make sure the cockroachdb dialect is used. Using the postgres:// URL prefix to connect to your CockroachDB cluster will not work.

   Copy the application connection string to an accessible location since you need it to configure the sample application in the next step.

Step 2. Test the application locally

1. Install SQLAlchemy, as well as a CockroachDB Python package that accounts for some differences between CockroachDB and PostgreSQL:

   $ pip install flask sqlalchemy sqlalchemy-cockroachdb Flask-SQLAlchemy
   

   For other ways to install SQLAlchemy, see the official documentation.

2. Run the hello.py code:

   $ python hello.py
   

   The application should run at http://localhost:5000.

3. Enter a new to-do item.

4. Verify that the user interface reflects the new to-do item added to the database.

5. Use Ctrl+C to stop the application.

Deploy the app

• Step 1. Start a local Kubernetes cluster
• Step 2. Create a Kubernetes secret
• Step 3. Change certificate directory path in configuration file
• Step 4. Dockerize the application
• Step 5. Deploy the application

Step 1. Start a local Kubernetes cluster

On your local workstation's terminal:

$ minikube start

The startup procedure might take a few minutes.

Step 2. Create a Kubernetes secret

Create a Kubernetes secret to store the CA certificate you downloaded earlier:

$ kubectl create secret generic <username>-secret --from-file $Home/Library/CockroachCloud/certs/<cluster-name>-ca.crt

Verify the Kubernetes secret was created:

$ kubectl get secrets

NAME                  TYPE                                  DATA   AGE
default-token-875zk   kubernetes.io/service-account-token   3      75s
<username>-secret       Opaque                                1      10s

Step 3. Change certificate directory path in configuration file

In the hello.cfg file in the flask-alchemy folder, replace the certificate directory path from the default location to /data/certs and save the file.

SQLALCHEMY_DATABASE_URI = 'cockroachdb://<username>@<host>:26257/todos?sslmode=verify-full&sslrootcert=$Home/Library/CockroachCloud/certs/<cluster-name>-ca.crt'

Step 4. Dockerize the application

1. In the flask-sqlalchemy folder, create a file named Dockerfile and copy the following code into the file:

   FROM python:3.7-slim
   
   WORKDIR /app
   
   ADD . /app
   
   RUN apt-get update && apt-get install -y libpq-dev gcc
   # need gcc to compile psycopg2
   RUN pip3 install psycopg2~=2.6
   RUN apt-get autoremove -y gcc
   RUN pip install --trusted-host pypi.python.org -r requirements.txt
   
   EXPOSE 80
   
   CMD ["python", "hello.py"]
   

2. Set the environment variable:

   $ eval $(minikube docker-env)
   

3. Create the Docker image:

   $ docker build -t appdocker .
   

4. Verify the image was created:

   $ docker image ls
   

   REPOSITORY         TAG             IMAGE ID            CREATED             SIZE
   appdocker          latest          cfb155afed03        3 seconds ago       299MB
   

Step 5. Deploy the application

1. In the flask-alchemy folder, create a file named app-deployment.yaml and copy the following code into the file. Replace the <username> placeholder with the SQL user's username that you created while preparing the cluster:

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: appdeploy
     labels:
       app: flask
   spec:
     selector:
       matchLabels:
         app: flask
     replicas: 3
     strategy:
       type: RollingUpdate
     template:
       metadata:
         labels:
           app: flask
       spec:
         containers:
         - name: appdeploy
           image: appdocker
           imagePullPolicy: Never
           ports:
           - containerPort: 80
           volumeMounts:
           - mountPath: "/data/certs"
             name: ca-certs
             readOnly: true
         volumes:
         - name: ca-certs
           secret:
             secretName: <username>-secret
   ---
   apiVersion: v1
   kind: Service
   metadata:
     name: appdeploy
     labels:
       app: flask
   spec:
     ports:
     - port: 80
       protocol: TCP
       name: flask
     selector:
       app: flask
     type: LoadBalancer
   

2. Create the deployment with kubectl:

   $ kubectl apply -f app-deployment.yaml
   

   deployment.apps/appdeploy created
   service/appdeploy created
   

3. Verify that the deployment and server were created:

   $ kubectl get deployments
   

   NAME           READY   UP-TO-DATE   AVAILABLE   AGE
   appdeploy      3/3     3            3           27s
   

   $ kubectl get services
   

   NAME         TYPE           CLUSTER-IP      EXTERNAL-IP   PORT(S)        AGE
   appdeploy    LoadBalancer   10.96.154.104   <pending>     80:32349/TCP   42s
   

4. Start the app:

   $ minikube service appdeploy
   

   The application will open in the browser. If you get a refused to connect message, use port-forwarding to reach the application:

   1. Get the name of one of the pods:

      $ kubectl get pods
      

      NAME                         READY   STATUS              RESTARTS   AGE
      appdeploy-577f66b4c8-46s5r   0/1     ErrImageNeverPull   0          23m
      appdeploy-577f66b4c8-9chjx   0/1     ErrImageNeverPull   0          23m
      appdeploy-577f66b4c8-cnhrg   0/1     ErrImageNeverPull   0          23m
      

   2. Port-forward from your local machine to one of the pods:

      $ kubectl port-forward appdeploy-5f5868f6bf-2cjt5 5000:5000
      

      Forwarding from 127.0.0.1:5000 -> 5000
      Forwarding from [::1]:5000 -> 5000
      

   3. Go to http://localhost:5000/ in your browser.

Monitor the app

• Step 1. Access the DB Console
• Step 2. Monitor cluster health, metrics, and SQL statements

Step 1. Access the DB Console

1. On the Console, navigate to the cluster's Tools page and click Open DB Console.

   You can also access the DB Console by navigating to https://<cluster-name>crdb.io:8080/#/metrics/overview/cluster. Replace the <cluster-name> placeholder with the name of your cluster.

2. Enter the SQL user's username and password you created while preparing the cluster.

   Warning:

   PostgreSQL connection URIs do not support special characters. If you have special characters in your password, you will have to URL encode them (e.g., password! should be entered as password%21) to connect to your cluster.

3. Click Log In.

Step 2. Monitor cluster health, metrics, and SQL statements

On the Cluster Overview page, view essential metrics about the cluster's health:

• Number of live, dead, and suspect nodes
• Number of unavailable and under-replicated ranges
• Queries per second
• Service latency across the cluster

Monitor the hardware metrics

1. Click Metrics on the left, and then select Dashboard > Hardware.
2. On the Hardware dashboard, view metrics about CPU usage, disk throughput, network traffic, storage capacity, and memory.

Monitor inter-node latencies

1. Click Network Latency in the left-hand navigation to check latencies between all nodes in your cluster.

Identify frequently executed or high latency SQL statements

1. Click Statements on the left.
2. The Statements page helps you identify frequently executed or high latency SQL statements. The Statements page also allows you to view the details of an individual SQL statement by clicking on the statement to view the Statement Details page.

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