Deploying a Python App built with (Flask and psutil) to ECR and Kubernetes

Cloud-Native-Monitoring-App

GITHUB LINK
This is a monitoring app built with Python, and it would be containerized with Docker and deployed to AWS EKS (Amazon Elastic Kubernetes Service).

Acquire

  • Learn Docker and How to containerize a Python application

  • Creating Dockerfile

  • Building DockerImage

  • Running Docker Container

  • Docker Commands

  • Create an ECR repository using Python Boto3 and push Docker Image to ECR

  • Learn Kubernetes and Create EKS cluster and Node groups

  • Create Kubernetes Deployments and Services using Python!

STEP 1 — Installations of Services on your WorkStation

  • Install AWS CLI, then Go to your AWS account and get your secret keys, and configure the workspace aws configure

  • Install Python on your workstation and a Python extension in vscode

  • The application uses the `psutil` and `Flask`, Plotly, boto3 libraries. Install them using pip pip3 install -r requirements.txt

  • Install dependencies psutil pip3 install psutil and flask pip install flask

  • Install Python for ECR SDK pip install boto3

  • Install Kubernetes, add the K8S python dependencies client library pip install Kubernetes and the extension of Kubernetes in vscode

  • Install the docker extension in vscode

Step 2: Run the application

Create requirement.txt file then Install them using pip pip3 install -r requirements.txt

Flask==2.2.3
MarkupSafe==2.1.2
Werkzeug==2.2.3
itsdangerous==2.1.2
psutil==5.8.0
plotly==5.5.0
tenacity==8.0.1
boto3==1.9.148
kubernetes==10.0.1

To run the application, navigate to the root directory of the project and execute the following command:

$ python3 app.py

This will start the Flask server on `localhost:5000`. Navigate to localhost:5000 on your browser to access the application.

Step 3: Dockerizing the Flask application

  • Create a Dockerfile in the root directory of the project with the following contents:
# Use the official Python image as the base image
FROM python:3.9-slim-buster

# Set the working directory in the container
WORKDIR /app

# Copy the requirements file to the working directory
COPY requirements.txt .

RUN pip3 install --no-cache-dir -r requirements.txt

# Copy the application code to the working directory
COPY . .

# Set the environment variables for the Flask app
ENV FLASK_RUN_HOST=0.0.0.0

# Expose the port on which the Flask app will run
EXPOSE 5000

# Start the Flask app when the container is run
CMD ["flask", "run"]
  • Build the Docker image, and execute the following command:
$ docker build -t <image_name> .
  • Run the Docker container, and execute the following command:
$ docker run -p 5000:5000 <image_name>

This will start the Flask server in a Docker container on localhost:5000. Navigate to localhost:5000 on your browser to access the application.

Step 4 — Pushing the Docker image to ECR

  • Create an ECR repository using Python in a folder ecr.py:

  • Configure the ECR repository to your workspace to enable a push, you will find the process in the console view push commands

import boto3

# Create an ECR client
ecr_client = boto3.client('ecr')

# Create a new ECR repository
repository_name = 'my-ecr-repo'
response = ecr_client.create_repository(repositoryName=repository_name)

# Print the repository URI
repository_uri = response['repository']['repositoryUri']
print(repository_uri)

Then run this python3 ecr.py

  • Push the Docker image to ECR using the push commands on the console:
$ docker push <ecr_repo_uri>:<tag>

Step 5 — Creating an EKS cluster and deploying the app using Python

  • Create an EKS cluster cloud-native-cluster and add a node group in the AWS console

  • Create a node group nodes in the EKS cluster.

  • Create deployment and service in a folder eks.py

from kubernetes import client, config

# Load Kubernetes configuration
config.load_kube_config()

# Create a Kubernetes API client
api_client = client.ApiClient()

# Define the deployment
deployment = client.V1Deployment(
    metadata=client.V1ObjectMeta(name="my-flask-app"),
    spec=client.V1DeploymentSpec(
        replicas=1,
        selector=client.V1LabelSelector(
            match_labels={"app": "my-flask-app"}
        ),
        template=client.V1PodTemplateSpec(
            metadata=client.V1ObjectMeta(
                labels={"app": "my-flask-app"}
            ),
            spec=client.V1PodSpec(
                containers=[
                    client.V1Container(
                        name="my-flask-container",
                        image="568373317874.dkr.ecr.us-east-1.amazonaws.com/my-cloud-native-repo:latest",
                        ports=[client.V1ContainerPort(container_port=5000)]
                    )
                ]
            )
        )
    )
)

# This is an automation to run deployment and svc using python
# Create the deployment
api_instance = client.AppsV1Api(api_client)
api_instance.create_namespaced_deployment(
    namespace="default",
    body=deployment
)

# Define the service
service = client.V1Service(
    metadata=client.V1ObjectMeta(name="my-flask-service"),
    spec=client.V1ServiceSpec(
        selector={"app": "my-flask-app"},
        ports=[client.V1ServicePort(port=5000)]
    )
)

# Create the service
api_instance = client.CoreV1Api(api_client)
api_instance.create_namespaced_service(
    namespace="default",
    body=service
)
  • make sure to edit the name of the image on line 25 with your image Url.

To run the K8s commands for deployment and service instead of adding the python script you create deployment.yml and service.yml use these commands `kubectl apply -f deployment.yml` and `kubectl apply -f service.yml`

  • Configure the AWS EKS to your workspace
aws eks update-kubeconfig - name cloud-native-cluster
  • Once you run this file by running python3 eks.py deployment and service will be created.

  • Check by running the following commands:

kubectl get deployment -n default (check deployments)
kubectl get service -n default (check service)
kubectl get pods <name of pod> -n default (to check the pods)

#edit images created if u made errors
kubectl edit deployment my-flask-app -n default 

#this will pull down the editted image
kubectl get pod -n default -w

Once your pod is up and running, run the port-forward to expose the service

kubectl port-forward service/<service_name> 5000:5000

⭐ Your app should be live. ⭐

✍️ Author by Harshhaa.