Day 16 of my 90-Day Devops Project: Implementing Canary Deployment Project Guidelines

Today, I focused on setting up the basics for canary deployment.

Project Overview

In my day 16 project, I established a canary deployment for a simple web app with Docker and kubernetes (minikube). This method basically enables a phased feature rollout minimizing the risks associated with new releases.

My Folder Structure

Day15-canarydeployment/
│
├── app/
│   ├── app.py
│   ├── requirements.txt
│   └── Dockerfile
│
├── canary/
│   ├── canary.py
│   ├── requirements.txt
│   └── Dockerfile
│
├── deployment/
│   └── k8s/
│       ├── deployment.yaml
│       └── service.yaml
│
└── scripts/
    ├── deploy.sh
    └── monitor.sh

Steps to Complete the Project

Step 1: Application Setup

1. Create the Main Application

   • File: app/app.py

    from flask import Flask
   
    app = Flask(__name__)
   
    @app.route('/')
    def home():
        return "Main Application is running!"
   
    if __name__ == '__main__':
        app.run(host='0.0.0.0', port=5000)
   

• Dependencies: Create app/requirements.txt
  

   Flask==2.0.3
  

• Dockerize the Application: Create app/Dockerfile
  

   FROM python:3.9
  
   WORKDIR /app
  
   COPY requirements.txt .
   RUN pip install --no-cache-dir -r requirements.txt
  
   COPY app.py .
  
   EXPOSE 5000
   CMD ["python", "app.py"]
  

Step 2: Canary Application Setup

1. Create the Canary Application

   • File: canary/canary.py

    from flask import Flask
   
    app = Flask(__name__)
   
    @app.route('/')
    def home():
        return "Canary Application is running!"
   
    if __name__ == '__main__':
        app.run(host='0.0.0.0', port=5001)
   

• Dependencies: Create canary/requirements.txt
  

   Flask==2.0.3
  

• Dockerize the Canary Application: Create canary/Dockerfile
  

   FROM python:3.9-slim
  
   WORKDIR /app
  
   COPY requirements.txt .
   RUN pip install --no-cache-dir -r requirements.txt
  
   COPY canary.py .
  
   EXPOSE 5001
   CMD ["python", "canary.py"]
  

Step 3: Kubernetes Deployment

1. Define all Kubernetes Resources

   • Deployments: Create deployment/k8s/deployment.yaml

    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: main-app
    spec:
      replicas: 3
      selector:
        matchLabels:
          app: main-app
      template:
        metadata:
          labels:
            app: main-app
        spec:
          containers:
          - name: main-app
            image: your-docker-repo/main-app:latest
            ports:
            - containerPort: 5000
   
    ---
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: canary-app
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: canary-app
      template:
        metadata:
          labels:
            app: canary-app
        spec:
          containers:
          - name: canary-app
            image: your-docker-repo/canary-app:latest
            ports:
            - containerPort: 5001
   

• Services: Create deployment/k8s/service.yaml
  

   apiVersion: v1
   kind: Service
   metadata:
     name: main-app-service
   spec:
     type: ClusterIP
     selector:
       app: main-app
     ports:
       - port: 80
         targetPort: 5000
  
   ---
   apiVersion: v1
   kind: Service
   metadata:
     name: canary-app-service
   spec:
     type: ClusterIP
     selector:
       app: canary-app
     ports:
       - port: 81
         targetPort: 5001
  

Step 4: Deployment Scripts

1. Create Deployment Script

   • File: scripts/deploy.sh

    #!/bin/bash
   
    docker build -t your-docker-repo/main-app:latest ./app
    docker build -t your-docker-repo/canary-app:latest ./canary
   
    docker push your-docker-repo/main-app:latest
    docker push your-docker-repo/canary-app:latest
   
    kubectl apply -f deployment/k8s/
   

2. Monitoring Script

   • File: scripts/monitor.sh

    #!/bin/bash
   
    kubectl logs -l app=main-app
    kubectl logs -l app=canary-app
    kubectl get deployments
   

Note: kindly replace all placeholders with your actual details

Challenges and Solutions

Challenges Encountered

1. Minikube Not Installed:

   • Initially, Minikube wasn't recognized due to a PATH issue. To resolve this, I needed to configure the system PATH properly to ensure Minikube was accessible.

2. Existing Minikube Instance:

   • Minikube detected an existing instance, which prevented me from starting a new cluster. To resolve this, I used the command minikube delete to remove the existing instance, and then I was able to start a new Minikube cluster using minikube start.

3. kubectl Configuration:

   • To ensure kubectl could communicate with the Minikube cluster, I needed to configure the kubectl context to use Minikube by running the command kubectl config use-context minikube.

Solutions

1. Verify Minikube Installation:

   • I checked the Minikube version with the command minikube version to ensure it was properly installed.

2. Delete Existing Minikube Cluster:

   • The command minikube deletehelped to remove the existing Minikube instance, which allowed me to start a new cluster.

3. Check VirtualBox:

   • I also ensured that VirtualBox was properly installed and running, as Minikube relies on a virtual machine provided by VirtualBox.

4. Start Minikube:

   • After resolving the previous issues, I was able to start the Minikube cluster using the command minikube start.

5. Access Logs:

   • To troubleshoot any remaining issues, I checked the Minikube logs using the command minikube logs.

These steps helped me to resolve the challenges I faced during the setup of the Minikube environment for this project.

Expected Results

• Main Application: When you visit http://localhost:80, you should see the message:

  Main Application is running!

• Canary Application: When you visit http://localhost:81, you should see the message:

  Canary Application is running!

Conclusion

Canary deployment ensures a gradual rollout of new application features, allowing teams to collect feedback and
monitor performance before the full release. By addressing challenges with effective Solutions, you can reduce risks and maintain stability.
I think it's a great approach, as it helps identify areas for improvement and allows for changes to be made before a complete release.

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