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Task Details

Objective

The objective of this task is to assess your skills in application development, containerization, Kubernetes deployment, monitoring, and automation.

Task Requirements

  1. Develop a Python Application:

    • Create a Python application that checks if google.com is up and running.
    • The application should expose a web interface that shows whether google.com is "Up" or "Down".

  2. Containerize the Application:

    • Write a Dockerfile to containerize the Python application.
    • Ensure the container runs with minimal dependencies.

  3. Deploy on Kubernetes:

    • Use the Kubernetes cluster provided by Docker Desktop.
    • Create Kubernetes manifests to deploy the containerized application:
      • Deployment: Define the deployment specifications for the application.
      • Service: Expose the application as a service within the cluster.

  4. Monitoring Setup:

    • Configure monitoring for the application using Prometheus and Grafana.
    • Collect basic metrics like request count, response status, and latency.
    • Include Kubernetes manifests or configurations to deploy Prometheus and Grafana in the same cluster.

  5. Automation Script:

    • Create a shell script (deploy.sh) that:
      • Sets up the entire environment (deploys the application and monitoring).
      • Tears down the environment (removes all resources).
    • Ensure the script is idempotent and can be run multiple times without issues.

Task Instructions

  1. Application Development:

    • Write a Python script that performs an HTTP check on google.com.
    • The script should return a simple HTML page saying "Google is Up" or "Google is Down" based on the HTTP response.
    • Use a lightweight web framework like Flask to handle HTTP requests.

  2. Dockerize the Application:

    • Create a Dockerfile in the docker/ folder.
    • Ensure the image is as lightweight as possible, focusing on a small footprint and efficiency.
    • Build and run the container locally to verify its functionality before proceeding.

  3. Kubernetes Deployment:

    • Create the following Kubernetes manifests in the k8s/ folder:
      • deployment.yaml: Defines the Deployment for the application.
      • service.yaml: Defines a Service to expose the application within the cluster.
    • Deploy these resources on Docker Desktop’s Kubernetes cluster to confirm they work as expected.

  4. Monitoring Setup:

    • Create a monitoring.yaml in the k8s/ folder.
    • This file should:
      • Set up Prometheus to scrape metrics from the application.
      • Deploy Grafana for visualizing the metrics.
    • Verify that Prometheus can collect and Grafana can display metrics like application uptime, request count, and latency.

  5. Automation Script:

    • Create a shell script named deploy.sh in the scripts/ folder.
    • The script should:
      • Deploy the application, service, and monitoring components in the Kubernetes cluster.
      • Include commands to set up and tear down the environment.
      • Be able to both start and stop the entire setup with a single command.