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Building a Cloud Monitoring Application with Flask, Docker, and Azure

Updated: at 03:00 PM

This post explains how to build and deploy a cloud-native monitoring application using Flask, Docker, and Azure. The application provides real-time metrics such as CPU usage, memory, and disk utilization. You can view the live demo here: Cloud Monitoring App.

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Introduction

Monitoring systems ensure the performance and reliability of distributed applications. This project leverages Flask for the backend, Docker for containerization, and Azure App Service for scalable hosting. The application tracks:

Tech Stack

Tool/TechnologyPurpose
FlaskBackend framework for creating the application
DockerContainerization of the application for portability
Azure App ServiceHosting the containerized application
Python psutilFetching real-time system metrics
HTML/CSSFrontend interface for displaying metrics

Code Implementation

Here’s the core Flask code for the monitoring application:

app.py

from flask import Flask, render_template
import psutil

app = Flask(__name__)

@app.route("/")
def index():
    cpu_usage = psutil.cpu_percent(interval=1)
    memory_info = psutil.virtual_memory()
    disk_info = psutil.disk_usage("/")
    return render_template(
        "index.html",
        cpu_usage=cpu_usage,
        memory_info=memory_info,
        disk_info=disk_info,
    )

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=8080)