This project provides a way to monitor system memory usage and trigger an alert if memory usage exceeds a predefined threshold. The alert is sent as an HTTP request to a Flask API, which then processes and acknowledges the alert.

1. Memory Monitor Script (monitor.py): A Python script that continuously checks the system's memory usage using the psutil library. If the memory usage exceeds the set threshold, it sends an alert to the Flask API.

2. Flask API (app.py): A Flask-based REST API that listens for alerts from the monitor script. It provides an endpoint (/receive-alert) to receive and acknowledge memory usage alerts.

3. Docker & Docker Compose: The project uses Docker to containerize the Flask API and a MongoDB database. Docker Compose is used to manage and orchestrate these containers.

• Docker and Docker Compose installed.
• Python 3.x with pip for running the memory monitor script.

1. Clone the repository:

   git clone [repository_url] memory_usage_alert
   cd memory_usage_alert

2. Build and Start the Containers:

   sudo docker-compose up --build

3. Run the Memory Monitor Script: In a separate terminal:

   cd monitor
   pip install -r requirements.txt
   python monitor.py

4. Testing: The Flask API provides a /value endpoint for CRUD operations with key-value pairs stored in the MongoDB database. You can use tools like curl or Postman to test these endpoints.

• Memory Threshold: The memory usage threshold after which an alert is sent is defined in monitor.py as MEMORY_THRESHOLD. By default, it's set to 40%.

• API URL: The Flask API endpoint to which the monitor script sends alerts is defined in monitor.py as API_URL. It's set to http://localhost:8080/receive-alert by default.

1. Docker Issues: If you face issues with Docker or Docker Compose, ensure that the Docker daemon is running. Restarting the Docker service or rebooting the system can resolve many common issues.

2. Connection Issues: Ensure that the Flask API is running and accessible if the monitor script cannot send alerts. Check the Docker logs for any errors.

3. Dependencies: Ensure that all Python dependencies are installed, both for the Flask API (in the Docker container) and the memory monitor script.