Python Service Monitor

The Problem

Raw service data is not yet a decision. A small monitoring tool needs to accept measurements, evaluate them consistently, and return a result that another script or person can understand.

The Build

The project packages that logic into a reusable Python function. It evaluates service status and resource thresholds while keeping the code small enough to inspect, test, and improve as new Python concepts are learned.

Architecture

A deliberately simplified public view. Operational addresses, credentials, firewall rules, and recovery details are excluded.

Challenges

• Separating input data from evaluation logic.
• Returning a useful result instead of only printing output.
• Choosing readable state names and predictable branches.
• Avoiding unnecessary complexity in an early learning project.

What I Learned

Functions turn a one-off exercise into a reusable component. Parameters make the monitor useful for more than one service, return values let other code use the result, and explicit state makes the behavior easier to test.

Current Status

The core learning milestone is complete; the project remains in development as testing, error handling, and API integration are added.

Next Step

Add structured test cases, handle missing or invalid inputs, and publish the project with concise setup and usage documentation.

Evidence