Building My Python Network Tester

Over the past couple of months, I’ve been tinkering with a side project: a Python Network Tester. The idea came directly from my time troubleshooting EKS and ECS solutions, where I often walked customers through a familiar set of network checks. While the tool may feel basic, it reflects the common gauntlet of tests I relied on whenever network concerns came up.

What I noticed in those scenarios was that, more often than not, the “network issue” wasn’t really the network at all. Instead, it was a misunderstanding of how networks behave—or how much application performance itself can influence perceived network performance. Sometimes, the simplest visibility into the basics is all someone needs to figure out their next step.

After plenty of tweaking, debugging, and refactoring, I’ve reached a point where I’m ready to share the project publicly.

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Using AI as a Programming Partner

One thing that helped me along the way was experimenting with Amazon’s Kiro Agentic AI. I often struggle with getting projects off the ground and into the right mindset, so I leaned on Kiro to help me draft code. But I made sure to carefully read every single line it suggested. That way, I understood exactly what the code was doing, which made refactoring and debugging much easier when things didn’t behave as expected.

In short, Kiro became a surprisingly good programming buddy. Beyond code, it was especially helpful for writing comments and documentation—an area I’ve always wrestled with, unsure if I’m writing too little or too much. Having that support gave me confidence to keep the docs clear and useful.

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Try It Out

If you’d like to explore the project yourself:

• GitHub Repository: Python Network Tester
• Docker Image (Linux/amd64): network-tester on Docker Hub

Feedback, recommendations, or issues are welcome—please report them in the GitHub Issues tab. I plan to keep iterating on this project to see what features make the most sense and where it can provide the most value.