I spent a year learning Go, but I switched back to Python.
Why? It made it easier to get a job.
In my early DevOps years, I used Python every day. But I wanted to learn Go because so much modern DevOps runs on it.
WHAT I FOUND LEARNING GO
Kubernetes and many cloud tools are built in Go. Most projects are huge and hard to fully understand if you don't write code full time.
Now I use AI to help me read Go when I need it.
Learning Go was still worth it:
- Strict typing
- Memory control
- Fast single binaries
Why I came back to Python:
- More jobs here in the Netherlands need Python
- Easy to learn but has depth
- Huge community and libraries
- AI and ML run on Python with PyTorch and NumPy
In daily DevOps I write scripts, APIs and small tools. Python does all of this well.
It keeps me flexible and ready for the AI side too.
WHY BOTH LANGUAGES MATTER
Both languages matter:
- Go runs so much infrastructure
- Python keeps me productive and open to more work
Here's what I actually build with Python in my daily DevOps work:
- Automation scripts
- APIs for internal tools
- Small utilities and tools
- AI/ML integrations when needed
WHAT I LEARNED FROM THIS EXPERIENCE
Both languages matter, but in different ways:
- Go runs so much infrastructure we depend on
- Python keeps me productive and employable
I still use my Go knowledge when I need to understand Kubernetes source code or debug cloud-native tools. But for building solutions day-to-day? Python wins.
Ready to level up your Python & DevOps skills? Join the KubeCraft community where we share practical projects and land people jobs every week
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Cheers,
Mischa