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Network automation is no longer a “nice to have”, it’s a necessity. As networks grow more complex, engineers need tools that can handle large-scale changes, integrate with APIs, and run reliably in production. While Python has long been the default for automation scripts, there’s another language making strong inroads: Go (Golang).
In this post, we’ll explore why Go is such a compelling choice for network automation and where it fits in your automation journey.
The Case for Go
Go was created at Google with a simple mission: make it easier to write reliable, performant software. It combines the speed and efficiency of a compiled language with the simplicity of a scripting language. This is especially useful for network engineers who need automation tools that are:
- Fast – Go compiles to native binaries, so tools run at near C-speed.
- Portable – The same code compiles to different platforms (Linux, Windows, macOS) without changes.
- Concurrent – Built-in concurrency primitives (goroutines and channels) make it easy to handle multiple network devices in parallel.
- Self-contained – No dependency hell. Go programs compile into single binaries, eliminating external package management issues.
Why Not Just Stick with Python?
Python is great but it’s not perfect for every automation use case. For large-scale or long-running network automation tasks, Python’s interpreter overhead and dependency management can be bottlenecks. Go offers:
- Better performance for API calls, data parsing, and large device inventories.
- No runtime dependency issues, deploy one binary to any machine.
- Fewer moving parts in production, which reduces failure points.
Think of it this way: Python is like a Swiss Army knife which is flexible, quick to start, great for scripts. Go is like a power tool that is purpose-built for speed, concurrency, and deployment at scale.
Go in the Network Automation Stack
In a modern network automation workflow, Go can fit into multiple layers:
- Configuration generation – Quickly build configs for hundreds of devices.
- API orchestration – Interact with RESTCONF, gNMI, and other APIs in parallel.
- Data processing – Parse telemetry or syslog data streams in real-time.
- Custom tooling – Build CLI tools or daemons for continuous monitoring.
