Chapter 5: Data Structures Every Network Engineer Should Know – Part 3

Your automation is only as smart as your data structure choices. Choose wisely.

Author

Leonardo Furtado
June 21, 2025

Before automating BGP policies, modeling telemetry pipelines, or optimizing routing decisions with Python, every network engineer should grasp a foundational truth:

The way you structure your data shapes the way you think, and ultimately, how fast and safely you can act on the network.

This is the third installment of our series Data Structures Every Network Engineer Should Know. If you haven't read the first two yet, I highly recommend checking them out, right herer on The Routing Intent newsletter!

  • 🔗 Part 1: Data Structures Every Network Engineer Should Know covers lists, sets, dictionaries, and tuples, setting the foundation for logic-driven automation.

  • 🔗 Part 2: Understanding Hash Tables, Heaps, Bitmaps, and B-Trees dives deeper into structures used for efficient lookups, prioritization, and memory-conscious set operations.

In this final chapter, we push into advanced and specialized structures that power the internals of modern network software:

  • Self-balancing trees like AVL and Red-Black Trees are essential for maintaining ordered data in compilers, protocol engines, and routing databases.

  • Skip Lists are often used for sorted indexing in distributed and high-throughput systems.

  • Trie Trees mirror the longest-prefix-match logic in IP forwarding tables and routing lookups.

  • And Segment Trees, powerful for answering real-time queries over ranges—think QoS metrics, telemetry windows, or packet classification intervals.

These structures are not just for competitive programmers or computer scientists; they are directly useful in building real-time, scalable, and precise tooling for modern network engineering.

So, whether you're building your own policy engine, troubleshooting data pipelines, or designing topology-aware automation, understanding these data structures will help you think and build like a systems engineer.

Let’s dive in.

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