10 GitHub Repositories to Master System Design

2026-03-05 · Source: KDnuggets · Field: Technology & Digital — Software Development & Engineering, Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure · Depth: Intermediate, medium

Summary

This article reviews 10 GitHub repositories that serve as comprehensive resources for mastering system design, covering fundamentals, interview preparation, and specialized areas like machine learning and agent-based systems. These repositories address core concepts such as scalability, performance, latency, throughput, CAP theorem, caching, load balancing, and database scaling. They provide structured learning paths, visual explanations, curated resources, and frameworks for approaching system design interviews. Specific repositories like "System Design Primer" and "System Design 101" offer foundational knowledge, while others like "Machine Learning Systems Design" and "Agentic System Design Patterns" delve into specialized architectural considerations for AI and distributed systems. The collection aims to equip engineers with the structured thinking necessary for designing reliable and scalable systems.

Key takeaway

For Software Engineers or AI Architects aiming to deepen your understanding of scalable systems beyond theoretical concepts, you should explore these curated GitHub repositories. They provide practical insights into architectural trade-offs, distributed systems, and specialized ML/agentic designs, helping you move from conceptual knowledge to applied architectural thinking and effective interview preparation.

Key insights

GitHub repositories offer structured learning paths for mastering system design fundamentals and specialized architectures.

Principles

• System design balances cost, scalability, latency, and complexity.
• No single "correct" answer exists in system design.
• Real-world case studies enhance architectural understanding.

Method

The article proposes learning system design by exploring curated GitHub repositories that cover fundamentals, interview strategies, distributed systems, ML system design, and agent-based architectures.

In practice

• Use "System Design Primer" for core concepts.
• Consult "ML Systems Design" for AI architecture.
• Practice with "System Design Interview Handbook".

Topics

• System Design
• Distributed Systems
• ML System Design
• Agentic System Design
• Scalability Engineering

Code references

• donnemartin/system-design-primer
• ByteByteGoHq/system-design-101
• karanpratapsingh/system-design
• ashishps1/awesome-system-design-resources
• checkcheckzz/system-design-interview

Best for: Software Engineer, Machine Learning Engineer, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by KDnuggets.