distributed-systems

Distributed Systems

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Overview

Understanding how to design and reason about systems that run across multiple machines. Covers consistency, fault tolerance, replication, distributed consensus, and the trade-offs inherent in distributed system design. Essential knowledge for modern cloud-based and scalable applications.

Prerequisites

Required:

• Computer Networking - Understanding network communication is fundamental
• Operating Systems - Concurrency and system-level concepts apply to distributed systems

Recommended:

• Databases - Many distributed systems concepts overlap with distributed databases
• Algorithms and Data Structures - Distributed algorithms build on fundamental algorithmic concepts

Programming Languages

• Any modern language (Intermediate) - Go, Java, Python, or others are suitable for implementing distributed systems
• Focus on understanding distributed system concepts rather than language specifics

Recommended Resources

Textbooks

• Designing Data-Intensive Applications by Martin Kleppmann

  • Highly readable, practitioner-oriented treatment
  • Covers replication, partitioning, transactions, consistency, and distributed data systems
  • Best modern introduction to distributed systems
  • Level: Intermediate
  • ISBN: 978-1449373320

• Distributed Systems by Maarten van Steen and Andrew Tanenbaum (3rd Edition)

  • Traditional textbook approach
  • More formal than DDIA
  • Level: Intermediate
  • Available online

Video Lectures

MIT 6.824 - Distributed Systems

• Instructor: Robert Morris
• Institution: MIT
• Platform: MIT course site
• URL: Course site
• Description: Graduate-level course with excellent labs implementing distributed systems (MapReduce, Raft, key-value store)
• Challenging but highly regarded
• Readings include important papers in distributed systems

Online Resources

• MIT 6.824 readings - Essential papers in distributed systems
• Papers We Love - Distributed Systems - Community discussions of important papers
• Jepsen analyses - Real-world distributed system consistency analyses

Exercises

Practice Problems

• Source: MIT 6.824 labs

• Difficulty: Advanced

• Estimated time: 100-200 hours

• Topics: MapReduce, Raft consensus, fault-tolerant key-value store, sharded systems

• Source: Papers from MIT 6.824 reading list

• Difficulty: Intermediate to Advanced

• Topics: MapReduce, GFS, Raft, Spanner, Dynamo, and more

• Activity: Read papers and implement concepts

Projects

• Implement Raft consensus algorithm
• Build distributed key-value store
• Complete MIT 6.824 lab sequence

Study Notes

[Personal notes and key insights can be added here during study]

Progress Tracking

• Completed Designing Data-Intensive Applications
• Watched MIT 6.824 lectures
• Read essential distributed systems papers
• Completed MIT 6.824 labs or similar projects
• Review and reinforcement