1. 1. Introduction
  2. 2. Lectures
    1. 2.1. Lecture 1: Introduction
    2. 2.2. Lecture 3: GFS
    3. 2.3. Lecture 6: Fault Tolerance: Raft (1)
    4. 2.4. Lecture 7: Fault Tolerance: Raft (2)
    5. 2.5. Lecture 8: Zookeeper
    6. 2.6. Lecture 10: Cloud Replicated DB, Aurora
    7. 2.7. Lecture 12: Distributed Transactions
    8. 2.8. Lecture 13: Spanner
    9. 2.9. Lecture 15: Big Data: Spark
    10. 2.10. Lecture 16: Cache Consistency: Memcached at Facebook
  3. 3. Extras
    1. 3.1. Extra 1: Scalability Harvard CS 75
    2. 3.2. Extra 2: Chord Algorithm Berkeley CS 162
    3. 3.3. Extra 3: Dynamo Amazon’s Highly Available Key-value Store
    4. 3.4. Extra 4: CAP Theorem
    5. 3.5. Extra 5: Serverless, Coordination-free Distributed Computing, and the CALM Theorem
    6. 3.6. Extra 6: Stellar
    7. 3.7. Extra 7: CockroachDB, Spanner, MongoDB
    8. 3.8. Extra 8: Scalability! But at What COST?
    9. 3.9. Extra 9: Ray: A Distributed Execution Framework for AI
    10. 3.10. Extra 10: Cluster Management with Borg and Kubernetes

Distributed Systems Notes

Introduction

MIT 6.824: Distributed Systems