An overview of MIT 6.824

What I understand of Distributed System?

Distributed systems tackle the problem of Performance Scalability, in particular horizontal scaliability: how can we improve throughput by N times, given we have ~ N machines.

• Usually this is not straightforward, as there can be bottlenecks introduced or failures.

Why I chose to take this course?

• interesting — hard problems, non-obvious solutions
• active research area — lots of progress + big unsolved problems
• used by real systems — unlike 10 years ago — driven by the rise of big Web sites
• hands-on — you’ll build a real system in the labs

Main topics cover by the course

1. 3 main abstractions for distributed infrastructure

   • Storage systems (e.g. Memcache at Facebook)
   • Computation systems (e.g. MapReduce)
   • Communication models (e.g. Network, Reliability)

2. Implementation of these abstractions including

   • RPC
   • Threads

3. Fault tolerance in the form of:

   • Availability
   • Recoverability
   • Common strategies include Replication, Non-volatile Storage

4. Consistency

   • Intuition: Usually we have multiple replicas of the same data, how can we talk about consistency between these replicas?

Labs

The labs will be written in Go. Previous iterations used C++. Golang avoids the various problems that come with C++ such as handling memory, keeping manual track of when the last thread has completed before freeing the memory etc.

(Still considering whether to work on the labs - might try a few first)

Useful links for the course

1. Official 2020 Course Schedule https://pdos.csail.mit.edu/6.824/schedule.html
2. 2015 Notes for the course https://wizardforcel.gitbooks.io/distributed-systems-engineering-lecture-notes/content/l01-intro.html

Written by Melodies Sim who lives and works in the Bay Area, California turning novel ideas into reality. Check out her projects on Github.