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Reason about consistency, time, consensus and failure, and build systems around storage engines, logs and events.
By the end you can
- State the consistency and availability trade-off a design is making
- Choose between consistency models, from linearizable to eventual
- Reason about time, consensus and failure in a cluster
- Build a system around events
- Separate read and write models when scale demands it
Start: Consistency, availability and CAP6 steps · about 8 hours of lessons and videos
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Distributed Systems ThinkerMaster every stepLearn · 0/1
- Consistency, availability and CAP
12 min · 4-question quiz
Explore · 0/1
- CAP theorem
Interactive simulation
Build · 0/1
- Consistency and lag
Open in the Builder
Watch · 0/3
CAP Theorem SimplifiedByteByteGo · 6 min
CAP Theorem in System Design InterviewsHello Interview · 14 min
2. CAP Theorem (Hindi) | High Level Design for Beginners | CAP Partition Tolerance explainedConcept && Coding - by Shrayansh · 19 min
Read · 0/3
- Martin Kleppmann: Distributed Systems Lectures
University of Cambridge
- Martin Kleppmann's Blog
martin.kleppmann.com
0% done. At 80% this step counts as mastered.
Master all 6 steps to earn the Distributed Systems Thinker badge and a grade. A step counts as mastered when you have done 80% of it. Lessons you finish, labs you pass and videos you watch on the site tick themselves.