The course that explains why distributed systems are hard and what to do about it. CAP theorem, Raft consensus, replication strategies, sharding, and the failure modes that production engineers actually debug.
This is a text-first course that links out to the best supporting material on the internet instead of trying to replace it. The goal is to make this the best course on distributed systems and scalable architecture you can find — even without producing a single minute of custom video.
This course is built by people who ship production distributed systems for a living. It reflects how things actually work on real projects — not how the documentation describes them.
Every day has working code snippets you can paste into your editor and run right now. The emphasis is on understanding what each line does, not memorizing syntax.
Instead of shooting videos that go stale in six months, Precision AI Academy links to the definitive open-source implementations, official documentation, and the best conference talks on the topic.
Each day is designed to finish in about an hour of focused reading plus hands-on work. You can do the whole course over a week of lunch breaks. No calendar commitment, no live classes, no quizzes.
Each day stands alone. Read them in order for the full picture, or jump straight to the day that answers the question you have today.
Why you can only have two of consistency, availability, and partition tolerance. What each property actually means in a real system, and which modern databases sacrifice which.
How distributed nodes agree on a single value. Paxos conceptually; Raft in detail — leader election, log replication, and the edge cases that make real implementations hard.
Single-leader, multi-leader, and leaderless replication. How Cassandra, MongoDB, and PostgreSQL each approach the problem, and the tradeoffs between each.
Hash partitioning, range partitioning, consistent hashing, and how to rebalance shards without downtime. How Kafka, Cassandra, and DynamoDB implement it.
Timeouts, retries, circuit breakers, bulkheads, and the distributed saga pattern for transactions that span multiple services. Production failure playbooks.
Instead of shooting our own videos, Precision AI Academy links to the best deep-dives already on YouTube. Watch them alongside the course. All external, all free, all from builders who ship this stuff.
Martin Kleppmann and the MIT lectures on distributed systems — the gold standard for this material.
The Raft paper visualized and explained step by step. Leader election, log replication, and safety guarantees.
What consistency, availability, and partition tolerance actually mean with real database examples.
The algorithm behind Cassandra, DynamoDB, and Kafka partitioning. Visualized with node additions and removals.
The best way to understand any technology is to read the production-grade implementations that prove it works. These repositories implement patterns from every day of this course.
The distributed key-value store that runs Kubernetes. Its Raft implementation is the most-read production consensus code in the world.
Distributed log — the reference implementation for partitioned, replicated event streaming. Day 4 sharding concepts in production scale.
The Raft library used by Consul, Nomad, and Vault. Clean Go implementation worth reading alongside Day 2.
Circuit breakers, bulkheads, and retry patterns from Day 5 as a Java library. Source shows the state machine behind each pattern.
You write services that sometimes fail in confusing ways. This course gives you the vocabulary and tools to reason about distributed failure modes.
You debug production incidents involving replication lag, split-brain, and cascading failures. This course explains what you are actually looking at.
Every system design question touches CAP, replication, or sharding. This course gives you the depth to answer why, not just what.
The 2-day in-person Precision AI Academy bootcamp covers distributed systems and scalable architecture hands-on. 5 U.S. cities. $1,490. 40 seats max. June–October 2026 (Thu–Fri).
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