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Reliable Data Engineering
Overview

System Design: Learning Path

Read in order, then practise with the system design problems.

#ModuleYou will be able to
1Interview frameworkRun a structured 45-minute design interview and show senior signals
2Back-of-envelope estimationTurn volumes into partitions, storage, compute and cost
3Building blocksPick and justify Kafka, stream engines, storage, serving stores, sketches
4Reliability patternsDesign idempotent, replayable, observable pipelines
5Hot keys across all systemsDetect and fix hot keys in Kafka, Spark, Flink, databases, caches and APIs, and explain the trade-off of each fix
6Data system design patternsUse 25 named patterns (outbox, CDC, CQRS, event sourcing, sagas, WAP, claim check, sketches, bulkheads…) and state their trade-offs
-Quick reference · Printable cheatsheetRevise the day before

Then go deeper on architecture topics in learn/architecture.