Build a CDC pipeline (Debezium + outbox)

About Build a CDC pipeline (Debezium + outbox)

Your service writes to its DB and publishes to Kafka — and any crash between those two writes is permanent inconsistency. Build a Change Data Capture pipeline (modeled on Debezium + the outbox pattern) that closes the gap by making the database itself the event source.

Difficulty
intermediate
Time
about 75 minutes
Stages
9
Topic
Queues, Pub/Sub & Event Streaming

How this problem is worked

Nine stages, from what the thing is for to how it compares with the real implementations. Each asks one question, and the simulator runs the architecture you draw against the requirements you wrote.

  1. 01Purpose & invariantsWhat is this for, and what must always be true of it?
  2. 02Workload characterizationWho writes, who reads, and in what shapes?
  3. 03Data model & on-disk formatWhat does the data look like at rest?
  4. 04Core algorithmsHow do the write path and the read path actually work?
  5. 05Distribution & replicationHow does this scale out and survive losing a machine?
  6. 06Consistency & correctnessUnder concurrency and failure, what is guaranteed?
  7. 07Failure modes & recoveryWhat actually happens when each part fails?
  8. 08Operational characteristicsCan a human run this at three in the morning?
  9. 09Trade-offs & comparisonWhere does this sit against the alternatives?

Primary sources for this problem

  • Debezium documentation — debezium.io/documentation/
  • Martin Kleppmann — Online Event Processing (Queue, 2019)
  • Gunnar Morling — Reliable Microservices Data Exchange With the Outbox Pattern (debezium.io/blog)
  • Designing Data-Intensive Applications, Ch 11 — Stream Processing
  • Postgres docs — Logical replication + replication slots
  • MySQL docs — Binary log overview

Browse the full problem catalog, or see what the simulator does and does not model.