Change Data Capture Pipeline Playbook
CDC looks attractive because it lets downstream systems react to database changes without changing application write paths. But the log is not a product contract by default. If teams expose it carelessly, they inherit brittle coupling fast.
Where CDC works well
- syncing operational data into analytics
- feeding search indexes
- keeping read models warm
- emitting downstream integration events
What must be designed deliberately
- table and column ownership
- schema evolution rules
- replay boundaries
- deduplication and ordering expectations
The mistake is assuming that “change happened in the DB” is the same as “business event is ready for consumers.” Often it is not.
Practical advice
- use CDC for replication-style integration first
- keep business semantics explicit instead of leaking raw table intent
- version downstream transforms
- track lag, dropped events, and replay cost as first-class metrics
CDC is powerful when it extends system visibility. It becomes dangerous when it becomes the hidden API of the company.
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