Data Contracts in Production
Practical guide to managing schema changes and maintaining data compatibility.
What are data contracts?
Data contracts are agreements between producers and consumers about data structure, semantics, and quality guarantees.
Why they matter
Without contracts:
- Schema changes break downstream pipelines
- Data quality issues cascade across systems
- Teams can’t safely evolve their data models
- Incidents become blame games instead of learning opportunities
Contract components
A good data contract includes:
- Schema definition: Fields, types, constraints
- Semantic meaning: What each field represents
- Quality guarantees: Completeness, freshness, accuracy SLAs
- Evolution rules: How schemas can change over time
Breaking vs. non-breaking changes
Non-breaking changes (safe):
- Adding optional fields
- Making required fields optional
- Widening types (int → float)
Breaking changes (require coordination):
- Removing fields
- Making optional fields required
- Narrowing types (string → int)
- Changing field semantics
Implementation strategies
Schema registry: Central catalog of schemas and versions Contract testing: Automated tests that validate contracts Gradual migration: Support multiple schema versions during transitions Communication: Notify consumers before breaking changes
The migration playbook
- Announce breaking changes with timeline
- Provide migration guide for consumers
- Support old and new schemas during transition
- Deprecate old schema after migration period
- Monitor adoption and help teams migrate