Schema Evolution Challenge
Context schemas must evolve as business needs change, yet changes cannot break existing consumers. This guide covers schema evolution strategies within the ECM Protocol framework.
Versioning Strategies
Semantic Versioning
Apply SemVer to context schemas: MAJOR for breaking changes, MINOR for backward-compatible additions, PATCH for corrections. Major version changes require consumer migration.
Version Embedding
Include schema version in context:
{
"schema_version": "2.1.0",
"context_type": "user-preferences",
"data": {
"theme": "dark",
"notifications": {
"email": true,
"push": false
}
}
}Backward-Compatible Changes
Additive Changes (Safe)
Adding optional fields is always safe. New consumers use new fields. Old consumers ignore unknown fields. Default values for new required fields.
Deprecation (Safe)
Mark fields as deprecated, don't remove. Document deprecation timeline. Provide migration guidance. Remove after deprecation period.
Field Widening (Safe)
Expanding allowed values (enum additions). Relaxing constraints (making required optional). Changing number to allow decimals.
Breaking Changes (Careful)
Field Removal
Never remove fields without deprecation period. Minimum 6-month deprecation. Monitor field usage before removal. Provide migration tooling.
Type Changes
Require major version bump. Consider dual-field approach during migration. Old field deprecated, new field added. Transform layer for compatibility.
Semantic Changes
Changing field meaning is breaking even if structure unchanged. Document clearly as major change. Consider new field name instead.
Schema Registry
Registry Functions
Central schema registry provides schema storage, compatibility checking, schema evolution history, and consumer registration.
Compatibility Checking
Automated validation of schema changes. Block incompatible changes. Require explicit override for breaking changes. Integration with CI/CD.
Migration Tools
Support schema migrations:
- Transform functions: Upgrade context to new schema
- Batch migration: Update stored context in place
- On-read migration: Transform during retrieval
- Parallel schemas: Support multiple versions simultaneously
Conclusion
Schema evolution is inevitable. Plan for it with semantic versioning, additive-first changes, proper deprecation, and tooling support. Breaking changes require careful planning and migration support.
