Multiple teams share event schemas and data-quality responsibilities.
Prevent a producer change from breaking consumers by validating the contract automatically.
Which quality approach is most appropriate?
Validate schema, required fields, ranges, freshness, and compatibility in CI, then version and phase contract changes.
Detailed explanation
A coordinated cutover removes staged migration and broadens failure impact.
A coordinated cutover removes staged migration and broadens failure impact.
Breaking changes are detected before release and consumers can migrate in stages.
Breaking changes are detected before release and consumers can migrate in stages.
Detection is delayed and impact analysis becomes larger.
Detection is delayed and impact analysis becomes larger.
Retention rules do not validate or notify about contract changes.
Retention rules do not validate or notify about contract changes.
Check official documentation
Compare the following points with the official documentation.
AWS Glue Schema Registry compatibility、Glue Data Quality、data contractの公式説明を確認する。
What to confirm
口頭共有と自動検証可能な品質契約の違いを説明できる。
Key points
- Data contract
- CI validation
- Compatibility
- Producer/consumer
Notes
- Environment: AWS公式DEA-C01試験ガイドと各サービスの公式ドキュメントの確認
- Confirm current AWS service behavior in the official DEA-C01 documentation.
Foundation review
Contract scope
Include types, required fields, units, freshness, deletion rules, and compatibility.
Staged migration
Run versions together and measure consumer migration before retiring the old version.