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Is Data Consistency Guaranteed Across Services?

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Is data consistency between services guaranteed?

Background/Overview

In microservices or loosely coupled systems, ensuring consistency becomes difficult, so it is necessary to clarify "when consistency should be achieved" during the design phase.


Examples

  • Adopt a consistency strategy based on event-driven architecture + eventual consistency.
  • Instead of synchronizing a status update bidirectionally between the Task service and the Document service, ensure consistency through a unidirectional data flow, such as having only the Task service perform the update and the Document service only subscribe to it.
  • Prevent inconsistencies by sending events after updates and validating them on the receiving end.

Common Failure Examples

  • Data becomes inconsistent due to bidirectional updates, making it unclear which information is the latest.
  • Processing order is not guaranteed, leading to data being overwritten by older events.
  • Read discrepancies occur due to replica lag.

FAQ

Q. Is eventual consistency really okay?

A. It depends on the case, but for many business operations, "consistency within a certain timeframe" is often sufficient rather than immediate consistency. It is important to consider this, define it, and document it clearly.

Q. Should bidirectional synchronization be avoided?

A. As a general rule, yes. You should avoid it because it leads to "synchronization hell" unless you adopt a unidirectional update flow.



📘 This article is part of the SaaS Design Review Perspective Checklist (2025 Edition).

0 Design perspective category: 🔁 Events / Asynchronous Processing
0 Level: Structure (Structure, Principles, Responsibility Organization Level)
0 Recommended readers: Design beginners / Teams in the design phase / Reviewers

🧭 Click here to read other perspectives as well.

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