Understanding Distributed Transaction Challenges and Practical Solutions in Microservices

Distributed transactions require that a set of operations across services either all succeed or have no effect, which is especially hard in high‑concurrency microservice systems that use NoSQL or sharded databases.

The core difficulty lies in handling timeouts and ensuring that the real execution status of each sub‑task (A and B) is known, which calls for a reliable "accounting" mechanism ("立字据") and the ability to perform reconciliation.

A unique transaction ID is essential for linking sub‑tasks, enabling idempotency and reconciliation. Various persistence strategies are discussed:

Local process logging combined with centralized collection.

SQL undo‑log tables that participate in the same local transaction.

NoSQL value fields that store an array of transaction IDs.

Code examples illustrate task logging and undo‑log insertion:

节点1完成任务1
节点2完成任务1
节点3完成任务1

节点1完成任务1
节点1完成任务2
节点1完成任务3

When external services are involved, their APIs must provide reconciliation and idempotency capabilities. Locking strategies, including transaction‑level locks that hold until the transaction fully completes, are presented as a way to trade availability for consistency.

For scenarios where strict consistency is not required, simpler solutions such as eventual consistency with periodic reconciliation or asynchronous compensation can be used.

The article concludes with a checklist for adopting distributed transactions: ensure each task is idempotent and reconcilable, define appropriate locking mechanisms, assess consistency requirements, and prefer low‑intrusion solutions before considering heavyweight transaction frameworks.