When an order is short on stock at a warehouse, the system creates an internal transfer request to move inventory from another location. The existing flow publishes one Kafka message per order, which triggers one transfer request per order.

During peak hours, a single warehouse can generate hundreds of these messages in minutes. Each one spawns a small transfer note. The warehouse team ends up processing dozens of tiny requests for the same destination when a single consolidated batch would do.

Note: Code examples in this article use Go. The concepts apply to any language.

Why lock at all?

Imagine two users trying to withdraw money from the same bank account simultaneously. Without proper synchronization, both might read the same balance, deduct their amounts independently, and write back—resulting in a lost update. One withdrawal effectively disappears.

This is a classic race condition, the correctness of the outcome depends on the timing of operations.