data-consistency-patterns

Distributed transactions across microservices are managed using saga patterns and the outbox pattern to coordinate multi-service workflows. This skill guides mapping a two-service checkout to a saga and defining compensation steps for rollback.

To prevent anomalies like dirty reads, non-repeatable reads, and phantom reads, you map them to appropriate isolation levels such as Read Committed or Serializable. This skill provides guidance on selecting the correct level for your consistency requirements.

Preventing double booking requires correct consistency guarantees and locking strategies. This skill provides guidance on using optimistic or pessimistic locking to ensure correct behavior and inventory reservation across services.

Optimistic and pessimistic locking are chosen based on contention levels and consistency models. This skill helps you reason about ACID vs BASE guarantees to select the appropriate locking strategy for your distributed system.

Compensation steps for failed payments in a saga are designed by outlining the rollback workflow for multi-service order processing. This skill demonstrates how to map service checkouts to saga-based workflows and define the required undo actions.

Eventual consistency can work for financial transfers by using patterns like sagas to manage distributed transactions. This skill provides a framework to reason about consistency guarantees and ensure correct behavior across services.