Challenges and Strategies with Concurrent Data Access

In today's rapidly evolving digital landscape, systems have shifted from traditional monolithic architectures to agile microservices, designed to meet diverse and growing business demands. This transformation, while enhancing scalability and flexibility, introduces significant challenges, particularly in managing concurrent data access. As multiple integrators interact with the same data entities, the risk of data duplication and integrity issues escalates, especially when unplanned concurrency arises from poorly designed client architectures or asynchronous processing strategies. To navigate these complexities, organizations must adopt robust methodologies, such as defining unique Business Keys and implementing optimistic locking mechanisms, ensuring that data remains accurate and reliable in a dynamic environment. Ultimately, service providers play a crucial role in safeguarding data integrity amidst the intricacies of modern systems.

1. Context of Modern Systems

Shift to Microservices: Systems have transitioned from monolithic architectures to microservices, allowing for greater agility and scalability.

Concurrency Risks: As systems evolve, new features can inadvertently affect existing functionalities, especially when multiple components interact with the same data concurrently.

2. Challenges with Concurrent Access

Concurrent Business Flows: It's crucial for systems to support multiple integrators accessing the same data simultaneously without losing data integrity.

Unplanned Concurrency: Issues can arise from poorly designed client architectures that cause multiple requests. Performance optimizations that lead to asynchronous processing. Hybrid systems where event-based and request-based architectures coexist.

3. Identity Crisis

Data Duplication: Parallel processing can result in duplicate records for the same data entity, leading to orphaned records.

Business Key Definition: To address this, it's essential to create a Business Key that: Unique, Scalable, Deterministic and Can be smart. A well-defined Business Key should clearly identify the unique characteristics of an object while being adaptable to business growth without needing redefinition. It must generate consistent values, regardless of the request's origin, and can incorporate sharding or routing details to enhance processing efficiency.

4. Clobbered Updates

Data Loss Risk: Concurrent updates (e.g., changing color and shape of an object) can result in lost information if not managed properly.

Optimistic Locking: This technique can be employed to prevent data loss. It involves checking that data hasn't changed before applying updates, and includes a retry mechanism if conflicts occur.

5. Responsibility for Data Integrity

Service Provider's Role: Providers must ensure accurate data management by defining data entities clearly and managing concurrent access effectively to maintain integrity.