EVENT-DRIVEN CACHED DATA REPRESENTATIONS IN HIGH-LOAD INTEGRATION FLOWS WITH ARCHITECTURAL SUPPORT AND CONSISTENCY GUARANTEES

Abstract

In modern distributed information systems, integration flows are characterized by a high frequency of changes and strict requirements for speed. Direct access to sources of truth creates the risk of overloading operational storage and instability in the operation of the entire infrastructure. This creates the need to use cached data representations that can provide fast access to information without constant access to the main systems.

However, the use of cached representations without update mechanisms leads to the accumulation of discrepancies with the source of truth. The problem is especially acute in environments with high-frequency events and in the event of failures of individual components. To maintain the integrity of the business process, architectural solutions are needed that can guarantee consistency between the cache and the source, regardless of the nature of the load.

The event-driven approach allows you to form cached representations based on a sequence of events that describe changes in the data state. Each event is an independent message with a defined identifier, time stamp, and type of operation, which makes it possible to reproduce the canonical state of the system. This model supports idempotence of event processing and ordering, and also creates conditions for controlling the obsolescence window.

Architectural support includes the use of a shared queue for receiving messages, normalization and deduplication algorithms, transactional state updates, and conflict resolution policies between different sources. Data recovery mechanisms through event log replay and synchronization quality monitoring using observation tools play an important role. This allows integration flows to remain stable even during peak loads.

Thus, event-driven cached data representations with architectural support and consistency guarantees form a holistic approach to building high-load integration systems. The combination of scalability, fault tolerance, and predictability of behavior makes them a suitable tool for modern distributed architectures when performance and data correctness requirements are critical.