What are the most common integration patterns for event-driven systems?

2 Event-carried state transfer

Another common integration pattern for event-driven systems is event-carried state transfer. In this pattern, a component publishes an event that contains not only the minimal information, but also the relevant state of the source component. The event acts as a snapshot of the source component's state at a given point in time, and can be used by other components to update their own state or perform some action based on the event. This pattern reduces the need for direct queries or remote calls between components, as they can rely on the events to synchronize their state. However, this pattern also increases the size and complexity of the events, and may introduce some challenges in handling conflicts or inconsistencies.

3 Event sourcing

Event sourcing is a more advanced integration pattern for event-driven systems, that involves storing the state of a component as a sequence of events, rather than as a current representation. In this pattern, a component publishes an event every time it changes its state, and uses the same events to reconstruct its state when needed. The events are immutable and append-only, and can be stored in a durable and distributed event store. This pattern enables a component to keep a complete history of its state changes, and to support features such as auditing, replaying, or undoing events. However, this pattern also requires a careful design of the events and the event store, and may introduce some performance and scalability issues.

4 Command-query responsibility segregation

Command-query responsibility segregation (CQRS) is a related integration pattern for event-driven systems, that involves separating the write and read operations of a component into different models or services. In this pattern, a component publishes a command event to request a change in the state of another component, and receives a confirmation or rejection event as a result. The component also publishes a query event to request the current state of another component, and receives a response event with the requested data. This pattern allows a component to optimize its write and read operations for different requirements, such as consistency, availability, or performance. However, this pattern also adds more complexity and overhead to the communication between components, and may require some coordination or synchronization mechanisms.

5 Complex event processing

Complex event processing (CEP) is a sophisticated integration pattern for event-driven systems, that involves analyzing and processing multiple events to derive higher-level events or insights. In this pattern, a component uses a CEP engine or framework to apply rules, patterns, or logic to the events it receives from other components, and to generate new events that represent complex or aggregated situations, such as trends, anomalies, or opportunities. The component can also use the CEP engine to trigger actions or responses based on the complex events. This pattern enables a component to perform real-time or near-real-time decision making, and to provide value-added services or features. However, this pattern also requires a high level of expertise and resources to implement and maintain the CEP engine and the rules, and may introduce some latency or reliability issues.