How can you design event-driven systems using common architecture patterns?

1 Pub/Sub Pattern

The publish/subscribe (pub/sub) pattern is a popular architecture pattern for event-driven systems. In this pattern, publishers send events to a broker or a bus, which then distributes them to subscribers who have registered their interest in certain topics or types of events. The pub/sub pattern allows publishers and subscribers to be loosely coupled, as they do not need to know each other's identities, locations, or protocols. The pub/sub pattern can also enable scalability, as multiple publishers and subscribers can join or leave the system without affecting each other. However, the pub/sub pattern can also introduce challenges such as message ordering, delivery guarantees, and event filtering.

2 Event Sourcing Pattern

The event sourcing pattern is another architecture pattern for event-driven systems. In this pattern, the state of the system is derived from a sequence of events that capture the changes that have occurred over time. The events are stored in an append-only log or a stream, which can be replayed or queried to reconstruct the state of the system at any point in time. The event sourcing pattern can enable benefits such as auditability, consistency, and resilience, as the events provide a reliable and immutable source of truth for the system. However, the event sourcing pattern can also pose challenges such as event schema evolution, data retention, and performance.

3 CQRS Pattern

The command and query responsibility segregation (CQRS) pattern is a complementary architecture pattern for event-driven systems that use the event sourcing pattern. In this pattern, the system is divided into two parts: one that handles commands, which are requests to change the state of the system, and one that handles queries, which are requests to read the state of the system. The commands are processed by generating and storing events, while the queries are processed by reading from projections, which are denormalized views of the state derived from the events. The CQRS pattern can enable benefits such as scalability, performance, and security, as the commands and queries can be handled by different services, databases, and policies. However, the CQRS pattern can also introduce complexity, latency, and consistency issues, as the commands and queries need to be synchronized and coordinated.

4 Saga Pattern

The saga pattern is a useful architecture pattern for event-driven systems that need to handle long-running or distributed transactions. In this pattern, a transaction is broken down into a series of steps, each of which is performed by a different service and generates an event. The events are then used to coordinate the execution and compensation of the steps, either by using a central orchestrator or by using a choreography of local handlers. The saga pattern can enable benefits such as reliability, availability, and fault tolerance, as the steps can be retried, rolled back, or skipped in case of failures. However, the saga pattern can also create challenges such as complexity, consistency, and error handling, as the steps need to be idempotent, atomic, and compensable.

5 Stream Processing Pattern

The stream processing pattern is a powerful architecture pattern for event-driven systems that need to perform real-time or near-real-time analysis or processing of large volumes of data. In this pattern, the data is treated as a continuous stream of events, which are then consumed and processed by one or more services that apply various functions, such as filtering, aggregation, transformation, or enrichment. The stream processing pattern can enable benefits such as scalability, performance, and responsiveness, as the data can be processed in parallel, in memory, and in a timely manner. However, the stream processing pattern can also raise challenges such as data quality, latency, and state management, as the data can be incomplete, delayed, or out of order.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?