Managing complexity: Event-driven architecture explained

Key elements of an event-driven architecture explained

Event-driven architecture is a software design framework that structures how decoupled components respond to and process user-, sensor- or system-driven events in real time. Within EDA environments, individual services are designed and configured to perform asynchronously and execute one hyperspecific task, ensuring that application components and system events function independently.

The services communicate through a messaging backbone that can employ a traditional pub/sub approach or distributed log, with the two methods often existing side by side. For example, when purchasing an item on an e-commerce platform, an order processing microservice can contact a payment microservice using specific API calls at checkout. These decoupled components -- the event producer and event consumer -- enable the rapid responses and independent scaling that constitute e-commerce today.

The three central components of an event-driven architecture include the event producer, event bus and event consumer.

Event producer

An event producer generates an event based on an action or change in a system. It is then transmitted to the rest of an application by way of an event bus. A customer making a bank account transaction is an example of an event, one that triggers security actions and account balance checks to handle the specific event in real time.

Event bus

Event transmission and processing are key aspects of an event-driven architecture. The event bus functions as a hub that enables events to be shared among different components within an environment.

Useful tools for event processing include Apache Kafka, a highly scalable, fault-tolerant platform for handling trillions of events per day, and RabbitMQ, which offers easy deployment, real-time monitoring and high availability. Both messaging systems ensure that events are received, broadcasted and ready to be processed.

Event consumer

Event consumers are system components that subscribe to specific broadcasts and generate dynamic responses based on the event they receive. Asynchronous processing is essential so that components don't need to wait to respond after receiving an event notification.

Different types of EDA

The advantages of an event-driven architecture include lower latencies and faster data transmissions. In contrast to manual IT approaches, the high levels of automation within event-driven architectures streamline IT maintenance, such as periodic updates and improvement of response capabilities to data center outages. While EDA adoption can increase complexity and overhead, it's also an architecture that works well with and benefits from the ubiquity of cloud services. The following architectural pattern examples explain specific use case requirements and represent a few of the dynamic EDA approaches.

Pub/sub and message queue architecture

In general, an EDA event processing system relies on message queues to communicate and generate events. Subscribers to that event then respond independently. As a result, disparate system components can flexibly engage, reacting instantly to an event such as a user-initiated request.

In the pub/sub model, a topic-based subscription represents the most common approach in which event notifications have associated topics under which they're published. Consumers are then notified and can respond appropriately. For example, within a social media app such as X, formerly known as Twitter, the message broker in the back end routes posts from publishers to subscribers based on relevant topics.

Command query responsibility segregation

Command query responsibility segregation (CQRS) differentiates between writing commands and reading queries within a system for optimized processing. It also results in improved scalability and performance for the read component within applications. CQRS is an especially useful approach when audits and complex data processing are required.

Complex event processing

Complex event processing (CEP) primarily detects data flow patterns within event-driven architectures. CEP correlates streams of different events instantaneously so that IT teams can review events in real time and respond appropriately. For example, IT teams can resolve issues and streamline redundant workflows to improve assembly lines and production systems in manufacturing.

Integrating EDA with IT systems

The demand for and increased adoption of distributed services, coupled with the immense amount of data that needs to be processed and managed, has made EDA a trendy architectural option. But, without successful design and implementation, challenges pertaining to complexity, latency and overhead will likely outweigh the benefits of an EDA adoption. This would likely be the case for organizations that do not expect to experience rapid, unpredictable growth or handle highly variable workloads.

EDA adoption is not as simple as acquiring a new tool or using a message bus to move data. Rather, IT leaders need to determine if they have an experienced enough team to take on a migration and address the run- and design-time aspects of event-driven adoption. They should explore ways to assimilate other sources of data in an event-driven system that principally uses messaging protocols. Organizations might also consider protocol- and cloud-agnostic approaches for their event-driven implementation, future-proofing for scalability and reduced latency.

Kerry Doyle has written about technology, business and higher education for a variety of publications and organizations. His current focus is on issues relevant to IT and enterprise leaders across a range of topics, from nanotech to the cloud to microservices.