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Event-driven Architectures: Leveraging Data Streaming For Reactive Systems

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By Author: Muthamilselvan
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Event-driven architectures (EDA) have become popular in recent times. They are used to design flexible, scalable, and reactive systems that handle real-time data processing and offer near real-time responses to user actions. At the heart of EDA is data streaming, where events are produced, captured, and propagated asynchronously across the system.
But what is EDA? What are the key components of event-driven architecture? And why should you use EDA in data streaming for reactive systems? Let’s find out.
What is Event-Driven Architecture?
EDA is a software architecture model that allows you to produce, identify, consume, and react to events. This architecture enables a group of systems to communicate with one another through event publication and consumption.
In EDA, an event implies a significant change in state or something that occurred in the production system. This architecture allows you to build a system in which information flow is determined by events.
Event-driven architecture allows messages to be ingested into an event-driven environment before broadcasting them to the services interested ...
... in them. It uses a messaging backbone to transfer messages from producers to consumers.
Key Components of Event-Driven Architectures
Here is an overview of the basic components of EDA:
Events
At the core of EDA are events. As initially stated, events are significant changes or occurrences in the system that carry information about what happened. Therefore, they can represent system updates, user actions, or external data arrivals, among other relevant activities.
An event is a small, self-contained data unit that carries enough information for consumers to act. For instance, when a user clicks a button on a mobile or web application, it can generate a click event.
Event Producers
As the name suggests, event producers are the services or components that generate a stream of events. Event producers may include background processes, sensors, and user interfaces, among other data sources that trigger events.
Event Consumers
Event consumers are the components that “listen” to the events. They act upon events and perform specific actions based on the event’s content. Some event consumers include serverless functions, microservices, or other system parts designed to manage event processing.
Event Routers
An event router filters and pushes events to consumers. It establishes indirection and interoperability between systems, enabling them to exchange data and messages while staying agnostic.
When to Leverage Event-Driven Architectures
Here are some instances where EDA can work the best:
• When massive data flows at a high velocity.

• When several subsystems want to process the same events.

• Where complex event processing is involved, including pattern matching.

• When real-time processing with minimal latency is necessary.
Why is Event-Driven Architecture Suitable for Reactive Systems?
Reactive systems are designed to be elastic, responsive, message-driven, and resilient. They are an architectural approach to developing distributed responsive systems. On the other hand, EDA is naturally reactive. This means they can respond to events and changes in real time. Leveraging EDA in reactive systems enables you to build systems that scale and gracefully manage failures while maintaining responsiveness.
Why Leverage EDA in Data Streaming for Reactive Systems?
Event-driven architectures have numerous benefits when used in data streaming for reactive systems. Here are some advantages of EDA:
1. Decoupling
Event-driven architecture promotes loose coupling between components, as they interact via events instead of direct calls. Event producers and consumers are decoupled. This means they can be maintained independently.
Decoupling promotes interoperability between services. However, a failure in one component does not affect the system's overall functionality. This mitigates the degree of harm or downtime caused by failure.


2. Scalability
The amount of data generated has been growing with time. This trend is not likely to change due to the increasing number of digital devices. So, scalability should be in your mind as you build your system.
Event-driven architectures leverage asynchronous processing and data streaming. This allows you to scale effectively, accommodating increasing data traffic and volumes with relative ease.
3. Agility and Flexibility
Leveraging data streaming for reactive systems requires a highly flexible and agile system. Your systems should support seamless modification to ensure you can respond quickly to business or data requirements changes.
Event-driven architectures are highly agile. They allow you to add or remove components without disrupting the entire system. This flexibility enables you to update your system quickly to accommodate new demands and changes. Also, it facilitates rapid development because components are loosely decoupled.
4. Cost Savings
Event-driven architectures or EDAs are push-based or event-triggered. This means everything occurs on-demand as events present themselves in the router. Therefore, you do not pay for continuous polling to check for a possible event. This implies less idle fleet capacity, SSL/TLS handshakes, network bandwidth consumption, and CPU utilization.
5. Seamless Auditing
Auditing is crucial when leveraging data streaming for reactive systems. It ensures that your data is only accessed by authorized users. Also, it helps you identify potential vulnerabilities in your system.
In event-driven architectures, events act as the system’s single source of truth. This makes implementing event sourcing and auditing easier, helping you maintain a historical record of all system changes.
Also, the event router serves as the centralized location for auditing your applications and defining policies. The policies can limit who can subscribe or publish to a router and regulate which resources and users can access your data.
6. Real-Time Processing Capabilities
Event-driven architectures support the real-time processing of events. This makes them ideal for reactive systems and applications where low latency is crucial, such as IoT, gaming, and financial systems.
Final Thoughts
Event-driven architectures with data streaming services are powerful paradigms for developing reactive and scalable systems that can manage real-time data processing. This makes them ideal for numerous modern applications, including data streaming apps. However, EDAs introduce several complexities, such as ensuring message delivery, handling possible event duplicates, and managing event ordering. Also, processing events simultaneously or in order can be challenging because each consumer type runs in multiple instances for scalability and resilience. Therefore, you must carefully address these challenges during the design and implementation stages.

More About the Author

Muthamilselvan is a passionate Content Marketer and SEO Analyst. He has 8 years of hands-on experience in Digital Marketing with IT and Service sectors. Helped increase online visibility and sales/leads over the years consistently with my extensive and updated knowledge of SEO. Have worked on both Service based and product-oriented websites.

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