Event-driven modeling constitutes a programming technique where the system responds to external and internal events, including actions such as key pressing, mouse clicks, and the message from the other threads, which determines the flow of the program. The event-driven model technique is based on the principle that systems have finite states and events are the reason for moving from one state to another. The GUI and applications like Javascript or web applications use event-driven programming techniques for undertaking certain types of actions as a response to user actions.
Event-Driven Applications
With a workable event-driven model or architecture, applications respond to data as soon as it is produced. Even driven approaches have become extremely popular recently, all thanks to explosions in data sources generating events like the IoT sensors and the development and adoption of technologies processing event streams. The event-driven approach empowers businesses to undertake their operation and generate data as a series of continuing events – instead of as a handful of metrics over a quarterly report.
For instance, let’s consider two fictional characters, Eve and Eva, who have lived in many locations. If we were to perform an address lookup with a traditional batch-based design and the data updates – we should see their address as it is currently recorded.
However, with an event-driven model, we can ask, what is Eve and Eva’s address now?
In addition to this, we can also ask; What was Eve and Eva’s address back in 2014?
OR
What was Eve’s last address before she shared an address with Eva?
The event-driven models and applications are common use cases for IoT, payment processing, fraud detection, real-time marketing, and website monitoring. Such applications treat the data as unchangeable or immutable, making it even easier to look for data values in previous instances. Thus, when information changes, actually a new data point is created with a new time instance.
Not every event is supposed to trigger an action by the application, though.
Take the case of IoT sensor data – in an application looking for anomalies within the sensor data, there might lie millions of non-anomalous events occurring without having to trigger the application for action.
Event-Driven Microservices and Architectures
Event-driven architectures and models are popular for microservices-based software applications. The microservices are built to undertake specific tasks, which are often based on the occurrence of an event.
Thus, mostly the event-driven model is the backbone of microservices.
Event-Driven Model
Event-driven models can be based on either a pub or sub-model or even on an event stream model.
Publisher/Subscriber Model
It is a messaging infrastructure that is based on subscriptions to an event stream, keeping track of subscriptions. In this model, after an event takes place or gets published, it is sent off to subscribers who need to be informed.
Event Streaming Model
With an event streaming model, the events are written on a log. The event consumers do not subscribe to an event stream. However, they can read from any part of the stream while also being able to join the stream at any given instant.
Benefits of Event-Driven Model
The event-based models are asynchronous without blocking, allowing resources to move about freely to the next task once their own unit of work gets completed. This is even without having to worry about what happens after or before.
- Services are not dependent on other services and neither require their knowledge. When using events, the services operate independently, without knowing other services, which include their implementation details and transport protocols.
- Thus, services under the event models are updated, tested, and deployed independently and quite easily.
- As the services are decoupled under the event-driven architecture, these services typically perform one task only. Thus tracking down bottlenecks to specific services and scaling them becomes very easy.
- The event-drive model architecture with a queue can also recover the lost work by replaying past events. This becomes valuable for preventing data loss when the consumer needs to recover.
- Such model patterns achieve top-notch performance via their asynchronous capabilities – and the ability to perform decoupled and parallel asynchronous operations outshine the costs of queuing and dequeuing messages.
- Scalability is another obvious benefit of this pattern, with the independent and decoupled event processors. Every event processor can be scaled separately, allowing the possibility of fine-grain scalability.
- Situational awareness in real-time is another plus, which means the business decisions, automated or manual, can be taken by using the data at hand, reflecting the current system’s state.
Event-Driven Model – the Futuristic Approach
In the fast-paced digital world, many companies are using a business model that is based on the “On-Demand Economy”. Additionally, information acquisition is getting big owing to technological and sociological trends such as the IoT and social media. The event-drive model is the obvious and most natural paradigm for using real-time information and designing flexible systems adaptable to changes.
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