APIs are dominating the digital landscape. End-users and business leaders are increasingly expecting digital experiences to be interactive, immersive, responsive, and immediate. Real-time reports of changes in states are necessary to help make executive decisions at the moment. The key to delivering these growing demands is to design APIs using event-driven architecture alongside service-oriented architectures.
EDA allows clients to subscribe to and receive events asynchronously and in real-time, eliminating the need to ask for updates or state changes. Shifting architectural complexity from client to producer allows organizations to drive fluid user experiences. EDA results in the ability to make real-time business decisions using the most up-to-date information.
What’s Event-Driven Architecture?
Event based architecture is a software pattern that allows organizations to detect events or business moments and act on them in real or near real-time. This pattern replaces the request-response architecture in which services wait for a reply before moving on to the next task. The flow of event-driven architecture is run by events and responds to them or carries out an action in response to an event. EDA is considered asynchronous communication, meaning the sender and recipient don’t have to wait for each other to proceed with the next task. An example of asynchronous communication is text messaging because regardless of who is receiving or listening to the message, the sender isn’t waiting for a response.
How Does EDA Work?
There are three components of event-driven architecture: producer, consumer, and broker. The broker is optional when there’s a single producer and a single consumer in direct communication with each other. Organizations typically have multiple sources sending various types of events with one or more consumers interested in some or all of the events. A retailer, for example, may collect all purchases that are completed at stores around the world. These purchases are fed into the EDA that monitors for fraud, sending them to credit card processors or the actions that need to happen next.
When planning a silent party, customers don’t want to wait to receive replies about equipment rental. They’d rather interact with the website, decide on what they want, and place an order, making event-based architecture essential. Party Headphones offers customers novel music options perfect for memorable experiences. Their site gives customers all the information they need to plan the perfect silent party, from rental fees and shipping to how to use the equipment. The production company is the premier silent disco rental company offering silent disco headphone rentals, leases, and purchases. Their wireless headphones allow party-goers to change music options with the flip of a switch and find the perfect songs to dance to without worrying about noise ordinances. A silent disco party is perfect for weddings, fundraisers, corporate events, art performances, and more.
The Advantages of EDA
EDA offers true decoupling of the event producers and event consumers as microservices, separating the ownership of data by domain. Decoupling enables a logical separation between the production and consumption of events. Loose coupling means microservices can be implemented in different languages or technologies that are appropriate for specific jobs.
The loose coupling of components means that services aren’t worried about the status or health of another service. Loose coupling provides a level of resiliency within the system, meaning if one microservice is down, the application can still run in its absence. This is possible because events are stored in the messaging backbone so the consuming service can continue where it left off once recovered.
EDA allows for push-based messaging through the presence of an intermediary broker. With event-based architecture, clients receive updates in real time as they happen, powering on-the-fly data transformation, analysis, and data science processes. Real-time event streams enable faster business decision-making and enable applications to respond to changing solutions as they occur and make decisions based on the available real-time data. Event stream processing is ideal for fraud detection, predictive analytics, handling security threats, and supply chain automation. Lastly, EDA provides an accelerated path for machine learning and data science into production environments.
