Event-driven systems are a powerful component of many businesses. By leveraging an event stream, it’s easier to track the event producer’s pathways to the event consumer. Event-driven architecture (EDA) is highly beneficial for business logic and can notify a state change in real-time. Whether you’re looking into new event queries or you’re applying logic to a simple event, the right systems architect can aid their organization greatly.
So, what are the best practices for EDA microservice setups? Which principles of event streams work most effectively? Understanding which types of events to track and query is highly applicable for several use cases. Here’s what you need to know.
EDA is, by nature, asynchronous without blocking. This means that your event source resources can move freely between tasks in the queue once units of work are completed. A resource may focus on a specific task and wait for a proper event notification to trigger its movement. Regardless of the event channel, EDA prevents event consumers from putting pressure on the event producers or blocking them, negatively impacting a workflow or specific task. This allows for greater levels of scalability and reduces latency for several event types. As it stands, it benefits complex events in particular and acts as a mediator between the event source and the event consumer in real-time.
Your services shouldn’t be dependent on one another in event-driven architecture. When you’re relying on event channels and logic flow, your services shouldn’t have a connection. In this case, they should operate independently. This means that implementation and deployment details, framework information, and transport protocols should fire without knowing other service processes. Since decoupling is complicated for many brands, it’s important to rely on an event orchestrator that keeps point-to-point integrations separate. While it’s not the only way to do so, this framework is perhaps the simplest for simple and complex events.
As mentioned, EDA allows for higher levels of scalability compared to other processes. You can get a snapshot of your event message queue and application state, develop a new order for events, and query your data more capably. Since services run independently of one another (and since services are commonly limited to a single task), it’s much easier for you to detect bottlenecks in your architecture pattern. As a result, scaling individual services is much easier across each event channel.
If your EDA has a queue, it’s simpler to recover your data by replaying key events located in your historical data. You can review past event messages and event notifications, parse your event channels, and prevent data loss. This is especially helpful if a consumer is the one experiencing data loss. As data deficiencies can negatively impact reputation and status, it’s important to use a broker to review your message queue and architecture pattern accordingly.
The immense proliferation of IoT devices means that you need to use compatible event channels. This is a surefire way to guarantee that your enterprise is future-forward. If you don’t use compatible event channels or more modern technology for your event store, you’re going to have a harder time maintaining an event queue or setting up an event mediator. IoT integration is critical for many current business intelligence processes and should be addressed as such.
While there are certainly other principles and impacts of EDA, these are some of the most topically relevant. Sensibly implementing EDA can greatly benefit brands and offer significant results. For your microservice architecture, it’s a smart idea to integrate EDA into your ongoing business processes.