Event Driven APIs

Event-driven APIs: they’re the cool kids of API architecture. If you’ve worked with them, you know the allure: real-time data updates, asynchronous communication, and the ability to decouple services so they can work independently and scale like nobody’s business. As the DZone article explains, event-driven systems can boost performance and scalability, making them perfect for complex environments where real-time changes are essential. In theory, they sound like a dream come true, right?

Now, imagine you’ve got a bunch of flight line maintainers who need to track aircraft maintenance in real time, but carrier pigeons would have more network connectivity then what most flight lines have. No, seriously, wireless and cellular connectivity on many flight lines is less than perfect. It’s a miracle they get any connection at all. Event-driven architecture? It’s great... as long as you have some semblance of a reliable connection to transmit those all-important events. But when your team is working in a patchy, often offline environment, the whole thing falls apart faster than a plane with no maintenance.

We had to face this exact issue while implementing our Aircraft Maintenance Tracking and Scheduling system. Distributed maintenance tracking was essential, but network connectivity was unreliable at best. So, even though the provided event-driven API was the logical starting point, it quickly became clear that it couldn’t solve the whole problem. Events weren’t getting through reliably enough. That’s when we had to get creative.

Here’s what we did instead:

1. Mesh-Based Data Sharing

We needed to ensure that maintainers could continue tracking and updating the system, even if their connection was sketchy. Enter mesh-based data sharing. Instead of relying on one central server, we allowed devices to sync updates with nearby devices directly. This local mesh network kept everyone up to date with minimal lag, even when the broader network connection was out to lunch.

2. Conflict Resolution and Local Ledgers

One of the biggest risks with multiple people working on the same aircraft is conflicting updates. Who gets the final say if two maintainers mark the same part as replaced? To avoid chaos, we built a real-time conflict resolution mechanism that could detect when two maintainers were trying to update the same resource. This system sent out alerts for immediate conflict resolution. And, when maintainers were offline, their local updates were recorded on a local ledger, synced up later when they reconnected.

3. Operational Process Fidelity

The other challenge was ensuring that all these distributed updates didn’t break process fidelity. We couldn’t have rogue updates disrupting operational workflows. So, we implemented blockchain backed checks both at the local ledger level and upon re-syncing to make sure nothing was out of place.

In the end, we got the best of both worlds: the agility of an event-driven API where it made sense, and a robust, mesh-based system to fill in the gaps where it didn’t. The result? Our team could operate smoothly, even with the unreliable network - maintenance records stayed intact, and conflict resolution happened in real time.

What’s the biggest roadblock you’ve hit when trying to implement an event-driven architecture? How did you (or didn’t you) work around it? Let’s hear some war stories!

#APIDevelopment #TechArchitecture #ScalableTech #SoftwareEngineering #APISecurity

https://dzone.com/articles/designing-high-performance-apis