Event-driven architectures like this are a relatively common design pattern in distributed systems. Like other distributed development models, they have their own problems, especially at scale. When you’re getting tens or hundreds of events a minute, it’s easy to detect and respond to the messages you’re looking for. But when your application or service grows to several hundred thousands or even millions of messages across a global platform, what worked for a smaller system is likely to collapse under this new load.
At scale, event-driven systems become complex. Messages and events are delivered in many different forms and stored in independent silos, making them hard to extract and process and often requiring complex query mechanisms. At the same time, message queuing systems become slow and congested, adding latency or even letting messages time out. When you need to respond to events quickly, this fragile state of affairs becomes hard to use and manage.
That’s where Drasi comes in. It provides a better way to automate the process of detecting and responding to relevant events, an approach Microsoft describes as “the automation of intelligent reactions.” It is intended to be a lightweight tool that doesn’t need a complex, centralized store for event data, instead taking advantage of decentralization to look for events close to where they’re sourced, in log files and change feeds.