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Using Flink Stateful Functions

Igal Shilman gives us an example of where Apache Flink’s Stateful Functions come in handy:

In this blog post, we’ll take a look at a class of use cases that is a natural fit for Flink Stateful Functions: monitoring and controlling networks of connected devices (often called the “Internet of Things” (IoT)).

IoT networks are composed of many individual, but interconnected components, which makes getting some kind of high-level insight into the status, problems, or optimization opportunities in these networks not trivial. Each individual device “sees” only its own state, which means that the status of groups of devices, or even the network as a whole, is often a complex aggregation of the individual devices’ state. Diagnosing, controlling, or optimizing these groups of devices thus requires distributed logic that analyzes the “bigger picture” and then acts upon it.

A powerful approach to implement this is using digital twins: each device has a corresponding virtual entity (i.e. the digital twin), which also captures their relationships and interactions. The digital twins track the status of their corresponding devices and send updates to other twins, representing groups (such as geographical regions) of devices. Those, in turn, handle the logic to obtain the network’s aggregated view, or this “bigger picture” we mentioned before.

Read on to see where stateful functions come into play.