When implementing a stream processor function, we often need more information than is available in the current event object. It is a best practice when publishing events to include all the relevant data that is available in the publishing context so that each event represents a micro snapshot of the system at the time of publishing. When this data is not enough, we need to retrieve more data; however, in cloud-native systems, we strive to eliminate all synchronous inter-service communication because it reduces the autonomy of the services. Instead, we create a micro event store that is tailored to the needs of the specific service.
First, we implement a listener function and filter for the desired events from the stream. Each ...
