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The dashboard shows yesterday's numbers, and the business wants today's, updating as events arrive.
What you'll have at the end
A Kafka Streams app producing a five-minute windowed count to an output topic, checked against a hand-counted sample
You need
An orders Kafka topic already receiving live records keyed by store ID, and a JVM project set up to build and run a Kafka Streams application against your cluster.
Not covered
Running this app across more than one instance in production, and what the dashboard does with the output topic once it exists.
Leans on
Decide whether a pipeline can tolerate duplicate Kafka messages or needs exactly-once
when a restart or rebalance must never double count a single order, a stronger guarantee than the running total merely surviving intact.
Read a Kafka topic into a Spark Structured Streaming job
when the team already runs Spark for everything else and would rather reuse that engine than stand up a second JVM app for one windowed count.
Checked 26 Aug 2026
Part of the Apache Kafka cookbook