The mean rate in Kafka metrics, as reported by the Kafka broker or client libraries, is typically calculated based on the exponential moving average (EMA). This is different from the 1-minute, 5-minute, and 15-minute average rates, which are explicitly calculated over those specific time windows.
The mean rate can appear significantly lower for a few reasons:
While the mean rate gives more weight to recent data, it still includes older data points, which can pull the average down if there were periods of low activity.
If the metric has been running for a long time, the mean rate will include data from the entire lifetime, including periods of low activity
If your Kafka cluster experiences bursty traffic (spikes in message production or consumption), the short-term rates will reflect those spikes, while the mean rate will smooth them out over time.
The mean rate is useful for understanding the long-term average behavior of your Kafka system.