Not enough valid window error

[kspmmitt]

Hello,

Got frequent error in cruise control logs as below and as per troubleshoot guide not clear with reason of error? It talks about possible reasons but how to verify it? ()

{"version": "1.2.0", "timestamp": "2025-08-02T04:45:31.281+00:00", "severity": "error", "service_id": "eric-data-messagebus-kf", "message": "Error processing POST request '/rebalance' due to: 'com.linkedin.kafka.cruisecontrol.exception.KafkaCruiseControlException: com.linkedin.cruisecontrol.exception.NotEnoughValidWindowsException: There are only 0 valid windows when aggregating in range [-1, 1754109931273] for aggregation options (minValidEntityRatio=1.00, minValidEntityGroupRatio=0.00, minValidWindows=1, numEntitiesToInclude=181, granularity=ENTITY)'. java.util.concurrent.ExecutionException: com.linkedin.kafka.cruisecontrol.exception.KafkaCruiseControlException: com.linkedin.cruisecontrol.exception.NotEnoughValidWindowsException:

[kyguy]

A couple of ways to verify this error listed in the Troubleshooting Guide [1]:

1. Give Cruise Control around 5-10m to collect metric samples it needs for creating valid sample windows.

2. If that doesn't work, check through the Kafka broker logs to see if there are any produce errors from the CruiseControlMetricReporter agents which are responsible for sending Kafka metrics to the configured cruise.control.metrics.topic topic.

3. If there are no errors in the broker logs concerning the CruiseControlMetricReporter agents, check the Cruise Control server logs for producer or consumer errors to or from any of the three Cruise Control topics - metric.reporter.topic, partition.metric.sample.store.topic, or broker.metric.sample.store.topic.

[1] https://github.com/linkedin/cruise-control/wiki/Troubleshooting#notenoughvalidwindowsexception---not-enough-windows-available-in-range

[kspmmitt]

I saw troubleshooting guide as it is mentioned above.

My query was why this exception comes, or it can be refined as per scenarios?

Also, this initial delay can be given as mentioned in 1) above. I am using strimzi operator-based Kafka in Kubernetes type deployment.

[kyguy]

My query was why this exception comes

To build an accurate model of the Kafka cluster, Cruise Control averages the raw metric data it collects from Kafka. Without this smoothing, the model used to make partition movement decisions would be overly sensitive to temporary metric spikes. Therefore, Cruise Control blocks on providing optimization proposals until it has had enough time to gather sufficient metrics to stabilize its internal cluster model.

or it can be refined as per scenarios?

I am sure the sampling configurations could be fine tuned to be more effective for specific use cases but the default configurations should suffice for most scenarios.