Hi, you may upgrade Flink to 1.19.3 or 1.20.2 or 2.0.1+. There's a known issue that Autoscaler may not minimize the number of TMs during downscaling with adaptive scheduler [1].
[1] https://issues.apache.org/jira/browse/FLINK-33977 Best, Zhanghao Chen ________________________________ From: Salva Alcántara <salcantara...@gmail.com> Sent: Wednesday, August 13, 2025 20:56 To: user <user@flink.apache.org> Subject: RE: Autoscaling Global Scaling Factor (???) BTW, I'm running on Flink 1.18.1 on top of operator 1.12.1 and the following autoscaler settings: ``` job.autoscaler.enabled: "true" job.autoscaler.scaling.enabled: "true" job.autoscaler.scale-down.enabled: "true" job.autoscaler.vertex.max-parallelism: "8" job.autoscaler.vertex.min-parallelism: "1" jobmanager.scheduler: adaptive job.autoscaler.metrics.window: 15m job.autoscaler.metrics.busy-time.aggregator: MAX job.autoscaler.backlog-processing.lag-threshold: 2m job.autoscaler.scaling.effectiveness.detection.enabled: "true" job.autoscaler.scaling.effectiveness.threshold: "0.3" job.autoscaler.scaling.event.interval: 10m job.autoscaler.stabilization.interval: 5m job.autoscaler.scale-up.max-factor: "100000.0" job.autoscaler.scaling.key-group.partitions.adjust.mode: "EVENLY_SPREAD" job.autoscaler.scale-down.interval: 30m job.autoscaler.scale-down.max-factor: "0.5" job.autoscaler.memory.tuning.scale-down-compensation.enabled: "true" job.autoscaler.catch-up.duration: 5m job.autoscaler.restart.time: 15m job.autoscaler.restart.time-tracking.enabled: "true" job.autoscaler.utilization.target: "0.8" ``` Regards, Salva
