That was on my agenda already. Will try and let you know how it goes. Regarding my questions, do you think it's possible to achieve any of those points to make the autoscaler work as when you simply add/remove replicas by hand?
Thanks Chen! Salva On Thu, Aug 14, 2025 at 2:58 AM Zhanghao Chen <zhanghao.c...@outlook.com> wrote: > 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 >
