The autoscaler only works for FlinkDeployments in Native mode. You should
turn off the reactive scheduler mode as well because that's something
completely different.
After that you can check the autoscaler logs for more info.

Gyula

On Tue, Aug 1, 2023 at 10:33 AM Raihan Sunny via user <user@flink.apache.org>
wrote:

> Hi,
>
> I have a workload that depends on the GPU. I have only 1 GPU card. As per
> the documentation I have added the necessary configurations and can run the
> GPU workload in standalone REACTIVE mode with as many taskmanager instances
> as required.
>
> I have set the number of task slots to 1 so that a raise in parallelism
> causes a new pod to be created. I can scale up the job just fine in this
> mode, however when I add autoscaling configurations to the FlinkDeployment
> manifest, scaling up doesn't work. This is because with the autoscaling
> manifest, there seems to be resource requests and limits are being
> automatically set to the pods for the gpu. This is not the case with the
> standalone mode which is why I guess scaling up doesn't cause any issues.
>
> So, what can I do to get the autoscaler working? I'm using Flink version
> 1.17.1 with PyFlink and Flink Kubernetes Operator version 1.5.0.
>
>
> Regards,
> Sunny
>
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