Description
Proposal
Kubernetes Workload Scaler currently has limitations with downscaling, that prevent using it to as a rollout mecanism to switch a workload with a totally diferent one (check use-case)
The proposal here is to
- Allow the use of '0' value for parameter
value
- Look at not only pod phase but also pod condition status. Currently the scaler activates with pods in running state, but it means that there may be downtime for this particular use case since Running != Ready
Use-Case
The actual use that we were trying to leverage was migration to Argo Rollouts. Currently there is no easy way to do this (even documentation recommends running both workloads in parallel and only then deleting the Deployment and work with the Rollout only). The Argo Rollout suggestion may work well within smaller companies, but at scale the whole procces may lead to a big operational overhead.
Since we use Keda and there is already a scaler that based itself into looking inside the cluster, it would be a perfect solution for these sorts of migrations, as everything is self contained (within the cluster. No external API or metrics required)
Is this a feature you are interested in implementing yourself?
Maybe
Anything else?
Discussion reference: #4393
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