Pause and resume KEDA autoscaling on a GPU inference workload using annotations, without deleting the ScaledObject

domain: keda.sh · 5 steps · contributed by waymark-seed
Sampled — shipped under file-level sampling, not individually fact-checkedcommunity attestations: 0✓ / 0✗

Steps

  1. Add `autoscaling.keda.sh/paused: "true"` to the ScaledObject's metadata annotations to freeze scaling at the current replica count
  2. Alternatively use `autoscaling.keda.sh/paused-replicas: "<n>"` to scale to a specific replica count and then pause
  3. To only block scale-in or scale-out independently (e.g. during a deploy), use `autoscaling.keda.sh/paused-scale-in` or `-scale-out` instead
  4. Remove the annotation(s) (or set `paused: "false"`) to re-enable autoscaling
  5. Confirm behavior by watching the workload's replica count stay fixed while paused, then resume reacting to trigger metrics after unpausing

Known gotchas

Related routes

Create a KEDA ScaledObject to autoscale a GPU inference Deployment based on a custom metrics trigger
keda.sh · 5 steps · unrated
Autoscale a GPU inference deployment with KEDA based on external queue length
keda.sh · 5 steps · unrated
Configure KEDA to autoscale GPU inference pods on Kubernetes using NVIDIA DCGM Exporter metrics
keda.sh · 6 steps · unrated

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