HPA Coexistence

Attune is designed to work alongside Horizontal Pod Autoscalers (HPAs) without causing scaling conflicts or death spirals.

Why HPA + VPA was problematic

VPA and HPA both react to CPU utilization. When VPA increases requests, the utilization percentage drops, causing HPA to scale in. When HPA scales in, per-pod load increases, causing VPA to increase requests again. This feedback loop is the classic "death spiral."

How Attune avoids conflicts

Attune adjusts resource requests (and optionally limits), while HPA adjusts replica count. The operator does not change the number of pods. Because in-place resize modifies cgroup limits on running pods without restarting them, the HPA's utilization metric reflects the new allocation immediately.

The conflict detector identifies HPAs targeting the same workload and logs a notice:

HPA my-hpa targets the same Deployment/my-app; attune will adjust
requests without interfering with HPA scaling

Configuration tips

Use RequestsOnly for CPU

When an HPA uses CPU utilization as its metric, set controlledValues to RequestsOnly so that limits remain unchanged:

spec:
  cpu:
    percentile: 95
    overhead: "20"
    controlledValues: RequestsOnly
    minAllowed: "100m"
    maxAllowed: "4000m"

Tip

HPA computes utilization as usage / request. Lowering requests increases the utilization percentage, which may cause HPA to scale out. Set conservative bounds to prevent requests from dropping too far.

Set appropriate bounds

Choose a min bound for CPU that keeps the HPA utilization target in a reasonable range. For example, if HPA targets 70% utilization and pods typically use 200m, a min: "200m" prevents requests from dropping below actual usage.

Memory is always safe

Memory-based HPAs (less common) scale on memory utilization, not requests. Attune can safely adjust memory requests alongside a memory-based HPA because the working set size does not change when the request changes.

Monitoring coexistence

Watch both HPA and AttunePolicy status together:

kubectl get hpa,rsp -o wide

Check for conflict-related events:

kubectl get events --field-selector reason=ConflictDetected

When to avoid combining them

If your HPA scales on custom metrics that are derived from resource requests (e.g. a custom ratio metric), changes to requests may affect the scaling signal. In this case, use Recommend mode to review changes manually before applying them.