Autoscaling Controller  ·  View 11 of 37  ·  2 · Structure

Authority and Arbitration

A workload policy, a schedule, a forecast and a human can all target the same fleet. One of them wins, and it is decided in one place.

Editable source SVG draw.io All views
Claimants Workload Policy target tracking Scheduled Policy floor or ceiling Forecast Floor may not undercut Operator Override expires in 4 h Single admission point Precedence Rules per target Combination Rule max out · min in Hard Bounds no claimant exceeds Declared Desired Capacity the workload layer Derived Node Layer Follows purely derivative Unmet Demand when it cannot cannot supply back as a signal Authority — Four Things Want to Scale One Fleet Application we own Person or role Decision point Security / platform Data store Risk / gap failure / alternate event / async Authority is strictly layered and arbitrated in one place. The infrastructure layer is derivative of the workload layer, and says so out loud when it cannot supply what was declared. v 1.0 · owner Data & AI Global Practice · date 2026-09

The decision

  • Authority is strictly layered and arbitrated at a single admission point: the workload layer declares, the infrastructure layer follows.
  • Combination is asymmetric — maximum on scale-out, minimum agreed on scale-in — so one claimant may raise capacity and none may lower it alone.
  • Hard bounds apply after arbitration, so no claimant, including an operator, can exceed a target's declared maximum from inside the controller.

When the layer below cannot supply

  • The node layer never invents a number. If it cannot supply what the workload layer declared, it emits unmet demand.
  • Unmet demand re-enters the loop as a signal, which is what lets a policy react to scarcity instead of the reconciler retrying into it.

Rejected alternatives

  • Precedence rules per target without a single admission point: cheap to build, impossible to reason about once two targets share a node pool.
  • Letting both autoscalers act independently: the standard failure is the node autoscaler removing a node the workload autoscaler is about to fill.