[Bug]: add validation for multiple PodAutoscalers targeting the same workload

[googs1025]

Pull Request Description

[Please provide a clear and concise description of your changes here]

➜  ~ kubectl get podautoscalers -A
NAMESPACE   NAME                                 MINPODS   MAXPODS   REPLICAS   STRATEGY   AGE
default     deepseek-r1-distill-llama-8b-hpa     1         10                   HPA        13s
default     deepseek-r1-distill-llama-8b-hpa-1   1         10                   HPA        3s
➜  ~ kubectl get podautoscalers -A -oyaml
apiVersion: v1
items:
- apiVersion: autoscaling.aibrix.ai/v1alpha1
  kind: PodAutoscaler
  metadata:
    annotations:
      kubectl.kubernetes.io/last-applied-configuration: |
        {"apiVersion":"autoscaling.aibrix.ai/v1alpha1","kind":"PodAutoscaler","metadata":{"annotations":{},"labels":{"app.kubernetes.io/managed-by":"kustomize","app.kubernetes.io/name":"aibrix"},"name":"deepseek-r1-distill-llama-8b-hpa","namespace":"default"},"spec":{"maxReplicas":10,"metricsSources":[{"metricSourceType":"pod","path":"/metrics","port":"8000","protocolType":"http","targetMetric":"gpu_cache_usage_perc","targetValue":"50"}],"minReplicas":1,"scaleTargetRef":{"apiVersion":"apps/v1","kind":"Deployment","name":"deepseek-r1-distill-llama-8b"},"scalingStrategy":"HPA"}}
    creationTimestamp: "2025-10-13T13:14:40Z"
    generation: 1
    labels:
      app.kubernetes.io/managed-by: kustomize
      app.kubernetes.io/name: aibrix
    name: deepseek-r1-distill-llama-8b-hpa
    namespace: default
    resourceVersion: "9526115"
    uid: b6e089bc-322f-408e-b7b1-66a389ffed99
  spec:
    maxReplicas: 10
    metricsSources:
    - metricSourceType: pod
      path: /metrics
      port: "8000"
      protocolType: http
      targetMetric: gpu_cache_usage_perc
      targetValue: "50"
    minReplicas: 1
    scaleTargetRef:
      apiVersion: apps/v1
      kind: Deployment
      name: deepseek-r1-distill-llama-8b
    scalingStrategy: HPA
  status: {}
- apiVersion: autoscaling.aibrix.ai/v1alpha1
  kind: PodAutoscaler
  metadata:
    annotations:
      kubectl.kubernetes.io/last-applied-configuration: |
        {"apiVersion":"autoscaling.aibrix.ai/v1alpha1","kind":"PodAutoscaler","metadata":{"annotations":{},"labels":{"app.kubernetes.io/managed-by":"kustomize","app.kubernetes.io/name":"aibrix"},"name":"deepseek-r1-distill-llama-8b-hpa-1","namespace":"default"},"spec":{"maxReplicas":10,"metricsSources":[{"metricSourceType":"pod","path":"/metrics","port":"8000","protocolType":"http","targetMetric":"gpu_cache_usage_perc","targetValue":"50"}],"minReplicas":1,"scaleTargetRef":{"apiVersion":"apps/v1","kind":"Deployment","name":"deepseek-r1-distill-llama-8b"},"scalingStrategy":"HPA"}}
    creationTimestamp: "2025-10-13T13:14:50Z"
    generation: 1
    labels:
      app.kubernetes.io/managed-by: kustomize
      app.kubernetes.io/name: aibrix
    name: deepseek-r1-distill-llama-8b-hpa-1
    namespace: default
    resourceVersion: "9526138"
    uid: 127bd894-59b7-40ca-9dee-53a6a5311e2b
  spec:
    maxReplicas: 10
    metricsSources:
    - metricSourceType: pod
      path: /metrics
      port: "8000"
      protocolType: http
      targetMetric: gpu_cache_usage_perc
      targetValue: "50"
    minReplicas: 1
    scaleTargetRef:
      apiVersion: apps/v1
      kind: Deployment
      name: deepseek-r1-distill-llama-8b
    scalingStrategy: HPA
  status:
    conditions:
    - lastTransitionTime: "2025-10-13T13:14:50Z"
      message: ""
      reason: AsExpected
      status: "True"
      type: ValidSpec
    - lastTransitionTime: "2025-10-13T13:14:50Z"
      message: Scaling target apps/v1.Deployment/default/deepseek-r1-distill-llama-8b
        is already controlled by PodAutoscaler default/deepseek-r1-distill-llama-8b-hpa,
        it will not take effect
      reason: MutilPodAutoscalerConflict
      status: "False"
      type: MutilPodAutoscalerConflict
    - lastTransitionTime: "2025-10-13T13:14:50Z"
      message: desired=0, actual=0
      reason: Stable
      status: "False"
      type: ScalingActive
    - lastTransitionTime: "2025-10-13T13:14:50Z"
      message: ""
      reason: InvalidSpec
      status: "False"
      type: AbleToScale
    - lastTransitionTime: "2025-10-13T13:14:50Z"
      message: ""
      reason: ReconcilingScaleDiff
      status: "False"
      type: Ready
kind: List
metadata:
  resourceVersion: ""

Related Issues

Resolves: ##1661

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[gemini-code-assist]

Summary of Changes

Hello @googs1025, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request addresses a critical bug where the system could allow multiple "PodAutoscaler" resources to attempt to control the same underlying workload, leading to unpredictable and potentially erroneous scaling actions. The changes introduce robust validation to ensure that each scaling target is managed by only one "PodAutoscaler" at a time. This significantly improves the stability and reliability of the autoscaling functionality by preventing conflicting instructions and providing clear status feedback when such conflicts arise.

Highlights

• Conflict Prevention for PodAutoscalers: Introduced a new validation mechanism to prevent multiple "PodAutoscaler" resources from simultaneously targeting the same workload, ensuring predictable autoscaling behavior.
• Internal State Management: Implemented internal maps ("scalingTargetToPA", "paToScalingKey") within the "PodAutoscalerReconciler" to track and manage which "PodAutoscaler" controls which scaling target, along with a mutex for thread safety.
• Enhanced Status Conditions: Added a new "MutilPodAutoscalerConflict" status condition to clearly indicate when a "PodAutoscaler" is in a conflicting state, and updated the "AbleToScale" and "Ready" conditions to reflect this conflict status.
• Resource Deletion Cleanup: Added logic to automatically clean up the internal conflict tracking state when a "PodAutoscaler" resource is deleted, preventing stale entries.

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[gemini-code-assist]

Code Review

This pull request introduces validation to prevent multiple PodAutoscalers from targeting the same workload, enhancing the stability and predictability of autoscaling behavior. The changes include adding a new condition type, implementing conflict checks, and updating the status computation to reflect potential conflicts. I have identified a critical issue regarding potential race conditions in the conflict checking logic that needs to be addressed.

[gemini-code-assist]

Consider combining these two lines into a single line for better readability.

Suggested change

	specOK := specValidationResult.Valid
	noConflict := conflictValidationResult.Valid
	noConflict := conflictValidationResult.Valid
	noConflict := conflictValidationResult.Valid

[Jeffwan]

For deployment, this is good. For stormservice, we expected multiple hpa rules created for same workloads. https://aibrix.readthedocs.io/latest/features/autoscaling/metric-based-autoscaling.html#stormservice-role-level-autoscaling

in this case, we do not want the validation. is this PR against pool autoscaling pattern?