Error: Initialization of V2beta1HorizontalPodAutoscalerStatus

[keigohtr]

When we use create_namespaced_horizontal_pod_autoscaler of AutoscalingV2beta1Api, the response always throws an exception since it doesn't set conditions in V2beta1HorizontalPodAutoscalerStatus .

Likewise, the response of read_namespaced_horizontal_pod_autoscaler throws an exception since it doesn't set current_metrics .

I will create a PR for this.

Situaltion

• Kubernetes 1.9 via Rancher 1.6.16
• Python 3.6.3
• python kubernetes 5.0.0

[ackintosh]

#554
It might be realized by fixing the API definition:

https://github.com/kubernetes-client/python/blob/71b5abce5a4e2d747c0bb26d4eaa17eeb08f8ac5/scripts/swagger.json#L68656

      "required": [
        "currentReplicas",
        "desiredReplicas",
        "currentMetrics",
        "conditions"
      ],

Removing "currentMetrics" and "conditions" in the swagger.json ( or its original data if the json is auto-generated file) will result as same as #554 .

[ackintosh]

Similar fix: https://github.com/kubernetes/kubernetes/pull/64996/files#diff-9ce7ea8441086bf1902b4f936f4601d0

[keigohtr]

Thank you for your information. Yes we can fix this issue by hands.
I am not sure but I think this Kubernetes swagger spec is automatically generated from a code. So I believe we need to fix the original Kubernetes code for this.

[flmu]

I am facing the same issue. Are there any plans to permanently fix this problem?

Btw, the same setting can be deployed with kubectl

[zq-david-wang]

I have the same issue, and sometimes "list_namespaced_horizontal_pod_autoscaler" would raise ValueError("Invalid value for conditions, must not be None") when the hpa has not condition set yet.

And I am using 9.0.0

For create_namespaced_horizontal_pod_autoscaler, add '_preload_content=False' can help

[Anurag2408]

I am also facing the same issue. When is plan to fix this permanently?

[nollimahere]

for those of us trying to get an HPA launched in a production environment where manual mods to the python modules are otherwise unreasonable, adding an annotation in the metadata has been enough to get past this issue for me.

resource_hpa['metadata']['annotations'] = { "autoscaling.alpha.kubernetes.io/conditions": "[ {\"type\":\"ScalingLimited\",\"status\":\"True\",\"reason\":\"TooFewReplicas\",\"message\":\"who needs messages\"}]" }

so, for reference, the whole dict looks like

>>> print( cc.json.dumps( resource_hpa, indent=2 ) )
{ 
  "apiVersion": "autoscaling/v2beta1",
  "kind": "HorizontalPodAutoscaler",
  "metadata": {
    "name": "my-serviceHPA",
    "annotations": {
      "autoscaling.alpha.kubernetes.io/conditions": "[ {\"type\":\"ScalingLimited\",\"status\":\"True\",\"reason\":\"TooFewReplicas\",\"message\":\"who needs messages\"}]"
    }
  },
  "spec": {
    "scaleTargetRef": {
      "apiVersion": "extensions/v1beta1",
      "kind": "Deployment",
      "name": "my-serviceHPA"
    },
    "minReplicas": 1,
    "maxReplicas": 10,
    "metrics": [
      { 
        "pods": {
          "targetAverageValue": 60,
          "metricName": "utilizationRate"
        },
        "type": "Pods"
      }
    ]
  }
}

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