Scaling

URL:
https://<root>/services/<ServiceName>.<ServiceType>/scaling
Methods:
GET
Required Capability:
Access allowed with either the "Update", "Delete", or "Security and infrastructure" privileges, or the Publisher role
Version Introduced:
10.9

Description

The scaling resource returns the scaling and resource allocation for a specific GIS service microservice. Some of the properties can be updated using the Edit operation. All of the microservice's properties can be viewed through the Deployment resource.

Request parameter

ParameterDetails

f

The response format. The default format is html.

Values: html | json | pjson

Response properties

PropertyDetails

type

The GIS service microservice type.

Values: FeatureServer | GeometryServer | GPServer | GPSyncServer | MapServer | TileServer

deploymentId

The microservice ID.

replicas

The number of replicas for the microservice. For manual scaling, the value for both min and max should be the same. Organizations using a version of ArcGIS Enterprise on Kubernetes at 10.9.1 or higher have the option to enable autoscaling. For more information on manual scaling and autoscaling, see the Edit operation.

Example
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"replicas": {
  "min": 3,
  "max": 3,
  "scalingMode": "manual" //Added at 11.0
},

resources

The minimum and maximum resource allocations for the microservice, including the minimum memory (memoryMin) and minimum CPU (cpuMin) resources required for the microservice to start. This property can be updated using the Edit operation.

Example
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"resources": {
  "memoryMin": "500Mi",
  "cpuMin": "0.125",
  "memoryMax": "8Gi",
  "cpuMax": "4"
}

Example usage

The following is a sample request URL used to access the scaling resource:

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https://organization.domain.com/context/admin/services/MyService.MapServer/scaling?f=pjson

JSON Response example

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{
  "scalingSpec": [
    {
      "deploymentType": "MapServer",
      "replicas": {
        "min": 3,
        "max": 3,
        "scalingMode": "manual"
      },
      "deploymentId": "kui6zmtqzkjrsihh6tegq",
      "resources": {
        "memoryMin": "500Mi",
        "memoryMax": "2Gi",
        "cpuMin": "0.125",
        "cpuMax": "2"
      }
    }
  ]
}

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