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Scaling based on CPU utilization | Compute Engine Documentation

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The simplest form of autoscaling is to scale a managed instance group (MIG) based on the CPU utilization of its instances.

You can also autoscale a MIG based on the load balancing serving capacity, Monitoring metrics, or schedules.

• Review the autoscaler limitations.
• Read about autoscaler fundamentals.
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You can autoscale based on the average CPU utilization of a managed instance group (MIG). Using this policy tells the autoscaler to collect the CPU utilization of the instances in the group and determine whether it needs to scale. You set the target CPU utilization the autoscaler should maintain and the autoscaler works to maintain that level.

The autoscaler treats the target CPU utilization level as a fraction of the average use of all vCPUs over time in the instance group. If the average utilization of your total vCPUs exceeds the target utilization, the autoscaler adds more VM instances. If the average utilization of your total vCPUs is less than the target utilization, the autoscaler removes instances. For example, setting a 0.75 target utilization tells the autoscaler to maintain an average utilization of 75% among all vCPUs in the instance group.

You can also scale based on forecasted CPU utilization. For more information, and to see if this is suitable for your workload, see Scaling based on predictions.

To perform this task, you must have the following permissions:

• compute.autoscalers.create on the project
• compute.instanceGroupManagers.use on the project

1. In the console, go to the Instance groups page.

   Go to Instance groups

2. If you have an instance group, click the name of the instance group, and then click Edit. On the edit instance group page, do the following:

   1. Click Group size & autosclaing to expand the section.
   2. Click Configure autoscaling.

3. If you don't have an instance group, click Create instance group and do the following:

   1. In the Name field, specify a name for the group.
   2. In the Instance template list, select a template.

   3. In the Location section, depending on whether you're creating a zonal or regional MIG, choose an option as follows:

      • For a zonal MIG, select Single zone, and then select a region and a zone.
      • For a regional MIG, select Multiple zones, and then select a region and zones.

4. In the Autoscaling section, a CPU utilization autoscaling signal is added by default. You can either use the default values for the signal or do the following:

   1. Specify the minimum and the maximum numbers of instances that you want the autoscaler to create in this group.

   2. To edit the target CPU utilization, click the CPU utilization signal to expand the section and specify the percentage.

      1. Under Predictive autoscaling, select Off. To learn more about predictive autoscaling, and whether it is suitable for your workload, see Scaling based on predictions.

   3. Click Done.

5. You can use the Initialization period to tell the autoscaler how long it takes for your application to initialize. Specifying an accurate initialization period improves autoscaler decisions. For example, when scaling out, the autoscaler ignores data from VMs that are still initializing because those VMs might not yet represent normal usage of your application. The default initialization period is 60 seconds.

6. Click Save.

Use the set-autoscaling sub-command to enable autoscaling for a managed instance group. For example, the following command creates an autoscaler that has a target CPU utilization of 60%. Along with the --target-cpu-utilization parameter, the --max-num-replicas parameter is also required when creating an autoscaler:

gcloud compute instance-groups managed set-autoscaling example-managed-instance-group \
    --max-num-replicas 20 \
    --target-cpu-utilization 0.60 \
    --cool-down-period 90

You can use the --cool-down-period flag to set the initialization period, which tells the autoscaler how long it takes for your application to initialize. Specifying an accurate initialization period improves autoscaler decisions. For example, when scaling out, the autoscaler ignores data from VMs that are still initializing because those VMs might not yet represent normal usage of your application. The default initialization period is 60 seconds.

Optionally, you can enable predictive autoscaling to scale out ahead of predicted load. To learn whether predictive autoscaling is suitable for your workload, see Scaling based on predictions.

You can verify that autoscaling is successfully enabled by using the instance-groups managed describe sub-command, which describes the corresponding managed instance group and provides information about any autoscaling features for that instance group:

gcloud compute instance-groups managed describe example-managed-instance-group

For a list of available gcloud commands and flags, see the gcloud reference.

To create an autoscaler, use the autoscalers.insert method for a zonal MIG or the regionAutoscalers.insert method for a regional MIG.

The following example creates an autoscaler for a zonal MIG:

POST https://compute.googleapis.com/compute/v1/projects/PROJECT_ID/zones/ZONE/autoscalers/

Your request body must contain the name, target, and autoscalingPolicy fields. autoscalingPolicy must define cpuUtilization and maxNumReplicas.

You can use the coolDownPeriodSec field to set the initialization period, which tells the autoscaler how long it takes for your application to initialize. Specifying an accurate initialization period improves autoscaler decisions. For example, when scaling out, the autoscaler ignores data from VMs that are still initializing because those VMs might not yet represent normal usage of your application. The default initialization period is 60 seconds.

Optionally, you can enable predictive autoscaling to scale out ahead of predicted load. To learn whether predictive autoscaling is suitable for your workload, see Scaling based on predictions.

{
  "name": "example-autoscaler",
  "target": "https://www.googleapis.com/compute/v1/projects/myproject/zones/us-central1-f/instanceGroupManagers/example-managed-instance-group",
  "autoscalingPolicy": {
    "maxNumReplicas": 10,
    "cpuUtilization": {
      "utilizationTarget": 0.6
    },
    "coolDownPeriodSec": 90
  }
}

For more information about enabling autoscaling based on CPU utilization, complete the tutorial, Using autoscaling for highly scalable apps.

During periods of heavy CPU utilization, if utilization is close to 100%, the autoscaler estimates that the group might already be heavily overloaded. In these cases, the autoscaler increases the number of virtual machines by 50% at most.

• Learn how to enable predictive autoscaling.
• Learn about managing autoscalers.
• Learn how autoscalers make decisions.
• Learn how to use multiple autoscaling signals to scale your group.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2025-08-07 UTC.

[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-07 UTC."],[[["Autoscaling for managed instance groups (MIGs) can be based on the CPU utilization of its instances, allowing for automatic scaling in response to changes in demand."],["In addition to CPU utilization, MIGs can also be scaled based on load balancing serving capacity, monitoring metrics, or predefined schedules."],["Setting the target CPU utilization allows the autoscaler to adjust the number of instances, adding more when utilization exceeds the target and removing instances when it's below the target."],["The initialization period setting is crucial, as it tells the autoscaler how long an application takes to initialize, thereby improving the accuracy of scaling decisions."],["During periods of heavy CPU utilization, when utilization approaches 100%, the autoscaler will increase the number of virtual machines by no more than 50%, to help prevent overloading."]]],[]]

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