Console

1. In the Google Cloud console, go to theInstance groups page.

   Go to Instance groups

2. Click the name of a MIG from the list.

3. ClickEdit.

4. ClickGroup size & autoscaling to expand the section.

5. In theAutoscaling mode list, make sure thatOn: add and remove instances to the group is selected.

6. In theMinimum number of instances field, enter the minimum numberof VMs that you want for this MIG. The minimum size of this MIG isalways maintained regardless of its autoscaling signals.

7. In theMaximum number of instances field, enter the maximum numberof VMs that you want for this MIG. The maximum size of this MIG is neverexceeded regardless of the recommended size generated by its autoscalingsignals.

8. For eachmetric-based autoscaling signalthat you want to add, clickAdd a signal.

   • To create an autoscaling signal based on average CPU utilization,in theSignal type list, selectCPU utilization. Then, enteraTarget CPU utilization and clickDone.For more information, seeScaling based on CPU utilization.
   • To create an autoscaling signal based on HTTP load balancing servingcapacity, in theSignal type list, selectHTTP load balancing utilization. Then, enter aTarget HTTP load balancing utilization andclickDone. For more information, seeScaling based on load balancing serving capacity.
   • To create an autoscaling signal based on Cloud Monitoring metrics,in theSignal type list, selectCloud Monitoring metric. Then,complete the remaining fields and clickDone. For moreinformation, seeScaling based on Cloud Monitoring metrics.

9. For each schedule-based autoscaling signal that you want to add, in theAutoscaling schedules section, clickManage.

   1. ClickCreate schedule.

   2. In theCreate scaling schedule pane, complete the requiredfields, and then clickSave.

   3. In theScaling schedules pane, clickDone.

   For more information, seeScaling based on schedules.

10. In theInitialization period section, enter the number of secondsthat your application needs to initialize. This period lets your VMsfinish initializing before the autoscaler considers its usage datareliable. For more information, seeInitialization period.

11. Optional: to enable scale-in controls, in theScale-in controlssection, select theEnable scale-in controls checkbox. For moreinformation, seescale-in controls

12. ClickSave.

gcloud

To create an autoscaler with multiple signals, use theset-autoscaling command.Pass in multiple signal specifications using their respectivecommand-line flags.

For example, the following command createsan autoscaler that uses CPU utilization, load balancing serving capacity,two custom metrics, and one scaling schedule. The--max-num-replicas and--min-num-replicas flags restrict how bigor small the MIG can get.

gcloud compute instance-groups managed set-autoscalingMIG_NAME \   --target-cpu-utilization=0.8 \   --target-load-balancing-utilization=0.6 \   --custom-metric-utilization metric=PATH_TO_CUSTOM_METRIC_1,utilization-target=1000.0,utilization-target-type=GAUGE \   --custom-metric-utilization metric=PATH_TO_CUSTOM_METRIC_2,utilization-target=2000.0,utilization-target-type=DELTA_PER_SECOND \   --set-schedule=workday-capacity \   --schedule-cron="30 8 * * Mon-Fri" \   --schedule-duration-sec=30600 \   --schedule-min-required-replicas=10 \   --schedule-description="Have at least 10 VMs every Monday through Friday from 8:30 AM to 5 PM UTC" \   --min-num-replicas=1 \   --max-num-replicas=50

Replace the following:

• MIG_NAME: the name of a MIG.
• PATH_TO_CUSTOM_METRIC_1 andPATH_TO_CUSTOM_METRIC_2: Optional: the paths tocustom metrics with a format similar tocustom.cloudmonitoring.googleapis.com/path/to/metric1 andcustom.cloudmonitoring.googleapis.com/path/to/metric2. For moreinformation, seeCustom metrics.

With the exception of the custom metric flags, you can only pass in one flagmaximum for each metric type pergcloud command. For custom metrics, youcan provide multiple custom metrics in a single command by repeatingthe--custom-metric-utilization flag.

For more information about how to configure the flags for each type ofautoscaling signal, see the following pages:

• Scaling based on CPU utilization
• Scaling based on load balancing serving capacity
• Scaling based on Cloud Monitoring metrics
• Scaling based on schedules

REST

To create an autoscaler, use theautoscalers.insert methodfor a zonal MIG or theregionAutoscalers.insert methodfor a regional MIG.

For example, the following request creates anautoscaler that uses CPU utilization, load balancingserving capacity, two custom metrics, and two scaling schedules. ThemaxNumReplicas andminNumReplicas fields restrict how big orsmall the MIG can get.

POST https://compute.googleapis.com/compute/v1/projects/PROJECT/zones/ZONE/autoscalers{  "autoscalingPolicy" : {    "cpuUtilization":{      "utilizationTarget": 0.8    },    "loadBalancingUtilization":{      "utilizationTarget": 0.6    },    "customMetricUtilizations":[      {        "metric": "PATH_TO_CUSTOM_METRIC_1",        "utilizationTarget": 1000,        "utilizationTargetType":"GAUGE"      },      {        "metric": "PATH_TO_CUSTOM_METRIC_2",        "utilizationTarget": 2000,        "utilizationTargetType": "DELTA_PER_SECOND"      }    ],    "scalingSchedules": {      "workday-capacity": {        "minRequiredReplicas": 10,        "schedule": "30 8 * * Mon-Fri",        "durationSec": 30600,        "description": "Have at least 10 VMs every Monday through Friday from 8:30 AM to 5 PM UTC"      },      "january-30-2030-schedule": {        "minRequiredReplicas": 30,        "schedule": "0 0 30 1 * 2030",        "timeZone": "America/New_York",        "durationSec": 86400,        "description": "Schedule a minimum of 30 VMs all day for January 30, 2030"      }    },    "maxNumReplicas": 50,    "minNumReplicas": 1  },  "target": "https://www.googleapis.com/compute/v1/projects/myproject/zones/us-central1-a/instanceGroupManagers/MIG_NAME",  "name": "MIG_NAME"}

Replace the following:

• PROJECT: yourproject id.
• ZONE: the zone where your MIG is located.
• MIG_NAME: the name of a MIG.
• PATH_TO_CUSTOM_METRIC_1 andPATH_TO_CUSTOM_METRIC_2: Optional: the paths tocustom metrics with a format similar tocustom.cloudmonitoring.googleapis.com/path/to/metric1 andcustom.cloudmonitoring.googleapis.com/path/to/metric2. For moreinformation, seeCustom metrics.

As shown in this example, you can provide multiple custom metrics andscaling schedules in the same request.

For more information about how to configure the fields for each type ofautoscaling signal, see the following pages:

• Scaling based on CPU utilization
• Scaling based on load balancing serving capacity
• Scaling based on Cloud Monitoring metrics
• Scaling based on schedules