Mig Predictive Autoscaling Initialization Latency Optimization

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An organization runs a stateless API service on a Google Cloud Compute Engine Managed Instance Group (MIG). The application exhibits predictable daily traffic surges and requires approximately 4 minutes to warm up local caches and initialize runtime dependencies during scale-out events. During sudden load increases, end users observe increased latency because the active VMs become heavily saturated while newly provisioned instances are still starting up.

The MIG currently uses real-time CPU-based autoscaling with a target CPU utilization of 80% and a default initialization period of 60 seconds.

Which configuration change should the DevOps engineer implement to prevent latency degradation during peak traffic cycles while balancing infrastructure costs?

Increase the target CPU utilization to 95% and reduce the initialization period (coolDownPeriodSec) to 30 seconds to trigger faster scaling events.

Switch the autoscaling policy from CPU utilization to a Cloud Monitoring metric based on Pub/Sub unacknowledged messages with single-instance assignment.

Enable predictive autoscaling on the CPU utilization autoscaling policy and set the initialization period (coolDownPeriodSec) to 240 seconds.

Convert the Managed Instance Group to a Stateful MIG and configure schedule-based autoscaling to double instance capacity during peak hours.

Professional Cloud DevOps Engineer

Mig Predictive Autoscaling Initialization Latency Optimization

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