mediumMultiple Choice
Google ACE Practice Question: A managed instance group (MIG) is running 4 VMs…
A managed instance group (MIG) is running 4 VMs with a CPU autoscaling target of 60%. A traffic spike drives average CPU to 90%. How does the autoscaler respond?
⚠ Common exam trap
Google Cloud often tests the misconception that autoscaling involves modifying existing instances (e.g., restarting, migrating, or resizing) rather than simply adding or removing instances based on a target metric.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The autoscaler adds VMs until average CPU across the group drops to approximately 60%
The autoscaler for a managed instance group (MIG) uses a target utilization metric—here, CPU at 60%. When average CPU exceeds that target (90%), the autoscaler calculates the desired number of VMs to bring utilization back to 60% (e.g., 4 VMs * 90% / 60% = 6 VMs) and adds instances accordingly. It does not terminate, migrate, or restart VMs; it scales out horizontally.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The MIG terminates the 2 least-used VMs to trigger a restart with higher performance settings
Why it's wrong here
Autoscaling never terminates VMs during a traffic spike; that would remove capacity exactly when demand is high. The autoscaler responds to elevated average CPU by adding instances, not by killing the least-used ones. Also, an instance's performance settings are fixed by its machine type/template, so terminating and restarting cannot grant higher performance. Termination for scale-in only occurs during sustained low utilization, not spikes.
- ✓
The autoscaler adds VMs until average CPU across the group drops to approximately 60%
Why this is correct
The autoscaler uses the target CPU utilization (e.g., 60%) to compute desired capacity: if the group's average CPU is above target, it calculates how many VMs are needed so that average utilization drops back to that level and provisions additional instances. For example, if 5 VMs run at 80%, it targets 7 VMs (5*0.8/0.6 ≈ 6.67) to bring average CPU to ~57%. This scale-out distributes load across new instances, reducing per-VM CPU demand. The autoscaler keeps adding until the measured average falls to approximately the target.
- ✗
The MIG live-migrates instances to larger machine types automatically
Why it's wrong here
Autoscaling in a MIG only adjusts the number of instances; it cannot change the machine type of running VMs. Live migration is a Google Compute Engine maintenance feature that moves VMs to different hosts without changing their configuration or resizing them. To move to larger machine types, you must create a new instance template with the desired machine type and perform a rolling update or recreate the group. The autoscaler is not involved in that decision.
- ✗
The MIG restarts all existing VMs to clear cached load
Why it's wrong here
The autoscaler does not restart existing VMs to 'clear cached load'; restarting would cause downtime and does nothing to reduce traffic on each instance. Instead, autoscaling responds to high load by creating new instances and adding them to the load balancer's backend service, which spreads incoming requests across a larger pool. Restarting all VMs would temporarily flush out connections and worsen the spike, whereas scale-out adds capacity without disrupting existing sessions. Cached data is not the trigger; CPU utilization is the metric.
Go deeper
Related to this question
Learn chapter
Instance Templates and Managed Instance Groups
Key term
Autoscaler
An Autoscaler is a cloud service that automatically increases or decreases the number of virtual machines (instances) or resources based on real-time demand, so your application always has enough capacity without wasting money on idle servers.
Key term
Managed instance group
A managed instance group is a collection of identical virtual machine instances that are automatically managed as a single unit to ensure high availability and scalability.
About these practice questions
This ACE question is part of Courseiva's 775-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This ACE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the ACE exam.