Google PCA Practice Question: Analysing and Optimising Technical and Business Processes
A media company runs a monthly batch pipeline that transcodes video uploads stored in Cloud Storage. The pipeline runs on a Managed Instance Group of Compute Engine VMs and typically completes in 6 hours. The VMs are only needed during this window, but the team wants to minimise the operational effort of stopping and starting the group. Which approach best optimises both cost and operational overhead?
⚠ Common exam trap
The trap here is assuming that autoscaling or cheaper VM types will address idle time, when the real cost driver is the predictable period when the group is not needed at all.
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
✓
Create an instance schedule that starts and stops the managed instance group on a recurring monthly calendar.
The workload has a known, recurring schedule, so the most efficient optimisation is to stop paying for VMs when the pipeline is not running. Instance schedules on a managed instance group start and stop instances automatically, which lowers compute cost and removes manual start/stop toil. Autoscaling, preemptible VMs, and Cloud Run do not eliminate the idle monthly window in the same controlled way.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Move the transcoding workload to a Cloud Run service with a minimum instance count of zero.
Why it's wrong here
Cloud Run scales to zero and can reduce cost for request-driven workloads, but video transcoding is a long-running, compute-intensive batch process that may exceed Cloud Run request timeouts and is not a natural fit for the service model. It would require re-architecting the pipeline, adding operational effort rather than reducing it.
- ✓
Create an instance schedule that starts and stops the managed instance group on a recurring monthly calendar.
Why this is correct
Instance schedules let you define recurring start and stop times for managed instance groups, so the VMs are not billed outside the transcode window. This directly reduces compute cost without manual intervention, and the schedule is managed centrally in Compute Engine, meeting the low operational effort requirement for a predictable monthly workload.
- ✗
Convert the VMs to preemptible instances and configure a restart policy.
Why it's wrong here
Preemptible VMs are cheaper but can be terminated at any time, which may disrupt a transcode job unless the pipeline is checkpointed. More importantly, preemptible instances still run and bill while the group is up, so the monthly idle period is not addressed. This changes the pricing model but not the fundamental scheduling problem.
- ✗
Enable autoscaling on the managed instance group based on CPU utilisation.
Why it's wrong here
Autoscaling adjusts the number of running instances in response to load, but it does not shut down the group to zero when the monthly pipeline is idle. At least one instance typically remains running, so the company continues paying for idle capacity. It also does not schedule the group around a known monthly window, so it fails the cost and operational goals.
Go deeper
Related to this question
Learn chapter
Google Cloud Compute Options Overview
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.
Key term
Batch
Batch is a cloud computing service that runs large numbers of computing jobs as a group, or batch, without needing to manage individual servers.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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