Google PCA Design and plan a cloud solution architecture Practice Question
A media streaming company is deploying a new video transcoding pipeline on Google Cloud. The pipeline receives raw video files uploaded to Cloud Storage, triggers a Cloud Function that submits transcoding jobs to a Compute Engine worker pool, and stores the transcoded output in another Cloud Storage bucket. The workers are managed by a managed instance group (MIG) running a custom container image. Currently, when there is a spike in uploads, the MIG takes 5-7 minutes to scale up new workers, causing processing delays. The architect needs to reduce the time to add new workers to under 2 minutes. The workers are stateless and the container image is about 2 GB. What should the architect do?
⚠ Common exam trap
Watch out — candidates often assume increasing the minimum instance count (Option B) solves the scaling delay, but it only pre-provisions a fixed number of instances and does not address the startup latency for additional instances beyond that baseline.
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 a custom Compute Engine image that includes the container runtime and pre-pulled container
Creating a custom Compute Engine image that includes the container runtime and pre-pulls the 2 GB container image eliminates the need to download the image during scale-up. This reduces the instance startup time from 5-7 minutes to under 2 minutes, as the container is already cached locally on the image, bypassing the network pull delay.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Cloud Run instead of Compute Engine to run the transcoding workers
Why it's wrong here
Cloud Run has a request timeout of 60 minutes and is not designed for batch processing.
- ✗
Increase the minimum number of instances in the MIG to 10
Why it's wrong here
This increases baseline cost and does not reduce the time to add new workers beyond the minimum.
- ✗
Replace the Compute Engine workers with Cloud Functions to handle the transcoding
Why it's wrong here
Cloud Functions have a maximum timeout of 60 minutes and may not be suitable for long transcoding jobs.
- ✓
Create a custom Compute Engine image that includes the container runtime and pre-pulled container
Why this is correct
A custom image with the container already pulled reduces boot time as the image does not need to be downloaded.
Go deeper
Related to this question
Learn chapter
Introduction to Google Cloud Platform
Key term
Compute Engine
Compute Engine is Google Cloud's Infrastructure-as-a-Service (IaaS) offering that lets you create and run virtual machines on Google's infrastructure.
Key term
Instance group
An instance group is a collection of virtual machine instances that are managed as a single unit for scaling, load balancing, and lifecycle management in cloud computing.
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