easyMultiple Choice
PMLE Practice Question: A user receives the error "Deployment failed due…
Exhibit
Refer to the exhibit: $ gcloud ai endpoints deploy-model $ENDPOINT_ID \ --model $MODEL_ID \ --display-name=my-model \ --machine-type=n1-standard-2 \ --min-replica-count=1 \ --max-replica-count=5 \ --traffic-split=0=100 ERROR: (gcloud.ai.endpoints.deploy-model) RESOURCE_EXHAUSTED: The machine type n1-standard-2 is not available in region us-central1 for AutoML models.
A user receives the error "Deployment failed due to insufficient memory. Please use a machine type with higher memory." when deploying an AutoML model. What should they do?
⚠ Common exam trap
Test-takers frequently confuse scaling (increasing replicas) with resource allocation (increasing memory per replica), leading them to choose Option C instead of addressing the per-instance memory bottleneck.
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
✓
Use machine type n1-highmem-2
When deploying an AutoML model, memory constraints are a common cause of deployment failures. Using a machine type with higher memory, such as n1-highmem-2, helps ensure the model can be loaded and served without out-of-memory errors. The other options do not address memory requirements: changing the region does not affect compute resources, increasing the min replica count does not increase per-instance memory, and removing traffic-split flags does not resolve memory issues.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Change the region to us-west1
Why it's wrong here
Changing region alters where the endpoint is hosted but not the machine type's memory, so the same deployment error recurs. It is tempting for latency or quota reasons, but the message explicitly requires a machine type with higher memory.
- ✓
Use machine type n1-highmem-2
Why this is correct
The error indicates the chosen machine type has insufficient RAM for the AutoML model. n1-highmem-2 supplies 13 GB of memory with a high memory-to-vCPU ratio, directly resolving the constraint, whereas standard or compute-optimised types offer less memory per core.
- ✗
Increase the min-replica-count to 2
Why it's wrong here
Raising min-replica-count adds more identical replicas, each still sized to the same insufficient machine type, so the memory error persists. It is tempting for availability or throughput scaling, but the fix here is selecting a machine type with more memory.
- ✗
Remove the traffic-split flag
Why it's wrong here
The traffic-split flag controls request routing between model versions and has no bearing on the memory allocated to the deployment. It is tempting when tuning serving behaviour, but the error names insufficient memory, so a machine type with more RAM is required.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PMLE 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 PMLE exam.