- A
Switch to GKE Standard cluster to remove resource minimums.
Why wrong: Switching clusters is a major architectural change. The correct fix is to set appropriate resource requests that meet Autopilot's minimums.
- B
Set resource requests to at least 250m CPU and 512Mi memory to meet Autopilot's pod minimums.
GKE Autopilot enforces minimum resource requests. Setting requests at or above the minimum (250m CPU, 512Mi memory) allows the pod to be scheduled.
- C
Add a LimitRange to the namespace to override Autopilot's minimum requirements.
Why wrong: LimitRange sets default and max limits within a namespace but cannot override Autopilot's enforced platform-level minimums. Autopilot's admission controller takes precedence.
- D
Set `resources: {}` (empty) to let Autopilot choose the correct resource allocation automatically.
Why wrong: An empty resources block leaves requests unset. Autopilot may mutate the pod to apply defaults, but specific workloads should have appropriate requests set to ensure correct scheduling and billing.
How to Fix Autopilot Rejected Pod: Set Minimum CPU and Memory Requests
This ACE practice question tests your understanding of configuring a gke autopilot cluster. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are configuring a GKE Autopilot cluster. A developer reports that their pod keeps being rejected with: `Autopilot rejected pod: resource request 0.5 vCPU and 64Mi memory is below minimum`. What should the developer do?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Quick Answer
The correct fix is to set resource requests to at least 250m CPU and 512Mi memory to meet Autopilot’s pod minimums. This is required because GKE Autopilot enforces a floor of 0.5 vCPU (500m) and 512Mi memory per pod, and the developer’s request of 0.5 vCPU with only 64Mi memory fails the memory threshold. On the Google Associate Cloud Engineer exam, this scenario tests your understanding that Autopilot’s managed infrastructure imposes non-negotiable minimums—unlike Standard mode, where you can set arbitrarily low requests. A common trap is assuming the CPU minimum is the only constraint, but memory is equally critical; the error message explicitly calls out both resources. Remember the mnemonic “500 and 512” for the absolute minimums, but note that the correct answer uses 250m CPU because the question’s “0.5 vCPU” already meets the CPU floor, so the fix focuses on raising memory to 512Mi.
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
Set resource requests to at least 250m CPU and 512Mi memory to meet Autopilot's pod minimums.
B is correct because GKE Autopilot enforces minimum resource requests per pod: at least 250m CPU and 512Mi memory. The developer's request of 0.5 vCPU (500m) and 64Mi memory meets the CPU minimum but fails the memory minimum. Therefore, setting requests to at least 250m CPU and 512Mi memory satisfies both minimums. Note that the CPU request can be lowered to 250m as long as it meets the minimum; the pod will not be rejected if the request is at or above the threshold. This is a hard constraint of Autopilot's managed infrastructure and cannot be overridden by LimitRange or other mechanisms.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch to GKE Standard cluster to remove resource minimums.
Why it's wrong here
Switching clusters is a major architectural change. The correct fix is to set appropriate resource requests that meet Autopilot's minimums.
- ✓
Set resource requests to at least 250m CPU and 512Mi memory to meet Autopilot's pod minimums.
Why this is correct
GKE Autopilot enforces minimum resource requests. Setting requests at or above the minimum (250m CPU, 512Mi memory) allows the pod to be scheduled.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Add a LimitRange to the namespace to override Autopilot's minimum requirements.
Why it's wrong here
LimitRange sets default and max limits within a namespace but cannot override Autopilot's enforced platform-level minimums. Autopilot's admission controller takes precedence.
- ✗
Set `resources: {}` (empty) to let Autopilot choose the correct resource allocation automatically.
Why it's wrong here
An empty resources block leaves requests unset. Autopilot may mutate the pod to apply defaults, but specific workloads should have appropriate requests set to ensure correct scheduling and billing.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that Autopilot's minimums are configurable via LimitRange or that empty resource requests will automatically assign compliant values, when in fact the minimums are hard-coded and must be explicitly met in the pod spec.
Detailed technical explanation
How to think about this question
GKE Autopilot uses an admission webhook that validates pod resource requests against predefined minimums (0.5 vCPU, 512Mi memory) and maximums (110 vCPU, 624Gi memory per pod). These minimums ensure each pod has sufficient resources for the node's system components (kubelet, container runtime, etc.) and prevent resource fragmentation. In practice, if a developer needs a smaller pod, they must either combine workloads into a single pod or use GKE Standard with a custom node pool that allows smaller resource allocations.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this ACE question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Set resource requests to at least 250m CPU and 512Mi memory to meet Autopilot's pod minimums. — B is correct because GKE Autopilot enforces minimum resource requests per pod: at least 250m CPU and 512Mi memory. The developer's request of 0.5 vCPU (500m) and 64Mi memory meets the CPU minimum but fails the memory minimum. Therefore, setting requests to at least 250m CPU and 512Mi memory satisfies both minimums. Note that the CPU request can be lowered to 250m as long as it meets the minimum; the pod will not be rejected if the request is at or above the threshold. This is a hard constraint of Autopilot's managed infrastructure and cannot be overridden by LimitRange or other mechanisms.
What should I do if I get this ACE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
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