Google Cloud Certified Associate Cloud Engineer Practice

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Prepare for the Google Cloud Certified Associate Cloud Engineer Exam with flashcards and multiple choice questions. Each question includes hints and explanations to help you study effectively. Get ready to pass your certification exam!

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If a Google Kubernetes Engine (GKE) cluster fails to schedule pods, what might be a contributing factor?

Insufficient CPU resources assigned to the GKE nodes.
Outdated Kubernetes version incompatible with pod configurations.
Cluster autoscaler not enabled to adjust resources dynamically.
Pods using deprecated API versions unsupported by the cluster.

The correct answer is: Insufficient CPU resources assigned to the GKE nodes.

Possible Explanation One potential reason for a GKE cluster failing to schedule pods could be an insufficient allocation of CPU resources to the cluster's nodes. If the nodes do not have enough CPU resources available, they may be unable to run all of the desired pods, causing failures in scheduling. While options B, C, and D may also cause issues with pod scheduling in certain circumstances, they are not directly related to CPU resource allocation and therefore are not as likely to be the primary contributing factor in this scenario. It is important to regularly monitor and adjust resource allocations in a GKE cluster to prevent issues like this from occurring.