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Answer: Examine the resource needs and usage trends of the Compute Engine instances, then acquire suitable committed use contracts for vCPUs and memory, and implement autoscaling with custom metrics that align with each instance's requirements and usage patterns.
**Correct Answer: D** - **D** is correct because it involves a detailed analysis of each instance's resource requirements and usage patterns, leading to the purchase of committed use contracts that precisely match these needs. Additionally, setting up autoscaling based on custom metrics ensures resources are optimally utilized, balancing performance and cost. - **A** is incorrect because Preemptible VMs, while cost-effective, are not suitable for all workloads due to their interruptible nature, potentially causing service disruptions. - **B** is incorrect as allocating minimal resources without considering actual needs can degrade performance, and autoscaling based solely on uptime does not guarantee efficient resource utilization or cost savings. - **C** is incorrect because purchasing maximum resources without regard to actual usage leads to over-provisioning, increasing costs unnecessarily.
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As a DevOps Engineer, your goal is to optimize resource utilization and leverage committed use discounts effectively in a Google Cloud Platform (GCP) project. The project includes multiple Compute Engine instances with diverse resource needs and usage behaviors. What strategy should you adopt to meet these optimization and cost-saving objectives?
A
Migrate all Compute Engine instances to Preemptible VMs after analyzing their resource requirements and usage patterns to cut costs.
B
Allocate the least possible vCPUs and memory for all Compute Engine instances and set up autoscaling based on instance uptime to reduce expenses.
C
Buy committed use contracts for the highest possible vCPUs and memory for every Compute Engine instance, ignoring their specific needs and usage patterns, to ensure the greatest cost efficiency.
D
Examine the resource needs and usage trends of the Compute Engine instances, then acquire suitable committed use contracts for vCPUs and memory, and implement autoscaling with custom metrics that align with each instance's requirements and usage patterns.
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