The process involves calculating the average usage for each resource, adding a 20% overhead, and selecting the smallest available specification that meets the new requirement.

• CPU: The average CPU usage is 16.57% of 4 vCPUs, which is 0.66 vCPUs. With a 20% overhead, the requirement is $0.66 \times 1.20 = 0.79$ vCPUs. The smallest option is 1 vCPU.
• RAM: Average RAM usage is 15% of 16GB, which is 2.4GB. With a 20% overhead, the requirement is $2.4\text{GB} \times 1.20 = 2.88\text{GB}$. The smallest option is 4GB.
• Disk: Average disk throughput is 4.43 MBps. With a 20% overhead, the requirement is $4.43 \times 1.20 \approx 5.32$ MBps. The smallest option is 10MBps.

Following the same right-sizing methodology as the web server:

• CPU: The average CPU usage is 65.57% of 4 vCPUs, which is 2.62 vCPUs. With a 20% overhead, the requirement is $2.62 \times 1.20 \approx 3.15$ vCPUs. The best-fit option is 4 vCPU.
• RAM: Average RAM usage is 80% of 16GB, which is 12.8GB. With a 20% overhead, the requirement is $12.8\text{GB} \times 1.20 = 15.36\text{GB}$. The smallest available option that meets this is 16GB.
• Disk: Average disk throughput is 86.71 MBps. With a 20% overhead, the requirement is $86.71 \times 1.20 \approx 104.05$ MBps. The next available tier is 110MBps.

AWS Well-Architected Framework, Cost Optimization Pillar (Whitepaper).

Reference: "Right Sizing" section under "Cost-effective resources."

Content: This official AWS document outlines the best practice of analyzing utilization metrics over time to select the instance type that meets performance requirements at the lowest cost. It explicitly advises against overprovisioning and recommends using monitoring data to make informed decisions, which is the core principle applied in this question.

Microsoft Azure Well-Architected Framework.

Reference: "Cost optimization" pillar, "Right-size resources" principle.

Content: Similar to AWS, this official Microsoft documentation emphasizes analyzing performance data such as CPU, memory, and IOPS to identify and deallocate underutilized resources. This directly supports the task of examining usage graphs to select smaller, more cost-effective server specifications.

Armbrust, M., et al. "A view of cloud computing." Communications of the ACM, vol. 53, no. 4, 2010, pp. 50-58.

Reference: Section 3, "Classes of Utility Computing," paragraph on pay-for-use models.

Content: This foundational academic paper discusses the economic benefits of cloud computing, including the ability to finely tune resource allocation to workload demands. The concept of right-sizing is a practical application of this principle, allowing users to avoid the costs of idle capacity inherent in statically provisioned on-premises environments.

DOI: https://doi.org/10.1145/1721654.1721672