The Ideal Feature for Provisioning VMs with Varying Load | CompTIA Cloud+ CV0-002
Question
A cloud administrator is provisioning five VMs, each with a minimum of 8GB of RAM and a varying load throughout the day.
The hypervisor has only 32GB of RAM.
Which of the following features should the administrator use?
Answers
Explanations
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A. B. C. D.C.
In this scenario, the cloud administrator is trying to provision five virtual machines (VMs) with a minimum of 8GB RAM each, but the hypervisor only has 32GB RAM available. To manage this resource constraint, the administrator must utilize a feature that optimizes the usage of available resources. Let's take a closer look at each of the answer options:
A. Memory overcommitment: This is a feature of virtualization that allows the hypervisor to allocate more memory to VMs than is physically available on the host. This is done by assuming that not all VMs will use their full allocation of memory at the same time. This can be a useful feature in situations where VMs have varying workloads, as in this scenario. However, overcommitting memory can cause performance issues if VMs are unable to access their full allocation of memory when they need it.
B. Thin-provisioned model: This is a storage optimization technique that allows administrators to allocate storage capacity to VMs on an as-needed basis. This means that VMs are only given as much storage as they currently need, rather than being allocated their entire capacity upfront. This feature can help optimize storage usage and reduce costs, but it does not address the issue of limited memory.
C. Process scheduling: This is a feature of the operating system that manages the allocation of processing resources to different processes and applications. While this feature can help optimize performance within individual VMs, it does not address the issue of limited memory.
D. Hyperthreading: This is a technology that allows a single CPU core to execute multiple threads simultaneously. This can improve CPU utilization and performance, but it does not address the issue of limited memory.
Given the scenario described, the best answer is A. Memory overcommitment. This feature allows the hypervisor to allocate memory to VMs dynamically based on their actual usage, rather than allocating a fixed amount of memory upfront. This can help optimize the usage of available resources, while still ensuring that each VM has enough memory to meet its minimum requirements. However, it is important to monitor VM performance closely to ensure that overcommitting memory does not cause performance issues.
