Ace the VMware VCP-DCV Challenge 2025 – Virtualization Mastery Awaits!

In a virtual machine environment, properly balancing Non-Uniform Memory Access (NUMA) nodes is crucial for optimizing performance. Each NUMA node has its own processors and memory, which allows for faster memory access within the same node. When NUMA nodes are not balanced correctly, it can lead to performance degradation in virtual machines.

This occurs because when a virtual machine is scheduled on a particular NUMA node, it benefits most from the local memory associated with that node. If a virtual machine straddles multiple NUMA nodes or does not have a proper allocation of virtual CPUs and memory across nodes, it may face higher memory access latency and increased contention for memory resources. As a result, workloads that require high memory bandwidth or low latency in memory access can significantly suffer, leading to slower application performance and inefficiency.

The other options, while they might seem relevant, do not directly relate to the consequences of improper NUMA balancing. Issues like virtual machine compatibility and network latency are influenced by different factors, while energy consumption may increase due to inefficient CPU utilization rather than being a direct consequence of NUMA imbalance. Thus, the most direct and significant impact of improper NUMA balancing is indeed the performance degradation in virtual machines.