The Ultimate Guide to Right-Sizing CPU & Memory for Virtual Machines

In the world of virtualization, more CPU and memory doesn’t always mean better performance. Over-provisioning resources can lead to higher contention and even degraded application responsiveness.

Right-sizing ensures your workloads get exactly the resources they need—no more, no less—while maximizing efficiency on your ESXi hosts.

In this guide, we’ll explore practical CPU and memory sizing strategies, NUMA awareness, and performance optimization tips to help you make data-driven decisions.

Why Right-Sizing Matters

Every ESXi host has finite CPU and memory resources. If one VM hoards them unnecessarily, other VMs suffer. The goal of right-sizing is to:

• Improve overall cluster performance by reducing contention.

• Optimize hardware utilization.

• Avoid VM-level performance degradation caused by unnecessary over-allocation.

• Reduce software licensing costs for CPU-bound products like databases.

CPU Right-Sizing

When it comes to CPU allocation, more isn’t always better. Virtual CPUs (vCPUs) introduce scheduling overhead—allocating more than necessary can slow things down.

Best Practices

1. Start Small

   • Begin with the minimum number of vCPUs required for peak load.

   • Common starting point: 2 vCPUs for general-purpose workloads.

2. Add CPUs Only When Needed

   • Monitor for CPU Ready Time or Co-stop events.

   • If they are consistently high, then consider adding more vCPUs.

3. Align with NUMA Topology

   • Configure vCPUs as Cores per Socket until:

     • You exceed the physical core count of a NUMA node, or

     • You exceed the memory available in a NUMA node.

4. Avoid Odd vCPU Counts

   • Maintain even counts for better scheduling efficiency.

5. Disable vCPU Hot Add Unless Necessary

   • Enabling hot add disables vNUMA—critical for workloads over 8 vCPUs.

6. Mind Licensing Models

   • some software licensing schemes had limitations on socket counts, configuring the socket count to 1 may result in better performance

     • For example, SQL Server Standard edition running on an 8-vCPU VM with 1 core per socket would be able to utilize only 4 vCPUs. But if the same VM were configured with 1 socket (that is, 8 cores per socket), then all 8 vCPUs would be leveraged.

Understanding NUMA & vNUMA

Modern servers use NUMA (Non-Uniform Memory Access), where CPU and memory are grouped into nodes. Accessing memory within the same node is faster (local memory) than accessing from another (remote memory).

• Let’s understand with an example. Lets assume:

  • Each physical server has 2 CPU sockets.

  • Each socket contains 24 physical cores.

  • This means one NUMA node = 1 socket = 24 cores + its own memory bank.

If you create a VM with up to 24 vCPUs, you can assign them as 1 socket × 24 cores.

• This keeps all vCPUs within the same NUMA node, so memory access stays local and fast.

If you create a VM with more than 24 vCPUs (say 32 vCPUs):

• The vCPUs will be split across two NUMA nodes (because a single node can’t handle more than 24).

• This means some CPU threads may need to access memory from the other node, which is slower.

• At that point, you should configure vNUMA so the VM and its OS are aware of this split.

NUMA Tips

• Keep vCPUs and memory allocations within a single NUMA node when possible.

• vNUMA becomes relevant when a VM’s vCPUs exceed a single NUMA node’s core count (often >8 vCPUs).

• vNUMA exposes NUMA topology to the guest OS so it can optimize memory locality.

Memory Right-Sizing

Just like CPU, over-allocating RAM can harm performance due to ballooning and swapping.

Best Practices

1. Start with the Working Set

   • Measure actual memory use and allocate slightly above it.

   • Example: If a VM uses 8 GB, allocate ~10 GB.

2. Avoid Large Headroom

   • Unused RAM may be reclaimed by ballooning, which can cause performance drops.

3. When Ballooning Occurs

   • Check if the VM is swapping/paging.

   • Right-size VMs with over-allocated RAM to free resources for others.

Final Thoughts

Right-sizing isn’t about giving VMs the most resources—it’s about giving them the right amount. By starting small, monitoring real usage, and scaling based on evidence, it will lead to boosting performance & reduce resource contention.

Awareness of physical topology and NUMA limits is also key to making the most of your hardware.