When dealing with VMware vSphere environments, one of the most common architectural decisions is determining the optimal vCPU-to-physical-core ratio. Your scenario with 24 vCPUs on dual Xeon E5-2699 v4 processors (22 cores each, HT enabled) presents several important considerations:

// Example PowerCLI snippet to check current CPU allocation
Get-VM | Select Name, NumCpu, Host, @{N="HostCores";E={$_.VMHost.ExtensionData.Hardware.CpuInfo.NumCpuPackages * 
$_.VMHost.ExtensionData.Hardware.CpuInfo.NumCpuCores}}

vSphere's CPU scheduler uses these key mechanisms:

• NUMA-aware scheduling (when possible)
• Hyperthread-based load balancing
• Co-scheduling constraints for SMP VMs

The scheduler will automatically distribute vCPUs across both physical CPUs and all available hyperthreads. A 24-vCPU VM on your 44-logical-core host (2x22 with HT) won't cause immediate issues, but may lead to:

# Potential performance counters to monitor
esxtop -b | awk '/^[0-9]/{print $1,$2,$3,$4,$5,$6,$7,$8,$9,$10,$11,$12}' | 
grep -i "%RDY|%MLMTD|%CSTP"

We tested three configurations:

Based on our testing:

1. For latency-sensitive workloads: Match vCPUs to physical cores (22 in your case)
2. For throughput-oriented VMs: You can oversubscribe but monitor %RDY
3. Consider NUMA boundaries when sizing large VMs

// PowerCLI to adjust vCPU count based on best practices
$vm = Get-VM "YourVMName"
$vm | Set-VM -NumCpu 22 -Confirm:$false

For critical workloads, these .vmx entries can help:

sched.cpu.latencySensitivity = "high"
sched.cpu.affinity = "all"
numa.autosize.cookie = "1"
numa.vcpu.maxPerVirtualNode = "11"

When configuring VMs in vSphere environments, one critical performance consideration is how virtual CPUs map to physical CPU resources. In your specific case with dual Xeon E5-2699 v4 processors (22 cores each, Hyper-Threading enabled) and a VM configured with 24 vCPUs, we need to examine several architectural factors.

ESXi uses a sophisticated CPU scheduler that:

• Treats each logical processor (physical core + HT thread) as a separate execution context
• Dynamically load-balances vCPUs across all available physical resources
• Respects NUMA boundaries when possible (more on this later)

With Hyper-Threading enabled, your 2x22-core processors present 88 logical processors to the hypervisor (2 sockets × 22 cores × 2 threads). The 24-vCPU VM will distribute across these resources.

Modern x86 servers use Non-Uniform Memory Access (NUMA) architecture where:

// Simplified NUMA node representation
struct numa_node {
    int id;
    cpu_set_t cpus;
    struct memory_region *local_memory;
    int latency_penalty; // Relative to remote access
};

Your dual-socket system has two NUMA nodes. vSphere's NUMA scheduler will attempt to keep vCPU and memory access within the same node, but with 24 vCPUs (exceeding a single socket's 22 cores), some memory access will inevitably cross NUMA boundaries.

For optimal performance in your scenario:

1. Right-size vCPU count: Consider reducing to 22 vCPUs (or fewer) unless the workload truly needs parallel execution capacity
2. Enable vNUMA: Add this to your VMX configuration:

   numa.vcpu.maxPerVirtualNode = 22
   forceNUMA = "TRUE"

3. Monitor CPU Ready: Use esxtop to identify scheduling contention:

   esxtop -b -n 1 -d 5 | grep "%RDY"

Benchmark results from similar configurations show:

The performance degradation at 24 vCPUs comes from cross-NUMA memory access penalties and increased scheduling overhead.

For latency-sensitive workloads, consider CPU affinity rules:

// Example PowerCLI script to set CPU affinity
$vm = Get-VM "YourVMName"
$spec = New-Object VMware.Vim.VirtualMachineConfigSpec
$spec.cpuAffinityAffinitySet = 0..21 # First NUMA node cores
$vm.ExtensionData.ReconfigVM_Task($spec)

Remember that affinity rules reduce the hypervisor's ability to load-balance and may hurt overall performance in many scenarios.