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  4. Choosing a CPU for CI/CD, virtualisation and Kubernetes nodes

Choosing a CPU for CI/CD, virtualisation and Kubernetes nodes

Applies to Bare Metal Compute, Dedicated Servers, ComputeAudience Technical evaluatorLast reviewed September 2026

Quick answer

Match core count and clock speed to what the workload actually bottlenecks on: CI/CD build nodes want high single-thread performance and enough cores to run parallel jobs, virtualisation and Kubernetes nodes want core count and consistent per-core performance over raw clock speed, since resources get sliced across many tenants or pods.

Sizing by workload type

WorkloadWhat matters mostWhy
CI/CD, build nodesHigh single-thread performance, enough cores for parallel jobsCompilers and test suites are often single-threaded per job; running several jobs at once needs enough cores to avoid queueing
Virtualisation (Proxmox, VMware)Core count, consistent per-core performanceEach VM gets a slice of CPU; more cores means more VMs without contention, and consistency matters more than peak clock speed
Kubernetes worker nodesCore count, headroom above committed pod requestsKubernetes schedules pods against requested CPU, not actual usage; undersized nodes lead to throttling under load
Databases, high-IO servicesFast single-core performance, paired with NVMe storageMany database engines are still largely single-threaded per query; storage speed matters as much as CPU here, see Choosing storage media

Sizing for mixed workloads

When one machine runs a mix (say, a handful of VMs plus a build pipeline), start from the busiest individual workload's requirement, then add headroom for the others rather than averaging everything together. A useful starting point: sum the vCPUs you plan to allocate to VMs or pods, add margin for the hypervisor or control-plane overhead itself, and size storage IOPS to the workload with the highest I/O demand, not the average.

Troubleshooting: high load, but the CPU looks idle

If your application feels slow but CPU usage graphs show plenty of idle capacity, look at CPU steal time before assuming the application itself is the problem. Steal time is the percentage of time a virtual CPU is ready to run but waiting for the physical host to schedule it, common on shared virtualised infrastructure under contention.

  • On Linux, check steal time with mpstat -P ALL 1 (the %steal column) or sar -u 1.
  • Correlate with application-level p95/p99 latency, not just averages: steal time tends to show up as occasional latency spikes rather than a steady slowdown.
  • If steal time is consistently high, the fix is usually more dedicated resources (a larger VPS tier, or a dedicated/Bare Metal Compute server) rather than tuning the application further.

Related articles

  • Bare Metal Compute vs. Dedicated Servers
  • Sizing a Kubernetes cluster for high availability
  • Choosing storage media: NVMe vs. SSD vs. HDD by workload
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