Best Practices

The following best practices can help optimize scan throughput and capacity planning results.

• Create multiple scan jobs to improve parallelism.

  A scanner processes one slice from each scan job concurrently; increasing the number of scan jobs can improve throughput without requiring additional scanners.

• Use scanners with identical hardware specifications whenever possible.

  Mixed scanner configurations can reduce overall pool performance because workload distribution is limited by the least-capable scanner.

• Keep Your Scanner Pool Uniformly Sized

  All scanners in a pool should have the same vCPUs, RAM, and configuration (virtual or physical). Mixed-spec pools create:

  • Uneven capacity distribution
  • Wasted scan slots
  • Unpredictable scan times — the weakest scanner becomes the bottleneck

• Avoid a Single Oversized Job

  A single oversized job forces all slices into a single queue. Instead, create multiple medium-to-large jobs sized to match your scanner count. Each scanner handles one slice per job at a time, so more jobs = more parallel throughput.

• Right-Size Your Scanners

  • CPU is usually the bottleneck. Ensure adequate vCPUs and CPU speed.
  • Follow the 1 vCPU : 2–3 GB RAM ratio (maximum 1:4).
  • For large enterprise environments or sustained high load, consider 16 vCPUs / 32 GB RAM.
  • Provision at least 100 GB of disk space for large or frequent scans.

• Match Option Profile Settings

  Ensure the values you enter for Parallel Host Scans (P) and Parallel ML Scaling match what is actually configured in your Option Profile in the Qualys platform. Mismatched values produce inaccurate estimates.