Cutter 16
- vCPU
- 6 × dedicated
- RAM
- 16 GB
- Storage
- 320 GB NVMe SSD
- Transfer
- 15 TB
- IPv4 / IPv6
- 1 / /64 routed
Solution
SEO tooling is memory-bound and IP-sensitive. Screaming Frog crawling 500,000 URLs wants 16 GB; a rank tracker wants several IPv4 addresses far more than it wants cores. Four dedicated cores, 16 GB and a handful of extra addresses is the configuration that actually works, and location diversity lets you check rankings as a local user would see them.
| Resource | What you actually need |
|---|---|
| CPU | 4 dedicated cores |
| RAM | 16 GB for large crawls; Screaming Frog is memory-hungry |
| Disk | 320 GB NVMe for crawl databases |
| IPs | Several IPv4 addresses for rotation |
Location is usually the decision that matters most for this workload — either because latency dominates, or because jurisdiction does.
Memory is what limits crawl size in practice.
Bind each worker to a distinct source address.
Screaming Frog and Sitebulb both have headless modes.
A Skiff 1 per country gives real localised checks.
Crawl databases grow fast; archive to a Hold instance.
Roughly 4 GB per 100,000 URLs in memory mode. Database storage mode trades speed for a much lower memory ceiling and is what you want past about 200,000 URLs.
Yes. Deploy a small instance in each target country and query from there — that is the only way to see genuinely localised results.
Yes, for lawfully accessible public data at rates that do not degrade the target.