Source: Varonis Blog
Author: Amanda Wicks
URL: https://www.varonis.com/blog/data-scanning-performance
https://www.varonis.com/blog/data-scanning-performance
ONE SENTENCE SUMMARY:
Varonis optimizes data security scanning via scalable scan units, throttling awareness, in-place collectors, DDC, Smart Scan, and automated remediation.
MAIN POINTS:
- Cloud-provider API rate limits commonly become the primary constraint on scan speed.
- Scan units map to compute resources, enabling predictable linear throughput scaling when not throttled.
- Recommended sizing approach starts small, then adds scan units only if needed.
- Varonis handles capacity planning automatically, removing customer infrastructure calculations.
- Google Workspace and similar services require multiple API calls per file, accelerating throttling.
- Throttling visibility inside the product prevents wasted scaling that cannot improve scan duration.
- Cloud-to-cloud scanning can introduce WAN bandwidth bottlenecks, egress charges, and privacy concerns.
- Private collectors scan data in-place, returning only metadata to avoid egress and exposure.
- Dynamic Data Concentration reduces redundant reads on repetitive datasets without statistical sampling.
- Smart Scan prioritizes high-risk data first, enabling remediation before full scan completion.
TAKEAWAYS:
- Optimize for fastest risk reduction, not merely fastest scan completion.
- Monitor API throttling before adding compute, since extra units may not increase throughput.
- Prefer in-environment collectors when data residency, cost, and bandwidth constraints matter.
- Combine DDC with Smart Scan to accelerate both overall scanning and early high-risk findings.
- Rely on policy-driven automated remediation to eliminate millions of exposures at scale quickly.