Sad Tux - Windows bias detected
This page contains Windows bias

About This Page

This page is part of the Azure documentation. It contains code examples and configuration instructions for working with Azure services.

Bias Analysis

Detected Bias Types
windows_first
missing_linux_example
windows_tools
Summary
The documentation page demonstrates a Windows bias primarily in the 'Use data collection rules for your Windows Security Events' section, which exclusively discusses Windows Server and the Windows Security Events connector. There are no equivalent examples or guidance for collecting security events from Linux systems, nor are Linux-specific connectors or data collection rules mentioned. The focus on Windows tools and lack of Linux parity may leave Linux administrators without clear guidance for cost optimization.
Recommendations
  • Add a section or examples for collecting and optimizing security event ingestion from Linux servers, including relevant connectors (e.g., Syslog, CEF) and data collection rules.
  • Mention Linux data sources and how to use data collection rules or agents (such as the Azure Monitor Agent on Linux) to filter and optimize log ingestion.
  • Ensure that references to connectors and data collection are platform-neutral where possible, or provide parallel guidance for both Windows and Linux environments.
  • Review the documentation for other areas where only Windows-centric tools or workflows are described, and add Linux equivalents or cross-platform instructions.
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Scan History

Date Scan Status Result
2026-01-14 00:00 #250 in_progress Biased Biased
2026-01-13 00:00 #246 completed Biased Biased
2026-01-11 00:00 #240 completed Biased Biased
2026-01-10 00:00 #237 completed Biased Biased
2026-01-09 00:34 #234 completed Biased Biased
2026-01-08 00:53 #231 completed Biased Biased
2026-01-06 18:15 #225 cancelled Clean Clean
2025-08-29 00:01 #95 completed Clean Clean
2025-07-23 00:00 #58 completed Clean Clean
2025-07-13 21:37 #48 completed Biased Biased
2025-07-12 23:44 #41 cancelled Biased Biased