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
windows_tools
missing_linux_example
Summary
The documentation page demonstrates a Windows-centric bias by consistently referencing Windows authentication technologies (Active Directory Domain Services, Kerberos, DACLs) and patterns first, with only brief mention of Linux support. Windows tools and terminology are used throughout, and there are no Linux-specific examples or guidance. The only reference to Linux is a parenthetical link, with no parity in explanation or workflow details.
Recommendations
  • Add explicit Linux client examples and workflows for identity-based authentication with Azure Files over SMB, including step-by-step instructions and troubleshooting tips.
  • Include Linux tools and commands (e.g., mount.cifs, Kerberos configuration on Linux, relevant package requirements) alongside or before Windows equivalents where appropriate.
  • Balance terminology and explanations by referencing both Windows and Linux authentication mechanisms, and clarify any differences or limitations.
  • Provide links to Linux-focused documentation in the main body, not just as a parenthetical note.
  • Where diagrams or workflows are shown, include Linux client scenarios and architecture.
  • Ensure glossary entries and references are not exclusively Windows-focused (e.g., mention Linux Kerberos implementations, Samba, etc.).
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Scan History

Date Scan Status Result
2026-01-14 00:00 #250 in_progress Clean Clean
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 Clean Clean
2025-08-19 00:01 #85 completed Clean Clean
2025-07-13 21:37 #48 completed Biased Biased
2025-07-12 23:44 #41 cancelled Biased Biased