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

Bias Types:
⚠️ missing_linux_example
⚠️ windows_first
⚠️ windows_tools
Summary:
The documentation page demonstrates a strong Windows bias. All workload examples, supported platforms, and backup scenarios are focused on Windows operating systems and Microsoft workloads (Windows Server, SQL Server, Exchange, SharePoint, Hyper-V). Linux is only mentioned as a guest OS in Hyper-V or VMware, with no details on native Linux backup, file-level recovery, or parity of features. Windows-specific tools and technologies (NTFS, VSS, ReFS, Windows Management Framework, NTLM authentication) are referenced throughout, and there are no Linux-specific instructions, requirements, or examples. The matrix and narrative consistently list Windows scenarios first or exclusively.
Recommendations:
  • Add explicit support matrix rows for native Linux workloads (not just as VMs), including supported distributions, file systems, and backup/recovery capabilities.
  • Provide Linux-specific requirements, limitations, and supported features (e.g., file-level backup, application-aware backup, snapshot mechanisms like LVM or filesystem freeze).
  • Include Linux examples and scenarios alongside Windows ones, ensuring parity in documentation structure and detail.
  • Reference Linux tools and patterns (e.g., ext4, XFS, LVM, rsync, SSH-based authentication) where relevant.
  • Clarify any feature gaps or differences between Windows and Linux support, and provide guidance or workarounds for Linux users.
  • Avoid listing only Windows-specific technologies (NTFS, VSS, ReFS) without mentioning Linux equivalents or alternatives.
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Scan History

Date Scan ID Status Bias Status
2025-08-17 00:01 #83 in_progress ✅ Clean
2025-07-14 17:05 #49 completed ❌ Biased
2025-07-13 21:37 #48 completed ✅ Clean
2025-07-09 13:09 #3 cancelled ✅ Clean
2025-07-08 04:23 #2 cancelled ❌ Biased