Metrics Library

Title: Enhancement: Report Detailed AD Sync Errors (Entra Connect) from Local Server Category: Inspector Enhancement (Active Directory or Windows Server) What is your feedback? Why is it important to you? Currently, Liongard reports on the service status of the AD Sync (Microsoft Entra Connect) service (i.e., is the service "Running" or "Stopped"), but it does not capture the content of synchronization errors. We frequently encounter scenarios where the sync service is technically "Running" (so no alert is triggered), but objects are failing to sync due to specific errors like AttributeValueMustBeUnique, InvalidSoftMatch, or LargeObject. These errors are critical because they result in users not being created in M365, password changes failing to sync, or group membership discrepancies. Without this data in Liongard, our team has to manually remote into the AD Connect server to check the "Synchronization Service Manager" UI or Event Viewer for every ticket, which defeats the purpose of centralized visibility. What is your ideal solution? I would like the Active Directory Inspector (or the Windows Inspector) to have the ability to query the local AD Connect instance (typically leveraging the MIIS_Server WMI class or parsing the Application Event Log for Source ADSync) to report: Error Count: The number of objects with sync errors. Error Details: A table listing the specific error type (e.g., sync-generic-failure) and the DN (Distinguished Name) of the impacted object. Last Successful Sync Time: The timestamp of the last fully successful export to Azure AD, not just the last time the scheduler ran. Business Impact: This would allow us to create Actionable Alerts for "AD Sync contains Errors," enabling proactive remediation of identity issues before end-users report login failures or missing account data.

This is helpful to someone who's trying to complete an audit of 2025 Windows Servers in an organization. This is a good Metric for a cross customer audit, and could be included in QBRs, recurring site reviews, or an onboarding report. Computers[?OperatingSystem != null && contains(OperatingSystem, 'Windows Server 2025')] | length(@)

This is helpful to someone who's trying to complete an audit of 2022 Windows Servers in an organization. This is a good Metric for a cross customer audit, and could be included in QBRs, recurring site reviews, or an onboarding report. Computers[?OperatingSystem != null && contains(OperatingSystem, 'Windows Server 2022')] | length(@)

This will return us the last logon for the AD user. Users[].join( , [join( , [ AD LOGIN: , to_string(UserName)]), join( , [ . Name of User: , to_string(Name)]),join( , [ : , to_string(LastLogonDate)])])

This is helpful to someone who's trying to obtain/maintain visibility into the count of enabled workstations at an organization. This is a good Metric for QBRs or recurring site reviews. Computers[?Type== Workstation && Enabled == true ] | length(@)

This is helpful to someone who's trying to obtain/maintain visibility into the count of enabled servers at an organization. This is a good Metric for QBRs or recurring site reviews. Computers[?Type== Server && Enabled == true ] | length(@)

This is helpful to someone who's trying to complete an audit of Windows 7 computers in an organization, as they are out of support. This is a good Metric for a cross customer audit, and could be included in QBRs, recurring site reviews, or an onboarding report. This Metric also could be used to create an Actionable Alert for computers that are out of support. Computers[? contains(to_string(OperatingSystem), Windows 7 )]. Name | length(@)

This is helpful to someone who's trying to obtain/maintain visibility into the count of OUs at an organization. This is a good Metric for QBRs or recurring site reviews. OrganizationalUnits | length(@)

This is helpful to someone who's trying to obtain/maintain visibility into a count of stale/inactive users at an organization. This is a good Metric for QBRs or recurring site reviews. Also, this Metric could be used to build a user audit with the intention of an end customer confirming that all looks as expected. Users[? DaysSinceLastLogin < 31 && UserStatus == Active && DaysSinceLastLogin != null && Email != null ] | length(@)

This is helpful to someone who's trying to obtain/maintain visibility into the count of groups at an organization. This is a good Metric for QBRs or recurring site reviews. Groups[] | length(@)