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This correction is for the separate condition: A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces. It would not directly restore the intended behavior in this situation: A support team wants error and latency signals from an on-premises Business Central instance into Azure Monitor. Here, correct the environment application insights connection settings and ingestion access then verify signals, because environment-level telemetry sends service operation events to azure application insights for monitoring and troubleshooting.

This correction is for the separate condition: An invoice approval extension needs explicit business-level counters beyond generic page-open telemetry. It would not directly restore the intended behavior in this situation: A support team wants error and latency signals from an on-premises Business Central instance into Azure Monitor. Here, correct the environment application insights connection settings and ingestion access then verify signals, because environment-level telemetry sends service operation events to azure application insights for monitoring and troubleshooting.

This correction is for the separate condition: A regional operations team needs to compare latency for two app versions using structured telemetry fields. It would not directly restore the intended behavior in this situation: A support team wants error and latency signals from an on-premises Business Central instance into Azure Monitor. Here, correct the environment application insights connection settings and ingestion access then verify signals, because environment-level telemetry sends service operation events to azure application insights for monitoring and troubleshooting.

This choice primarily fits a different requirement: A custom discount capability needs a measurable signal when users discover, activate and successfully use it. There, custom feature telemetry records application-specific behavior that generic infrastructure events may not reveal. In the current situation, A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events. Application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. Acceptance requires publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

This choice primarily fits a different requirement: A support engineer sees frequent exception events but cannot isolate whether they came from the latest extension deployment. There, structured telemetry dimensions let investigators narrow events to a deployment and correlate performance or errors. In the current situation, A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events. Application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. Acceptance requires publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

This choice primarily fits a different requirement: A large extension's posting route is slow but the team optimizes UI rendering without evidence of the bottleneck. There, performance work should target observed long-running calls rather than speculative components. In the current situation, A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events. Application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. Acceptance requires publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

That mechanism explains why the alternative action—emit purposeful custom feature telemetry such as usage, uptake and error signals—helps in another case. It does not justify the proposed fix here; application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. The distinguishing requirement is: A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events.

That mechanism explains why the alternative action—analyze application insights traces using kql filters for environment, app id, version and time—helps in another case. It does not justify the proposed fix here; application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. The distinguishing requirement is: A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events.

That mechanism explains why the alternative action—use timing and performance telemetry to locate the measured slow operation before optimizing—helps in another case. It does not justify the proposed fix here; application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. The distinguishing requirement is: A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events.

This would verify emit purposeful custom feature telemetry such as usage, uptake and error signals, which addresses a different engineering need. It does not demonstrate that the current issue is resolved: A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events. The decisive local proof is publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

This would verify analyze application insights traces using kql filters for environment, app id, version and time, which addresses a different engineering need. It does not demonstrate that the current issue is resolved: A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events. The decisive local proof is publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

This would verify use timing and performance telemetry to locate the measured slow operation before optimizing, which addresses a different engineering need. It does not demonstrate that the current issue is resolved: A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events. The decisive local proof is publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

This correction is for the separate condition: An invoice approval extension needs explicit business-level counters beyond generic page-open telemetry. It would not directly restore the intended behavior in this situation: A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events. Here, correct the app manifest telemetry configuration and verify emitted events carry the right app identity, because application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry.

This correction is for the separate condition: A regional operations team needs to compare latency for two app versions using structured telemetry fields. It would not directly restore the intended behavior in this situation: A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events. Here, correct the app manifest telemetry configuration and verify emitted events carry the right app identity, because application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry.

This correction is for the separate condition: A warehouse application sometimes times out and engineers guess which database operation is expensive. It would not directly restore the intended behavior in this situation: A marketplace app publisher wants platform-emitted runtime errors and app lifecycle telemetry from only its extension across customer tenants, without adding new feature-specific events. Here, correct the app manifest telemetry configuration and verify emitted events carry the right app identity, because application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry.

This choice primarily fits a different requirement: A custom discount capability needs a measurable signal when users discover, activate and successfully use it. There, custom feature telemetry records application-specific behavior that generic infrastructure events may not reveal. In the current situation, A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces. Application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. Acceptance requires publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

This choice primarily fits a different requirement: A support engineer sees frequent exception events but cannot isolate whether they came from the latest extension deployment. There, structured telemetry dimensions let investigators narrow events to a deployment and correlate performance or errors. In the current situation, A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces. Application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. Acceptance requires publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

This choice primarily fits a different requirement: A large extension's posting route is slow but the team optimizes UI rendering without evidence of the bottleneck. There, performance work should target observed long-running calls rather than speculative components. In the current situation, A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces. Application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. Acceptance requires publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

That mechanism explains why the alternative action—emit purposeful custom feature telemetry such as usage, uptake and error signals—helps in another case. It does not justify the proposed fix here; application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. The distinguishing requirement is: A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces.

That mechanism explains why the alternative action—analyze application insights traces using kql filters for environment, app id, version and time—helps in another case. It does not justify the proposed fix here; application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. The distinguishing requirement is: A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces.

That mechanism explains why the alternative action—use timing and performance telemetry to locate the measured slow operation before optimizing—helps in another case. It does not justify the proposed fix here; application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry. The distinguishing requirement is: A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces.

This would verify emit purposeful custom feature telemetry such as usage, uptake and error signals, which addresses a different engineering need. It does not demonstrate that the current issue is resolved: A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces. The decisive local proof is publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

This would verify analyze application insights traces using kql filters for environment, app id, version and time, which addresses a different engineering need. It does not demonstrate that the current issue is resolved: A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces. The decisive local proof is publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

This would verify use timing and performance telemetry to locate the measured slow operation before optimizing, which addresses a different engineering need. It does not demonstrate that the current issue is resolved: A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces. The decisive local proof is publisher diagnostics show extension-specific operations and failures attributed to the expected app id.

This correction is for the separate condition: An invoice approval extension needs explicit business-level counters beyond generic page-open telemetry. It would not directly restore the intended behavior in this situation: A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces. Here, correct the app manifest telemetry configuration and verify emitted events carry the right app identity, because application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry.

This correction is for the separate condition: A regional operations team needs to compare latency for two app versions using structured telemetry fields. It would not directly restore the intended behavior in this situation: A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces. Here, correct the app manifest telemetry configuration and verify emitted events carry the right app identity, because application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry.

This correction is for the separate condition: A warehouse application sometimes times out and engineers guess which database operation is expensive. It would not directly restore the intended behavior in this situation: A partner needs platform-generated diagnostics for only one extension across tenants, rather than new manual feature telemetry or whole-environment traces. Here, correct the app manifest telemetry configuration and verify emitted events carry the right app identity, because application-level telemetry can emit extension-related events to an app publisher's resource separately from general environment telemetry.

This choice primarily fits a different requirement: A support engineer sees frequent exception events but cannot isolate whether they came from the latest extension deployment. There, structured telemetry dimensions let investigators narrow events to a deployment and correlate performance or errors. In the current situation, A custom discount capability needs a measurable signal when users discover, activate and successfully use it. Custom feature telemetry records application-specific behavior that generic infrastructure events may not reveal. Acceptance requires sample business actions produce identifiable feature events with useful non-sensitive dimensions.

This choice primarily fits a different requirement: A large extension's posting route is slow but the team optimizes UI rendering without evidence of the bottleneck. There, performance work should target observed long-running calls rather than speculative components. In the current situation, A custom discount capability needs a measurable signal when users discover, activate and successfully use it. Custom feature telemetry records application-specific behavior that generic infrastructure events may not reveal. Acceptance requires sample business actions produce identifiable feature events with useful non-sensitive dimensions.

This choice primarily fits a different requirement: An administrator needs diagnostic telemetry from a Business Central online production environment that currently has no Application Insights connection. There, environment-level telemetry sends service operation events to azure application insights for monitoring and troubleshooting. In the current situation, A custom discount capability needs a measurable signal when users discover, activate and successfully use it. Custom feature telemetry records application-specific behavior that generic infrastructure events may not reveal. Acceptance requires sample business actions produce identifiable feature events with useful non-sensitive dimensions.

That mechanism explains why the alternative action—analyze application insights traces using kql filters for environment, app id, version and time—helps in another case. It does not justify the proposed fix here; custom feature telemetry records application-specific behavior that generic infrastructure events may not reveal. The distinguishing requirement is: A custom discount capability needs a measurable signal when users discover, activate and successfully use it.

That mechanism explains why the alternative action—use timing and performance telemetry to locate the measured slow operation before optimizing—helps in another case. It does not justify the proposed fix here; custom feature telemetry records application-specific behavior that generic infrastructure events may not reveal. The distinguishing requirement is: A custom discount capability needs a measurable signal when users discover, activate and successfully use it.

That mechanism explains why the alternative action—enable and verify environment-level telemetry to the intended application insights resource—helps in another case. It does not justify the proposed fix here; custom feature telemetry records application-specific behavior that generic infrastructure events may not reveal. The distinguishing requirement is: A custom discount capability needs a measurable signal when users discover, activate and successfully use it.