LEARN. PRACTICE. GROW.Concept and mechanism
Application Insights supports performance and behavior analysis with platform-appropriate telemetry. For many code-instrumented server scenarios, current guidance uses Azure Monitor OpenTelemetry Distro. Do not assume the same configuration fits every runtime: the documented browser path uses Application Insights JavaScript SDK. Identify source, destination, and export mechanism. If the application responds but the dashboard is empty, check instrumentation, connection string, exporter, and ingestion-endpoint access. Missing events can indicate collection failure. SDK Stats helps observe exports, drops, and retries; observation-channel health is part of operational capability.
Guided application
In KQL, start with the question and fields actually available. To count recent failures in a fictional ReleaseEvents table, filter TimeGenerated and Status before count. If you project away the time field before filtering, you lose data required by the condition. If you aggregate first, the result no longer retains every event column. Use clear windows and denominators when comparing releases. Lower average latency after telemetry loss can reflect a different sample rather than better service. Correlate metrics with customer reports, available traces, and infrastructure signals. During a canary, do not progress solely because a dashboard is green if collection is degraded. Define who validates evidence and who decides to hold, expand, or reverse exposure.
ReleaseEvents | where TimeGenerated > ago(1h) | where Status == "Failed" | count is an example using a fictional schema, to adapt to actual logs.
Common pitfalls
Empty dashboard as healthy; universal OTel; filtering after losing columns; averages without completeness.
Related topics: Flow, traceability, and handover · Git, review, and recovery
Validate the observation channel before using its numbers for decisions.
Reference: Application Insights OpenTelemetry overview · AZ-400 objectives 2026-07-27