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Reason through mitigation choices during a live App Service production incident.
Improve diagnosis when App Service log stream does not show enough information during an incident.
Diagnose a growing queue backlog in an Azure-based background processing system.
Investigate SQL timeouts that appear after a new .NET API release.
Investigate resource spikes on App Service after a new .NET API release.
Traces duplicate side effects across message delivery, lock ownership, settlement, durable job state, and external idempotency, then repairs affected users safely.
Diagnose missing trace continuity when an API enqueues work processed by an Azure worker.
Investigate a .NET API that appears to run but sends little or no telemetry to Application Insights.
Investigate messages that repeatedly fail and move to a poison queue or dead-letter queue.
Decide whether Azure SQL errors are transient platform faults or a real application/query regression.
Explains health endpoints, readiness versus liveness, warm-up, dependency checks, and safe App Service health behavior.
Covers deployment logs, startup failures, runtime stack, app settings, missing files, Key Vault references, and post-deployment diagnosis.
Explains correlation IDs, distributed tracing, dependency telemetry, message boundaries, and logs across App Service, queues, and downstream APIs.
Compares OpenTelemetry-based Azure Monitor instrumentation with older Application Insights SDK patterns for .NET services.
Covers useful request, dependency, exception, log, metric, and availability telemetry for a production .NET API.
Covers symptom-based alerting for latency, error rate, availability, dependency failures, queue length, and resource pressure.
Explains scale-out bugs from in-memory sessions, local caches, background queues, uploaded files, and per-instance behavior.