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Investigate production HTTP 500 errors that start immediately after a deployment slot swap.
Diagnose missing trace continuity when an API enqueues work processed by an Azure worker.
Diagnose a .NET API that cannot connect to Azure SQL using managed identity.
Investigate a .NET API that appears to run but sends little or no telemetry to Application Insights.
Explains how to troubleshoot absent logs or telemetry by checking configuration, sampling, sinks, levels, deployment, and correlation.
Investigate messages that repeatedly fail and move to a poison queue or dead-letter queue.
Explains a constraint-first approach to responsive layout, intrinsic sizing, overflow, and content resilience.
Introduces API versions only for unavoidable breaks, with explicit routing, versioned documentation, migration support, telemetry, deprecation, and removal criteria.
Builds a risk-based frontend test strategy across unit, component, integration, contract, and end-to-end boundaries.
Explains soft delete in EF Core APIs with practical .NET data-access examples and production trade-offs.
Places contract, use-case, domain, authorization, and database validation at the boundaries that can enforce each rule consistently.
Design list endpoints with pagination, filtering, sorting, limits, and database-aware performance behavior.
Uses read replicas selectively while accounting for stale reads, read-after-write behavior, routing, failover, query cost, and replication health.
Design request DTOs that protect API contracts from domain and persistence models.
Uses unique namespaces and correctly scoped fixtures so parallel tests improve speed without creating collisions.
Treats flakiness as an observable defect in timing, state, order, infrastructure, or product behavior.
Diagnoses hidden per-row EF Core queries and replaces them with a bounded query shape without creating an oversized join.
Explains a telemetry-driven path from slow endpoint symptoms to database, cache, dependency, CPU, or payload root cause.
Decide whether Azure SQL errors are transient platform faults or a real application/query regression.
Treats JSON serialization settings and DTO shape as a public contract, including naming, enums, nulls, converters, compatibility, and tests.
Frames a vague system-design problem with explicit flows, constraints, scale estimates, and measurable quality targets before selecting components.
Explain how a .NET BackgroundService should handle cancellation, in-flight work, and application shutdown.
Explains initial incident triage: confirm impact, mitigate, assign roles, preserve evidence, and communicate.
Shows how publisher-to-subscriber references can retain objects and how to clean up event-based lifetimes.