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Clarify the common misconception that await starts work on a new thread, and explain what actually happens for I/O-bound operations.
Sets concurrency from the constrained resource and verifies throughput, latency, and downstream safety instead of maximizing active work.
Decide how to handle CPU-heavy work in an API without damaging request throughput or making the system unreliable.
Investigate a production API slowdown caused by blocking async calls, thread-pool pressure, and dependency waits.
Proves parallel speedup against a sequential baseline while accounting for overhead, saturation, tail latency, resource contention, and downstream impact.
Chooses a parallel API based on whether the workload is a data query or an imperative loop and keeps CPU work pure, bounded, and measurable.
Combines ThreadPool counters, repeated stack snapshots, and wait-event traces to distinguish blocked workers from CPU or dependency pressure.
Investigate deadlocks or starvation caused by blocking on async code with Result, Wait, or GetAwaiter().GetResult().
Explain when Task.Run is useful, when async/await is enough, and why Task.Run is usually wrong for I/O in ASP.NET Core.
Compare Task and Thread in .NET, including abstraction level, scheduling, and when direct thread management is rarely appropriate.
Diagnose thread-pool starvation caused by blocking work, unbounded concurrency, or sync-over-async in .NET APIs.
Separates memory visibility and ordering from atomic multi-step updates, avoiding volatile as a substitute for real synchronization.