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Builds a story about turning unclear requirements into a scoped, testable plan without overbuilding.
Separates process start from readiness, coordinates hosted-service startup, and drains work within a bounded shutdown window.
Handles an urgent production fix from verified impact and deployed provenance through minimal code, focused validation, controlled rollout, rollback readiness, and merge-forward.
Connects EF Core change tracking to object retention, query shape, projections, and read-only API performance.
Focuses on ToList chains, collection capacity, repeated enumeration, and memory-aware data shaping.
Explains staging slots, validation before swap, warm-up, traffic continuity, and safer production releases for App Service APIs.
Explains controller actions, result types, status codes, thin controllers, and HTTP response generation.
Explains transient, scoped, and singleton lifetimes in ASP.NET Core APIs and production bugs caused by wrong lifetime choices.
Explains how App Service plans provide compute capacity, how scale-out affects app instances, and why APIs need stateless design.
Explains endpoint routing, route templates, HTTP method matching, endpoint metadata, and ambiguity problems.
Explains when to capture dumps, what to compare, and how to use roots without turning dumps into guesswork.
Explains a practical approach to diagnosing failed builds, tests, package restore, environment issues, or flaky checks.
Explains a structured response to a failed production deployment in a .NET application.
Explains release notes and changelog thinking for engineering, QA, support, and product communication.
Explains semantic versioning for .NET applications and how it communicates release impact.
Explains transient database errors, retry strategy, EF Core execution strategy, idempotency, timeouts, and avoiding retry storms.
Propagates request cancellation through async dependencies while keeping committed side effects and timeout policy explicit.
Covers App Service app settings, environment-specific configuration, restarts, slot settings, and avoiding hard-coded production values.
Explain how Task.WhenAll behaves when one or more tasks fail and how to inspect failures safely.
Covers allocation rate, collection frequency, latency symptoms, and safe production steps for GC-heavy services.
Uses file upload processing to practice bounded memory, stream ownership, temporary files, and retained buffers.
Covers chunking, bounded concurrency, scoped dependencies, progress, retries, and avoiding full-dataset memory spikes.
Explains health endpoints, readiness versus liveness, warm-up, dependency checks, and safe App Service health behavior.
Covers queue-backed work, idempotency, retries, visibility timeout, poison messages, progress tracking, and choosing Storage Queues or Service Bus.