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Implements a small in-memory fixed-window rate limiter with per-key counters.
Processes a large import in chunks with fresh DbContexts, idempotent keys, cancellation, and bounded tracker growth.
Explains how to inspect EF Core generated SQL and connect LINQ shape to database execution behavior.
Chooses between atomic operations and a critical section based on whether one value or a multi-step invariant must change safely.
Investigates a growing-data EF Core slowdown through one correlated request, generated SQL, representative parameters, execution plan, waits, query shape, measured repair, and guarded rollout.
Explains how to triage post-release 500 errors using deployment correlation, logs, traces, feature flags, and rollback safety.
Explains how to diagnose 401/403 spikes across token validation, identity provider issues, clock skew, deployment changes, and abuse.
Uses per-dependency concurrency limits, queues, pools, and workload partitions to stop one failing path from exhausting the whole API.
Separates the ASP.NET Core HTTP server from proxy, TLS, load-balancing, process-management, and forwarded-header responsibilities.
Design a bounded-concurrency approach for calling an external API safely from .NET code.
Explains LINQ translation boundaries with practical .NET data-access examples and production trade-offs.
Relies on a database unique constraint and translates only the expected provider error into a domain conflict.
Explains cache observability across hit rate, latency, source load, memory, evictions, stale data, and fallback behavior.
Proves parallel speedup against a sequential baseline while accounting for overhead, saturation, tail latency, resource contention, and downstream impact.
Explains operational signals for queue-backed systems and how to respond when consumers fall behind.
Compares OpenTelemetry-based Azure Monitor instrumentation with older Application Insights SDK patterns for .NET services.
Explains expand-and-contract migrations, backwards-compatible schema changes, backfills, rollout order, and rollback thinking.
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.
Explains what happens when a hot key expires and how request coalescing, TTL jitter, background refresh, and stale serving help.
Finds circular lock acquisition and replaces timing-dependent nested locking with a stable order or a simpler ownership boundary.
Explains correlation IDs across request logs, dependency calls, queues, workers, and support investigations.
Combines ThreadPool counters, repeated stack snapshots, and wait-event traces to distinguish blocked workers from CPU or dependency pressure.
Fits database command timeouts into endpoint latency budgets while diagnosing slow SQL, blocking, pool pressure, and uncertain write outcomes.
Investigate and fix a race condition caused by shared mutable state in a .NET service.