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Explains when to capture dumps, what to compare, and how to use roots without turning dumps into guesswork.
Covers allocation rate, collection frequency, latency symptoms, and safe production steps for GC-heavy services.
Explains health endpoints, readiness versus liveness, warm-up, dependency checks, and safe App Service health behavior.
Gives a practical incident flow for memory growth using metrics, traffic correlation, heap evidence, and safe mitigation.
Explains correlation IDs, distributed tracing, dependency telemetry, message boundaries, and logs across App Service, queues, and downstream APIs.
Builds a bounded readiness check for one required dependency while keeping liveness independent and responses non-sensitive.
Explains how to inspect EF Core generated SQL and connect LINQ shape to database execution behavior.
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.
Explains when to store large payloads outside the broker and pass references through messages.
Explains cache observability across hit rate, latency, source load, memory, evictions, stale data, and fallback behavior.
Chooses between a modular monolith and microservices using domain boundaries, team ownership, scaling, deployment, data consistency, and operational cost.
Explains operational signals for queue-backed systems and how to respond when consumers fall behind.
Explains when backend work belongs in a queue instead of slow or unreliable inline request handling.
Compares OpenTelemetry-based Azure Monitor instrumentation with older Application Insights SDK patterns for .NET services.
Preserves order only within the business key that requires it, while handling hot keys, gaps, stale events, replay, and poison messages explicitly.
Explains what happens when a hot key expires and how request coalescing, TTL jitter, background refresh, and stale serving help.
Explains insecure direct object reference risks and how APIs enforce ownership, tenant scope, and authorization per resource.
Explains why request DTOs should expose only allowed fields and how server-owned fields stay protected.
Explains correlation IDs across request logs, dependency calls, queues, workers, and support investigations.
Explains where secrets and tokens should live, what not to log, how rotation works, and how client storage changes risk.
Uses an actual execution plan, row-flow evidence, runtime measurements, and representative parameters to diagnose a slow query without guessing.
Repairs a workflow when a remote operation may have succeeded but local state, messages, and callbacks disagree.