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Explains how to diagnose and mitigate a downstream dependency slowing the API through timeouts, retries, and degraded behavior.
Explains how to investigate queue age, backlog, worker health, poison messages, dependency failures, and safe catch-up.
Explains post-incident review, root cause, contributing factors, action items, tests, alerts, runbooks, and ownership.
Explains closed, open, and half-open behavior, failure classification, recovery probes, and the limits of circuit breakers.
Explains saturation signals and how systems shed, queue, throttle, or degrade before cascading failure.
Use correlation IDs, structured logs, and logging scopes to make API failures traceable in production.
Uses EF Core context pooling only when reusable context state, tenant isolation, and underlying connection state are controlled and tested.
Explains when EF Core compiled queries help, what they do not fix, and how to measure their value.
Explains how query tags, request correlation, and telemetry help connect slow SQL back to code paths.
Explains referential integrity, cascade delete trade-offs, restrict behavior, soft deletes, and operational safety.
Redesigns read-heavy shared state so readers observe a complete version without coordinating every access through a lock.
Explains the different diagnostic roles of logs, metrics, and traces during backend production issues.
Prevents lost updates with an original rowversion predicate, maps zero affected rows to an explicit conflict, and defines user, retry, aggregate, and API precondition behavior.
Explains the risks of Redis-based distributed locks and when database constraints, queues, or idempotency are safer.
Explains structured logging fields, safe context, redaction, event naming, and avoiding secret or personal-data leaks.
Makes business uniqueness race-safe with the exact database key, while handling normalization, tenant scope, nulls, soft deletion, rollout cleanup, and stable API conflicts.
Use Task.WhenAll to run independent asynchronous I/O operations concurrently while handling exceptions, cancellation, and dependency limits.
Captures test activities to prove one incoming request and its outgoing HTTP dependency share trace context.
Covers useful request, dependency, exception, log, metric, and availability telemetry for a production .NET API.
Covers symptom-based alerting for latency, error rate, availability, dependency failures, queue length, and resource pressure.
Explains scale-out bugs from in-memory sessions, local caches, background queues, uploaded files, and per-instance behavior.
Clarifies the difference between objects being retained accidentally and code simply allocating too much temporary memory.
Explains why memory diagnostics need access control, retention limits, and careful handling of secrets and user data.
Practices incident response after an OOM: restore service, collect evidence, identify trigger, and prevent recurrence.