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Explains soft delete in EF Core APIs with practical .NET data-access examples and production trade-offs.
Protects transactional traffic from reporting load through freshness requirements, bounded asynchronous jobs, tuned summaries, workload isolation, replicas or warehouses, and explicit capacity gates.
Uses unique namespaces and correctly scoped fixtures so parallel tests improve speed without creating collisions.
Implements correct half-open interval overlap logic for booking validation.
Diagnoses hidden per-row EF Core queries and replaces them with a bounded query shape without creating an oversized join.
Explains a telemetry-driven path from slow endpoint symptoms to database, cache, dependency, CPU, or payload root cause.
Separates a live blocking chain from a deadlock victim, gathers the right database evidence, stabilizes the incident, and fixes lock duration or access order.
Pairs a bounded isolated reproduction with telemetry and a disposal fix for leaked database connections.
Explains N plus one query behavior, symptoms in APIs, fixes with set-based reads, batching, projections, and monitoring.
Explains EF Core projections into DTOs with practical .NET data-access examples and production trade-offs.
Explains raw SQL in EF Core with practical .NET data-access examples and production trade-offs.
Explains split queries versus single joined queries with practical .NET data-access examples and production trade-offs.
Explains EF Core tracking versus no-tracking queries with practical .NET data-access examples and production trade-offs.
Performs a set-based bulk update without loading session entities into the change tracker.
Explains join behavior using API-shaped data, missing related rows, and result-cardinality trade-offs.
Compares offset and keyset pagination for stable API lists, large tables, and user-facing result consistency.
Explains relational modeling, duplication, write consistency, read performance, and when denormalized data is justified.
Writes predicates the optimizer can use as index search arguments, then proves the effect through plans and reads while balancing computed columns, composite indexes, and write overhead.
Explains SQL three-valued logic, null-safe filters, optional relationships, and API behavior around missing values.
Explains parameter sniffing, data skew, cached plans, symptoms, and cautious mitigation options in SQL Server.
Explains how statistics and cardinality estimates affect plan choice, joins, memory grants, and slow queries.
Explains filtered Include in EF Core with practical .NET data-access examples and production trade-offs.
Uses EXISTS instead of a row-multiplying join when the related table is only a filter.
Groups normalized email values to identify duplicates before adding or repairing a uniqueness rule.