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Designs search and filtering with controlled query contracts, indexing, pagination, ranking, and operational limits.
Designs plan entitlements, provider webhooks, idempotent billing updates, access checks, grace periods, and support overrides.
Designs a controlled support impersonation workflow with scoped access, approvals, visible banners, audit trails, and session boundaries.
Designs membership, role changes, removal, ownership transfer, and permission updates without weakening tenant boundaries.
Designs an invitation workflow with token security, expiry, membership creation, email delivery, and replay-safe onboarding.
Designs a settings service with defaults, validation, scoped preferences, caching, and safe rollout of new settings.
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.
Explains N plus one query behavior, symptoms in APIs, fixes with set-based reads, batching, projections, and monitoring.
Decide whether Azure SQL errors are transient platform faults or a real application/query regression.
Maps an HTTP ETag precondition to EF Core rowversion and returns 412 when the representation is stale.
Performs a set-based bulk update without loading session entities into the change tracker.
Explains how consumer groups share event-stream work and how offset commits affect duplicate or lost processing.
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 why exactly-once claims do not remove the need for idempotent side effects and consistency boundaries.
Uses EXISTS instead of a row-multiplying join when the related table is only a filter.