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Page 9 of 52
Treats Alembic autogeneration as a candidate schema diff that still needs semantic and operational review.
Explains migration state, historical model lookup, replay safety, and the limits of migration-time models.
Explains how tenant query filters help, where they can be bypassed, and what extra safeguards protect tenant isolation.
Design and debug rate limiting while protecting the API without blocking legitimate users and integrations.
Explains dynamic filters and SQL injection risk with practical .NET data-access examples and production trade-offs.
Designs a pragmatic branching strategy for normal releases, hotfixes, and production traceability.
Design background jobs that handle cancellation, retries, and duplicate execution without corrupting external state.
Use Channel<T> to coordinate producer/consumer background processing inside a .NET service while respecting backpressure and shutdown.
Explains partition key selection for ordering, load distribution, hot keys, and consumer scalability.
Maps business invariants and stale-data tolerance to strong or eventual consistency, explicit failure behavior, reconciliation, and user-visible state.
Reason through mitigation choices during a live App Service production incident.
Compares managed model APIs with operating open-weight models across control, expertise, privacy, scale, latency, cost, and portability.
Chooses between managed ingestion and retrieval convenience and custom control over indexing, ranking, security, evaluation, and operations.
Balances burst flexibility, predictable capacity, latency variance, commitment cost, and realistic traffic shape.
Connects orchestrator requests and limits to .NET GC, thread-pool behavior, throttling, OOM termination, and capacity planning.
Sets concurrency from the constrained resource and verifies throughput, latency, and downstream safety instead of maximizing active work.
Serializes work for the same resource while preserving concurrency across independent keys and managing keyed-lock lifetime safely.
Decide how to handle CPU-heavy work in an API without damaging request throughput or making the system unreliable.
Applies CQRS proportionally, separating model responsibilities without assuming separate databases, messaging, or event sourcing.
Creates and disposes explicit service scopes for hosted, queued, and parallel work without sharing scoped dependencies across operations.
Explain why awaiting while holding synchronization resources can create deadlocks, contention, or stalled workflows.
Uses deadlock evidence to correct EF Core transaction scope, query plans, and resource order, with bounded retries only for repeat-safe victims.
Diagnose and recover from a production failure caused by rotated secrets or stale secret references.
Explains database connection pool exhaustion with practical .NET data-access examples and production trade-offs.