Concurrency Control in .NET: Optimistic vs Pessimistic
Data integrity in high-traffic applications relies on how you handle concurrent updates. We compare DB locks (Pessimistic) against Row Versioning (Optimistic) in EF Core.
7 articles found
Data integrity in high-traffic applications relies on how you handle concurrent updates. We compare DB locks (Pessimistic) against Row Versioning (Optimistic) in EF Core.
Why BlueRobin moved from standard UUIDs to NanoIDs for primary keys: URL aesthetics, database considerations, and a custom alphabet implementation.
Going beyond simple webhooks. How to build a robust C# BackgroundService that listens to NATS events and manages a bidirectional Telegram Bot.
Separating reads from writes doesn't have to be complicated. Learn how to implement a practical CQRS architecture using FastEndpoints for the API and MediatR for clean command handling.
How we slashed system latency by 95% by moving from sequential HTTP calls to parallel NATS requests, implementing Redis caching, and tuning Qdrant vector search.
Decoupling frontend and backend tests by defining API contracts. How we verify Blazor/FastEndpoint compatibility in CI/CD without integration environments.
Achieve 100% reliable messaging by atomically committing state changes and events. A deep dive into the Outbox Pattern with EF Core and NATS utilizing background relay workers.