
Event Sourcing in Practice: Patterns and Pitfalls
A practical guide to event sourcing — when to use it, how to implement event stores, build projections, handle schema evolution, and avoid common pitfalls.
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A practical guide to event sourcing — when to use it, how to implement event stores, build projections, handle schema evolution, and avoid common pitfalls.

A hands-on tutorial for a production-ready REST API with Go and Chi: routing, middleware, JSON handling, error responses and graceful shutdown.

Practical data modeling for MongoDB and document databases: embedding versus referencing, denormalization tradeoffs and schema evolution patterns.

How to configure and monitor database connection pools — covering pool sizing, leak detection, failover handling, and common misconfiguration pitfalls.

How API gateways handle routing, authentication, rate limiting and response aggregation — and how to build or choose the right one.

A practical introduction to machine learning concepts that backend engineers need when integrating ML models into production applications.

A deep dive into rate limiting algorithms with implementations, trade-offs, and guidance on choosing the right approach for your API.

Network failures mean requests get retried — idempotent API design makes processing the same request twice produce one result, not duplicate charges.

Every API evolves — the question is whether you version through URL paths, headers or query parameters, and how you ship breaking changes safely.

Opening a new database connection per request is a silent performance killer — connection pools solve this with a managed set of reusable connections.

GraphQL isn't a REST replacement — it's an alternative with different trade-offs that matter depending on your client complexity, team size, and data shape.

When HTTP polling isn't enough — a practical guide to WebSocket connections, message patterns, and production concerns like reconnection and scaling.