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Why WebSockets Aren't Always the Best Choice for Real-Time Communication

The hidden costs of WebSockets — persistent connections, scaling nightmares, server bills, and when simpler alternatives like SSE or polling actually win.

architecturebackenddistributed-systems

Engineering Trade-Offs Every Backend Engineer Must Understand

The fundamental trade-offs in backend engineering — consistency vs availability, latency vs throughput, simplicity vs flexibility, and how to navigate them.

architectureengineeringcareer

Designing Systems That Survive Production Traffic

Patterns for building systems that handle real-world traffic — load shedding, circuit breaking, graceful degradation, and capacity planning.

architecturebackenddistributed-systems

What 4+ Years of Backend Engineering Taught Me About System Design

Hard-won system design principles from building production systems — on complexity, trade-offs, data modeling, and the decisions that actually matter.

architecturecareerengineering

Building Scalable Go APIs with Clean Architecture

How I structure Go API services for maintainability and scale — handler/service/repo layers, dependency injection, and practical project layout.

gobackendarchitecture

Production Patterns for Event-Driven Systems in Go

Battle-tested patterns for running event-driven Go systems in production — transactional outbox, consumer groups, event replay, and schema evolution.

godistributed-systemsarchitecture

Building Resilient Workers in Go for Queue-Based Architectures

Patterns for building Go workers that consume from message queues reliably — graceful shutdown, health checks, backpressure, and poison message handling.

gobackendarchitecture

Handling Partial Failures in Distributed Go Systems

Strategies for dealing with partial failures in Go — circuit breakers, retry budgets, fallbacks, and the Saga pattern for distributed transactions.

godistributed-systemsarchitecture

Reliable Background Jobs in Go: Retries, Dead Letters, and Idempotency

Building production-grade background job processing in Go with exponential backoff, dead-letter queues, and idempotent handlers.

gobackendarchitecture

Lessons from Building Event-Driven Microservices in Go

Practical lessons on event schemas, eventual consistency, idempotent consumers, and the realities of building event-driven systems in Go.

gomicroservicesdistributed-systemsarchitecture

Designing a Distributed Task Queue in Go from Scratch

How I built a distributed task queue in Go with priority scheduling, retries, dead-letter queues, and horizontal scaling.

godistributed-systemsarchitecture