grep "#go" posts/*
25 results
When Go Is the Right Choice (and When It Isn't)
An honest assessment of Go's strengths and weaknesses — when to choose Go over Node.js, Rust, Java, and when to avoid it.
Rate Limiting in Go for High-Traffic APIs
Implementing rate limiting in Go — token bucket, sliding window, distributed rate limiting with Redis, and per-user vs global strategies.
Graceful Shutdown in Go Microservices Done Right
Complete guide to graceful shutdown in Go — signal handling, connection draining, worker completion, and Kubernetes integration.
Production-Ready Logging and Observability in Go
Setting up structured logging, distributed tracing, and metrics in Go services — slog, OpenTelemetry, Prometheus, and the observability stack.
Designing Go Services That Scale Horizontally
Patterns for building stateless Go services that scale by adding instances — session externalization, distributed locking, and load balancing strategies.
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.
Designing Safe Concurrent Systems in Go
Practical patterns for writing concurrent Go code that doesn't race — mutexes vs channels, atomic operations, and race condition detection.
Context Propagation in Go: Designing Cancelable Systems
Deep dive into Go's context package — propagation patterns, timeout chains, value storage, and designing systems that cancel gracefully.
Avoiding Goroutine Leaks in Long-Running Go Services
Common causes of goroutine leaks in Go and how to prevent them — context cancellation, channel cleanup, and leak detection in tests.
Worker Pools in Go: Design Patterns and Production Pitfalls
How to build worker pools in Go that handle backpressure, graceful shutdown, dynamic scaling, and error recovery without goroutine leaks.
Advanced Concurrency Patterns Every Go Engineer Should Know
Beyond goroutines and channels — fan-out/fan-in, pipelines, semaphores, singleflight, and errgroup patterns for production Go code.
Memory Optimization Techniques for High-Traffic Go Services
Practical memory optimization in Go — sync.Pool, arena patterns, slice pre-allocation, string interning, and reducing GC pressure.
Reducing Latency in Go APIs: Lessons from Production
Techniques that cut our API P99 latency from 800ms to under 100ms — connection pooling, query optimization, caching layers, and async processing.
Practical Go Performance Tuning in Real Production Systems
A field guide to Go performance tuning — GC tuning, allocation reduction, efficient I/O, and the benchmarks that actually matter.
Understanding Go Scheduler Behavior in High-Concurrency Systems
How the Go scheduler works under heavy load — GOMAXPROCS, goroutine scheduling, preemption, and what happens when you spawn a million goroutines.
Optimizing Go Services Handling Millions of Requests
Concrete optimizations for Go HTTP services at scale — connection reuse, zero-alloc patterns, efficient serialization, and database query tuning.
Profiling Go Services in Production: CPU, Memory, and Goroutine Leaks
Practical guide to profiling Go services using pprof, trace, and runtime metrics — finding CPU hotspots, memory leaks, and goroutine leaks in production.
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.
Designing a High-Throughput Event Processing Pipeline in Go
Architecture and implementation of a Go event pipeline handling millions of events — fan-out, batching, buffering, and backpressure.
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.
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.
How I Design Go Microservices for High Throughput Systems
Architectural patterns for building Go microservices that handle thousands of requests per second — connection pooling, batching, and backpressure.
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.
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.
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.