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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.

gobackendperformance

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.

goperformance

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.

goperformancebackend

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.

goperformance

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.

goperformanceconcurrency

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.

goperformance

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.

goperformanceobservability

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.

godistributed-systemsperformance

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.

gomicroservicesperformance