benchmark-analyzer

Performance bottlenecks in Go are identified by running benchmarks and analyzing execution metrics—ns/op (nanoseconds per operation), B/op (bytes allocated), and allocs/op (allocation count). benchmark-analyzer automates this: it discovers or generates benchmarks, executes them with consistent parameters, and reports which functions consume the most time or memory, pinpointing optimization targets.

Optimize Go benchmarks by first measuring what matters: run benchmarks multiple times to find stable results, then analyze memory allocations and CPU cycles. benchmark-analyzer executes go test -bench with memory profiling, captures reliable metrics across iterations, and suggests concrete trade-off-aware improvements based on the actual hot paths it discovers.

Yes. benchmark-analyzer generates missing benchmarks when they don't exist, targeting the functions most likely to benefit from optimization. It detects existing Benchmark functions in your test files, runs them with standardized parameters (go test -bench=. -benchmem -benchtime=3s), and reports results without requiring hand-written benchmark code.

Memory profiling in Go reveals allocation patterns—how many bytes and allocations occur per operation. benchmark-analyzer performs CPU and memory profiling on your benchmarks, collecting B/op and allocs/op metrics to identify functions wasting heap space or triggering garbage collection, enabling targeted optimization recommendations.

Three core metrics matter: ns/op (operation duration), B/op (bytes per operation), and allocs/op (heap allocations per operation). benchmark-analyzer interprets all three, identifies which metric dominates your bottleneck, and provides prioritized optimization guidance—whether the issue is latency, memory throughput, or garbage collection pressure.

No. benchmark-analyzer works with or without existing benchmarks. It scans your Go project for Benchmark functions, generates missing ones as needed, runs them with consistent parameters, and outputs a markdown report with optimization recommendations—whether your codebase has benchmarks already or needs them created.