moai-essentials-perf

CPU and memory profiling identifies which functions consume the most resources. Use tools like Scalene or cProfile to measure execution time and memory allocation, then focus optimization efforts on the hotspots that consume the most resources.

Profiling works across Python, Node.js, and Go but uses language-specific tools. Node.js uses Clinic.js, Go uses pprof, and Python uses Scalene or cProfile; each tool adapts to its runtime but follows the same profiling methodology.

Benchmarking compares baseline measurements against optimized code to quantify gains. Establish a baseline with profiling data, apply optimizations like caching or parallelism, then re-profile and measure the performance delta.

Memory optimization combines profiling to find allocations, applying strategies like lazy loading and caching, then validating improvements through production-staged benchmarks using tools like Scalene that separate CPU and memory metrics.

Multi-language profiling requires language-specific tools rather than a single solution. This Skill covers profiling strategies and tools across Python, Node.js, and Go to handle heterogeneous stacks in development, staging, and production.