Profile Go applications with pprof and benchmarks to identify CPU and memory bottlenecks.
npx skills add https://github.com/baphled/dotopencode --skill performance-baphled
Please help me install this Agent Skill. Skill: performance Source: https://github.com/baphled/dotopencode/tree/main/skills/performance Command: npx skills add https://github.com/baphled/dotopencode --skill performance-baphled
This Skill helps developers identify and resolve performance bottlenecks in Go applications, leading to faster execution and reduced resource consumption.
Use the performance skill to profile the CPU usage of the benchmarked function in the provided Go code.
High-intent search queries and answers about installing and using this skill.
You can profile Go application CPU usage by utilizing pprof to identify execution bottlenecks. This Skill implements data-driven profiling techniques to pinpoint exact lines of code causing high CPU load, allowing you to target and resolve performance issues directly.
To reduce memory allocations in Go APIs, you can apply optimization strategies like using sync.Pool to reuse objects. This minimizes garbage collection pressure under high load, leading to faster execution and significantly reduced resource consumption.
You can write and run benchmarks using the `go test -bench` command to quantify Go code performance. This Skill helps you implement these data-driven benchmarking techniques to accurately measure execution time before and after applying optimization strategies.
High latency in Go APIs often stems from memory allocations causing garbage collection pressure or concurrency contention. By profiling critical endpoints with pprof, you can identify these specific resource bottlenecks and refactor the code for better efficiency.
Yes, pprof can be used to identify goroutine concurrency contention in Go applications. This Skill utilizes pprof for comprehensive CPU, memory, and goroutine profiling to locate exactly where concurrent processes are blocking execution.
QunnnnBenchmark and profile Go applications using pprof and performance metrics.
eduardo-slProfiles and optimizes Go code to reduce allocations and improve hot-path performance.
VIethoangnguyenleBenchmark and profile Go code to analyze performance issues.
AI-Foundry-CoreInstruments applications with OpenTelemetry and deploys Jaeger/Tempo for end-to-end tracing.
