eBPF in Go: Observability for AI-Generated Services

A developer used eBPF with Go to debug a production issue in an AI-generated service where P95 latency spiked from 40ms to 4 seconds due to excessive kernel-level file I/O calls invisible to traditional tools. The tutorial demonstrates attaching eBPF programs to syscalls to trace kernel behavior without modifying the kernel or restarting services.

eBPF in Go: Observability for AI-Generated Services A hands-on tutorial on using eBPF with Go for kernel-level observability to debug production issues in AI-generated services. I recently hit a wall debugging a Go service that was generating AI code. P95 latency jumped from 40ms to 4 seconds with no app-level visibility into what was happening. Traditional logging and profiling tools were useless - the issue was happening at the kernel level. AI-generated code often lacks context about kernel interactions. eBPF lets you trace: All without modifying your kernel or restarting services. package main import "fmt""os"" " func main {// Load the eBPF programobjs := &struct {TraceOpen ebpf.Program ebpf:"trace open" }{} collSpec, err := ebpf.LoadCollectionSpec "trace.pbf" if err = nil { panic err } if err := collSpec.LoadAndAssign objs, nil ; err = nil { panic err } // Attach to the open syscall kp, err := ebpf.Kprobe "do syscall 64" if err = nil { panic err } if err := objs.TraceOpen.Attach kp ; err = nil { panic err } fmt.Println "Tracing... Hit Ctrl-C to exit" <-make chan struct{} } This approach helped me identify that AI-generated services were making excessive file I/O calls that weren’t visible in application logs. Once we added eBPF tracing, we could see the actual kernel-level behavior and optimize accordingly. I’ve published a complete working example with step-by-step instructions: https://cheikhhseck.medium.com/ebpf-in-go-observability-for-ai-generated-services-9aae7573b823 https://cheikhhseck.medium.com/ebpf-in-go-observability-for-ai-generated-services-9aae7573b823