Performance Tracing with eBPF

You will hook Rust application performance data into system-wide eBPF tracers.

In this lesson, you will learn how to bridge the gap between your Rust application's internal performance metrics and system-wide eBPF tracers to gain observability into runtime behavior.

The Problem of Visibility

Standard instrumentation (like tracing or log) is excellent for application-level events but often blind to what happens during system calls, context switches, or kernel-level contention. While you can profile a Rust binary locally, eBPF allows you to hook into the kernel to observe how your application interacts with the OS without modifying the application code itself.

Hooking into the Kernel

To integrate your Rust app with eBPF, we treat our binary as a telemetry source. We can use uprobes (user-space probes) to attach eBPF programs to specific symbols in our Rust binary. For example, if your application has a high-level function process_request, you can write an eBPF program that triggers whenever that symbol is hit:

// Inside your eBPF source (C or Rust via aya)
#[uprobe]
pub fn probe_process_request(ctx: ProbeContext) -> Result<u32, i64> {
    // Collect latency or argument data here
    let pid = bpf_get_current_pid_tgid();
    // Emit data to a perf event buffer for the Rust user-space app to read
    Ok(0)
}

System-Wide Contextualization

The true power lies in correlation. By injecting metadata—like your Rust application’s request IDs—into the task's bpf_local_storage or thread-local storage, an eBPF program can associate a kernel-level event (e.g., a disk I/O stall) with a specific application request.

Instead of asking, "Why is the system slow?", you can now ask, "What kernel events are occurring specifically during the lifetime of this Rust-orchestrated thread?" By utilizing the aya crate, you can write the user-space component of your eBPF loader entirely in Rust, allowing you to share data structures, types, and error-handling logic between your application and your monitoring tool. This unified ecosystem ensures that when you profile your production runtime, your application-level context remains intact even deep within the kernel stack.

Key Takeaway: By using uprobes to link internal Rust function execution to system-wide kernel events, you transform eBPF from a generic diagnostic tool into a surgical instrument for application performance optimization.