Mastering eBPF for Kernel-Level Tracing: Techniques and Real-World Patterns

TL;DR — eBPF lets you run sandboxed programs in the kernel to safely trace, profile, and network‑filter without recompiling or loading custom kernel modules. By attaching to well‑defined hook points you can capture latency metrics, security events, or custom metrics at micro‑second granularity. The Rust ecosystem now makes writing verified eBPF code as easy as writing ordinary application code.

eBPF has become the de‑facto bridge between userspace observability and the kernel, offering a safe, programmable path to instrument nearly every kernel subsystem. What started as a modest extension for network packet filtering (via BPF) has evolved into a general‑purpose runtime that can run millions of lightweight programs per second. In this post we’ll walk through the core concepts, attachment points, and production‑ready patterns for writing eBPF programs in Rust, and we’ll illustrate how to stitch those programs into a full‑stack tracing pipeline that feels native to modern observability stacks.

Understanding eBPF Fundamentals

What eBPF Is

eBPF (extended Berkeley Packet Filter) is a virtual machine embedded in the Linux kernel. Programs written in a restricted subset of C (or Rust via front‑ends) are verified for safety—no unbounded loops, no out‑of‑bounds memory access—and then JIT‑compiled to native instruction sets. Because the verifier guarantees memory safety, the kernel can load these programs at runtime without compromising stability.

The typical life‑cycle of an eBPF program looks like this:

1. Write the program (C, Rust, or a high‑level language such as bpftrace).
2. Compile it to BPF object format (*.o).
3. Load the object into the kernel via bpf() syscall.
4. Attach the program to a kernel hook (kprobe, uprobe, XDP, tracepoint, etc.).
5. Interact with the program through BPF maps (hash, array, per‑CPU) from userspace.

eBPF vs Traditional Kernel Probes

Traditional kernel probes (kprobes, jprobes, return‑probes) let you intercept any instruction address, but each probe incurs a relatively heavyweight context switch and often requires kernel recompilation or module loading. eBPF probes are loaded once and can be attached or detached dynamically; the verifier ensures they cannot corrupt kernel state. Moreover, eBPF programs can maintain persistent state via maps, enabling correlation across multiple events—something classic probes struggle with without external data structures.

Attachment Points and Program Types

Attaching to Tracepoints and kprobes

Tracepoints are statically defined kernel locations that emit events when triggered. They are the most performant way to hook into kernel logic because the overhead is minimal—only a conditional branch is added. kprobes, on the other hand, can be inserted at any address, giving fine‑grained control over function entry/exit, but they require the verifier to resolve the target address at load time.

// Example: kprobe that records the latency of do_sys_open
#include <linux/bpf.h>
#include <bpf/bpf_helpers.h>

SEC("kprobe/do_sys_open")
int BPF_KPROBE(record_open_latency) {
    u64 start = bpf_ktime_get_ns();
    // allow the actual syscall to proceed
    return 0;
}

// Tracepoint for the actual syscall return
SEC("tracepoint/syscalls/sys_enter_open")
int BPF_TRACEPOINT_PROBE(record_open_return) {
    u64 duration = bpf_ktime_get_ns() - start;
    // store duration in a per‑CPU map
    u64 *val = bpf_map_lookup_elem(cpu_map, &cpu, 0);
    if (val) *val += duration;
    return 0;
}

XDP: Network‑Level Interception

The eXpress Data Path (XDP) hooks into the network driver early in the packet path, before the kernel’s networking stack. This enables line‑rate packet processing with sub‑microsecond latency. XDP programs receive a struct xdp_md describing the packet and can return one of several actions: XDP_PASS (continue normal processing), XDP_DROP (drop), XDP_TX (re‑inject), or XDP_REDIRECT (send to another interface).

// Minimal XDP program in Rust using libbpf-rs
use libbpf_rs::BPFObject;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let obj = BPFObject::open_file("xdp_prog.bpf.o")?;
    let prog = obj.program("xdp_prog")?;
    // Attach to interface "eth0" at XDP hook
    prog.attach_xdp("eth0")?;
    println!("XDP program attached on eth0");
    Ok(())
}

uprobes and Userspace‑to‑Kernel Tracing

Uprobes allow you to set breakpoints in userspace binaries. When the target instruction is hit, the kernel runs the attached eBPF program. This is useful for tracing library calls, system‑call arguments, or performance‑critical code paths without modifying the binary.

Writing eBPF Programs in Rust

Getting Started with libbpf‑rs

Rust developers can lean on libbpf-rs, a safe wrapper around the C libbpf library. It handles object loading, map management, and program attachment with zero‑copy semantics.

// Example: Simple eBPF program that increments a map counter
use libbpf_rs::BPFObject;

fn main() {
    let obj = BPFObject::open_file("hello.bpf.o").expect("Failed to open BPF object");
    let prog = obj.program("hello").expect("Failed to find program");
    // Attach a kprobe to do_sys_open
    prog.attach_kprobe("do_sys_open", "p:myprobe").expect("Failed to attach kprobe");
    println!("eBPF program attached");
}

The above snippet opens a pre‑compiled BPF object, retrieves the program named hello, and attaches it to the do_sys_open entry point. All map interactions are performed through the same obj handle.

Verifying Safety with Rust’s Type System

One of Rust’s superpowers is its compile‑time guarantee of memory safety. When using libbpf-rs, the types for maps, programs, and helpers are explicitly defined, so a mismatched map lookup or an out‑of‑bounds access will cause a compile error long before the program ever reaches the kernel. Pairing libbpf-rs with static_assertions or const generics further reduces runtime surprises.

Using the tracing Crate from eBPF

The tracing crate provides a first‑class logging framework that works nicely with eBPF‑generated events. By emitting events through BPF maps and reading them in userspace, you can integrate eBPF data into existing tracing pipelines without custom adapters.

// Pseudo code for feeding eBPF data into a tracing subscriber
use tracing_subscriber::fmt;
use ring_buffer::RingBuffer;

let rb = RingBuffer::new(obj.map("events"))?; // events map defined in BPF program
loop {
    let event = rb.read::<Event>()?;
    tracing::info!("eBPF event: {:?}", event);
}

The RingBuffer abstraction leverages the kernel’s BPF_PERF_EVENT map type, delivering events with sub‑microsecond latency and back‑pressure handling.

Performance Considerations and Optimization

Map Operations and Lock‑Free Access

BPF maps are the primary communication channel between eBPF programs and userspace. Choosing the right map type is critical:

When performing lookups inside an eBPF program, prefer the bpf_map_lookup_elem helper with the BPF_ANY flag to avoid unnecessary allocations. In userspace, use the libbpf streaming APIs (bpf_map_lookup_batch, bpf_map_update_batch) to batch multiple operations into a single syscall, reducing lock contention and syscall overhead.

Avoiding Common Pitfalls

• Verifier rejection: Programs that use unsupported helpers, out‑of‑bounds array access, or loops with data‑dependent iteration will be rejected. Always compile with bpftool prog show or cargo bpf to inspect verifier logs.
• Map size: Hash maps have a maximum of 4096 entries (configurable). Pre‑allocate a size that matches your expected cardinality to avoid rehashing penalties.
• CPU migration: Per‑CPU maps automatically migrate with the executing CPU, but if you store a pointer to a per‑CPU value in a global variable, you may encounter stale data after migration. Keep per‑CPU data entirely within the map.

Latency Budget and CPU Overhead

A well‑tuned eBPF program typically adds 1–5 µs of latency per event on modern Xeon/AMD CPUs. When the program performs complex arithmetic or large map updates, that number can climb to 10–20 µs. To stay within acceptable bounds:

1. Minimize work in the program—offload heavy computation to userspace.
2. Use per‑CPU maps to avoid cross‑CPU synchronization.
3. Profile with perf record --bpfframe or bpftrace to identify hot paths.
4. Limit the number of simultaneously attached programs; each additional program adds a small but cumulative overhead.

Architecture: Building a Production‑Ready Tracing Pipeline

Data Flow: eBPF → Userspace via Ring Buffers

The most scalable pattern for high‑throughput tracing is the ring buffer (BPF_MAP_TYPE_PERF_EVENT). An eBPF program writes events into a perf event buffer, and a userspace consumer reads them in a lock‑free manner. This design decouples the producer (kernel) from the consumer (application) and naturally handles back‑pressure via buffer size configuration.

// Pseudo code for feeding eBPF data into a tracing subscriber
use tracing_subscriber::fmt;
use ring_buffer::RingBuffer;

let rb = RingBuffer::new(obj.map("events"))?; // events map defined in BPF program
loop {
    let event = rb.read::<Event>()?;
    tracing::info!("eBPF event: {:?}", event);
}

The RingBuffer type from the ring-buffer crate wraps the bpf_perf_event_open syscall, providing an iterator that yields events as they arrive. Applications can integrate this stream directly into the tracing subscriber, enabling correlation with logs, metrics, and spans from other services.

Integration with the tracing Crate

By emitting structured events (e.g., tracing::info!, tracing::error!) from within eBPF programs via BPF maps, you obtain a unified log format that works across processes, containers, and cloud platforms. The tracing-subscriber can be configured to pretty‑print, export to Jaeger, or write to Elasticsearch, all without modifying the kernel code.

Example: End‑to‑End Latency Histogram

Consider a scenario where we want to measure the latency of open() syscalls across a fleet of servers. The eBPF program records timestamps at entry and exit, stores the delta in a per‑CPU hash map, and periodically flushes the aggregated data to userspace.

// eBPF program: record open() latency into per‑CPU hash map
#include <linux/bpf.h>
#include <bpf/bpf_helpers.h>

struct data_t {
    u64 latency_ns;
};

BPF_HASH(latency_map, u64, struct data_t, 1024); // per‑CPU hash with 1024 entries

SEC("kprobe/do_sys_open")
int BPF_KPROBE(record_open_entry) {
    u64 start = bpf_ktime_get_ns();
    // store start timestamp keyed by current CPU id
    u64 cpu = bpf_smp_processor_id();
    struct data_t *val = latencymap.lookup_or_init(&cpu, (struct data_t){0});
    val->start = start;
    return 0;
}

SEC("kretprobe/do_sys_open")
int BPF_KRETPROBE(record_open_return) {
    u64 cpu = bpf_smp_processor_id();
    struct data_t *val = latencymap.lookup(&cpu);
    if (!val) return 0;
    u64 duration = bpf_ktime_get_ns() - val->start;
    // aggregate into a histogram stored in a userspace‑accessible map
    // (simplified: just accumulate into a running total)
    val->total += duration;
    val->count++;
    return 0;
}

In userspace, a periodic task reads the per‑CPU maps, computes percentiles, and emits the results as tracing spans or Prometheus metrics.

Deploying and Observability

Deploying eBPF programs in production typically involves:

1. Packaging the compiled BPF object as part of a DaemonSet (Kubernetes) or system service.
2. Feature flags to enable/disable specific probes per environment.
3. Metrics exposure via a sidecar Prometheus exporter that scrapes the userspace maps.
4. Tracing correlation by embedding a request‑ID in the BPF map key, allowing you to follow a request through kernel‑level events and application logs.

Key Takeaways

• eBPF programs run in a verified sandbox, guaranteeing safety without kernel recompilation.
• Choose the right attachment point: XDP for line‑rate networking, kprobes/uprobes for system‑call tracing, tracepoints for kernel events.
• Rust’s libbpf‑rs and the tracing crate combine zero‑cost abstractions with production‑grade observability.
• Maps (hash, array, per‑CPU) are the primary IPC mechanism between eBPF and userspace; prefer per‑CPU maps for hot paths.
• Always profile the eBPF program’s own overhead; a few microseconds of extra latency is acceptable, but dozens of microseconds can dominate tail latency.
• Keep programs small and focused; complex logic should be offloaded to userspace where debugging is easier.

Further Reading

• eBPF Documentation – Comprehensive tutorials, reference guides, and tooling overview.
• Linux Kernel eBPF Subsystem – Official kernel documentation for BPF API, maps, and verifier details.
• libbpf‑rs GitHub – Rust bindings to libbpf, featuring zero‑copy maps and program loading helpers.
• bpftrace – High‑level tracing language that compiles to eBPF, great for quick experiments.
• XDP: eXpress Data Path – Kernel documentation on XDP hooks and performance characteristics.