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Introduction to eBPF: Linux Kernel-Level Observability and Performance Monitoring

Observing and securing systems at the kernel level historically meant writing kernel modules. However, writing kernel modules is risky. A single bug can crash the entire operating system, and updating them requires complex rebuilds.

Enter eBPF (Extended Berkeley Packet Filter). eBPF is a revolutionary technology that allows developers to run sandboxed programs inside the Linux kernel dynamically without modifying the kernel source code or loading external kernel modules. This enables safe, high-performance observability, networking, and security monitoring.

In this guide, we will break down how eBPF works, why it is transforming system observability, and how to write a simple system call monitor using BCC (BPF Compiler Collection).

How eBPF Works

At its core, eBPF turns the Linux kernel into an event-driven virtual machine. When a specific event occurs (such as a network packet arrival, a system call initiation, or a function tracepoint entry), the kernel executes the attached eBPF program.

The execution flow follows these steps:

  1. Write the Program: Write the eBPF program in restricted C.
  2. Compile to Bytecode: Compile the C code into eBPF bytecode using LLVM/Clang.
  3. Load into Kernel: Load the bytecode into the kernel using the sys_bpf system call.
  4. Verification: The kernel verifier inspects the bytecode to ensure it is safe (e.g., no infinite loops, no illegal memory accesses, and termination guarantees).
  5. JIT Compilation: The Just-In-Time compiler translates the bytecode into native machine instructions for maximum speed.
  6. Execution: The program runs at kernel speed when the target events are triggered.

Key Observability Use Cases

eBPF operates at the absolute center of system execution, giving it visibility into everything happening on the host or inside containers:

  • Low-Overhead Profiling: Traditional profilers introduce significant performance overhead. eBPF can sample CPU stacks directly in kernel space, minimizing overhead to less than 1 percent.
  • Network Performance Monitoring: eBPF programs can attach directly to network interfaces (XDP - eXpress Data Path) to inspect, route, or drop packets before they even reach the kernel networking stack.
  • Security Auditing: By monitoring system calls (syscalls) like sys_execve, eBPF can track every new process executed on a system, flagging unauthorized actions in real-time.
  • Container Observability: Since all containers on a host share the same kernel, a single eBPF agent can monitor all containerized workloads on a node without needing sidecars in each container.

Writing a Simple eBPF Program with BCC

The easiest way to start experimenting with eBPF is by using the BPF Compiler Collection (BCC). BCC allows you to write the kernel-space program in C and control/read output using a Python script.

Make sure you have BCC installed on your Linux machine before running this.

Create a file called monitor.py:

# monitor.py
from bcc import BPF

# 1. Define the eBPF C program running in kernel space
ebpf_code = """
int hello_world(void *ctx) {
    bpf_trace_printk("Hello, a process was created!\\n");
    return 0;
}
"""

# 2. Compile and load the program into the kernel
b = BPF(text=ebpf_code)

# 3. Attach the eBPF program to the sys_clone system call tracepoint
# sys_clone is triggered when new processes or threads are created
b.attach_kprobe(event=b.get_syscall_fnname("clone"), fn_name="hello_world")

# 4. Print trace output from the kernel
print("Tracing clone syscalls... Press Ctrl+C to exit.")
try:
    b.trace_print()
except KeyboardInterrupt:
    pass

Run this script as root:

sudo python3 monitor.py

Open a new terminal window and run any command (e.g., ls or pwd). In your BCC terminal, you will see a log printed every time a new process clones itself, demonstrating real-time kernel interception in action.

eBPF vs. Traditional Observability Tools

Traditional tools like tcpdump, strace, and prometheus exporters rely on copying data between kernel space and user space. This context switching is highly expensive under heavy workloads.

eBPF solves this by processing, filtering, and aggregating data directly inside kernel space. Only the final summary metrics are sent to user space, eliminating unnecessary CPU overhead and data copying.

Conclusion

eBPF is reshaping the infrastructure landscape. By turning the OS kernel into a programmable runtime, it allows developers to build extremely efficient monitoring, networking, and security solutions. Whether you are running containerized microservices in Kubernetes or troubleshooting low-level Linux performance bottlenecks, eBPF provides the deep observability needed for modern production environments.