OpenTelemetry eBPF: Auto-Instrument Without Code Changes (2026)

OpenTelemetry’s eBPF integration lets you get telemetry without touching your application code, but it’s not magic; it’s a clever bit of kernel-level programming.

Let’s see it in action. Imagine a simple Go web server:

package main

import (
	"fmt"
	"net/http"
	"time"
)

func handler(w http.ResponseWriter, r *http.Request) {
	time.Sleep(100 * time.Millisecond) // Simulate work
	fmt.Fprintf(w, "Hello, %s!", r.URL.Path[1:])
}

func main() {
	http.HandleFunc("/", handler)
	fmt.Println("Server listening on :8080")
	http.ListenAndServe(":8080", nil)
}

Normally, to get OpenTelemetry traces for this, you’d add SDKs, configure exporters, and wrap your HTTP handlers. With eBPF, you don’t. You deploy the eBPF collector (often as part of a larger agent like the OpenTelemetry Collector with the eBPF receiver) and it attaches to your running process.

Here’s a simplified view of what the eBPF program does:

1. Kernel Hooking: It uses eBPF to hook into specific kernel events related to network I/O and process scheduling. For a web server, this means watching for sendmsg and recvmsg syscalls (for sending/receiving network data) and sched_switch (when the CPU switches between processes).
2. Event Correlation: When a sendmsg or recvmsg syscall occurs, the eBPF program inspects the packet headers to identify the connection (source/destination IP, port). It also looks at the process ID (PID) associated with the syscall.
3. Span Creation (In-Kernel): If the eBPF program recognizes this as part of an HTTP request (based on port 80/443 or by inspecting L7 protocols if more advanced features are enabled), it can create a "start span" event. It records the PID, the start time, and potentially details like the request method and path if it can parse them.
4. Trace Continuation: When the corresponding "end" event occurs (e.g., a sendmsg for the response, or a sched_switch indicating the process has done its work and is ready to send), the eBPF program correlates this back to the initial "start span" using the PID and timing. It then calculates the duration and generates a "end span" event.
5. Userspace Communication: These span events (start/end) are sent from the kernel to a userspace collector (like the OpenTelemetry Collector) via eBPF maps or ring buffers.
6. Trace Assembly: The userspace collector receives these raw span events, reconstructs the full traces by associating parent-child relationships (often inferred by the order of events or by matching trace IDs if the eBPF agent can inject them), adds necessary metadata (like service name, host IP), and then exports them to your backend (Jaeger, Prometheus, etc.) using standard OpenTelemetry protocols.

The core problem this solves is the "observability gap" for microservices and containerized applications where deploying code changes for instrumentation can be slow, error-prone, or simply impossible (e.g., third-party libraries, legacy systems). eBPF bridges this gap by observing system calls and network traffic at the kernel level, effectively seeing the application’s interactions without it knowing.

The key levers you control are:

• Attachment: Which PIDs or containers the eBPF program is allowed to attach to. This is usually configured in the agent’s deployment.
• Protocol Parsing: Whether to just capture network traffic or attempt to parse higher-level protocols (HTTP, gRPC) within the kernel or in userspace. This determines the richness of your spans (e.g., HTTP method, path, status code).
• Export Configuration: How the collected telemetry is formatted and sent to your backend (e.g., OTLP, Prometheus exposition format). This is standard OpenTelemetry Collector configuration.
• Sampling: While eBPF can generate a lot of data, you’ll still want to apply sampling strategies, often done in the userspace collector, to manage cardinality and cost.

The one thing most people don’t realize is that the eBPF program itself is often stateless regarding trace context. It relies heavily on correlating events based on process IDs and timing, and in some advanced scenarios, it might inject a minimal trace ID into network packets (if it can parse and rewrite them, which is complex) to help userspace reconstruction, but the heavy lifting of assembling complex trace graphs with parent-child relationships and rich attributes is typically done after the eBPF program sends raw span-like events to the userspace collector. The eBPF part is primarily about capturing the events and their basic timing/identity.

The next thing you’ll want to understand is how to configure the eBPF receiver’s protocol parsing capabilities to extract specific application-level attributes from network traffic.