Decoding HTTP/2 Traffic with eBPF: A Deep Dive into Modern Observability

As web applications scale and adopt more complex architectures, performance and observability become key priorities. HTTP/2, with its improved efficiency and multiplexed streams, has become the backbone of many modern services. But with its binary framing and stream multiplexing, decoding HTTP/2 traffic is not as straightforward as with HTTP/1.1.

This is where eBPF (Extended Berkeley Packet Filter) comes in. Once a niche feature in the Linux kernel, eBPF is now revolutionizing performance monitoring, network observability, and security by enabling programs to run safely in the kernel space.

In this blog, we’ll break down how eBPF can be used to decode HTTP/2 traffic, the challenges involved, and why it’s a game-changer for deep observability.

 

What is HTTP/2 and Why Is It Hard to Inspect?

HTTP/2 is the successor to HTTP/1.1 and offers significant performance improvements:

  • Binary framing: Instead of plain text, HTTP/2 encodes data in binary frames, making it more efficient and faster—but harder to read.


  • Multiplexing: Multiple streams of data can coexist over a single TCP connection.


  • Header compression: HPACK compression reduces redundant headers but adds complexity for monitoring tools.



These features make HTTP/2 fast but also opaque to traditional logging or packet capture tools like tcpdump or Wireshark unless they are HTTP/2 aware.

 

Enter eBPF: A Kernel-Level Superpower

eBPF allows developers to run sandboxed programs in the Linux kernel without modifying kernel source code or inserting modules. These programs can hook into various kernel events such as system calls, network packets, tracepoints, and more.

When it comes to network traffic, eBPF can attach to socket-level hooks, trace raw packets, and provide insights into how data flows through applications.

Here’s what makes eBPF ideal for decoding HTTP/2:

  • Real-time packet analysis


  • Low overhead performance monitoring


  • Dynamic tracing without restarts


  • Deep visibility into user and kernel space transitions



Challenges of Decoding HTTP/2 with eBPF

Decoding HTTP/2 with eBPF isn’t a plug-and-play task. The main challenges include:

1. Binary Protocol


Unlike HTTP/1.1, HTTP/2 is a binary protocol. eBPF must parse a stream of binary-encoded frames (e.g., HEADERS, DATA, SETTINGS) to reconstruct meaningful data.

2. HPACK Compression


Headers in HTTP/2 are compressed using the HPACK algorithm. Decompressing headers requires maintaining a dynamic table of header fields per connection.

3. Stream Multiplexing


Multiple request-response pairs can be in flight over a single connection, making it difficult to correlate data.

4. TLS Encryption


Most HTTP/2 traffic is encrypted over TLS, meaning payloads are not directly visible unless you tap into the application layer (e.g., using uprobes).

Practical Approach: How to Decode HTTP/2 with eBPF

To analyze HTTP/2 traffic effectively, you need a multi-layer strategy:

1. Use Socket-Level eBPF Programs


Attach eBPF programs to kprobes or tracepoints on system calls like sendmsg and recvmsg to capture raw TCP data.

2. Buffer Reassembly


Implement logic to reassemble TCP segments, especially since HTTP/2 frames might span across multiple packets.

3. Frame Parsing in User Space


Since eBPF programs have size and complexity limitations, frame decoding (including HPACK decompression) is typically offloaded to user space agents.

4. Stream Tracking


Maintain context in user space to track open streams per connection, decode multiplexed data correctly, and associate requests with responses.

5. TLS Workaround


If traffic is encrypted, you can:

  • Use uprobes to hook into the user-space functions of the server application (like nghttp2_send_frame) to capture plaintext data before encryption.


  • Leverage tools like bcc or bcc-tools to trace the application's memory space.



Real-World Tools That Do This

Several modern observability tools already implement these techniques:

  • Cilium: Uses eBPF to provide L7 visibility into HTTP/2 traffic across Kubernetes clusters.


  • Pixie: An open-source observability platform that uses eBPF + uprobe instrumentation to trace and decode application-layer traffic.


  • Keploy: Although focused on API testing and mocking, Keploy can utilize eBPF to capture API calls at the network layer to generate test cases.



Benefits of eBPF-Powered HTTP/2 Observability

  • Zero instrumentation: No need to modify source code or add SDKs.


  • Live traffic inspection: Capture and decode traffic in real-time.


  • Minimal performance impact: eBPF runs safely in the kernel with low overhead.


  • Works with any language: Since you're inspecting system calls or packets, it doesn’t matter what language the app is written in.



Final Thoughts

Decoding HTTP/2 traffic isn’t easy, but with eBPF, it’s finally feasible and efficient. By giving deep visibility into kernel and application behaviors, eBPF allows developers and DevOps teams to monitor, debug, and secure HTTP/2-based services at unprecedented levels of granularity.

Whether you’re building observability tools, tracking API performance, or debugging network latency issues, eBPF + HTTP/2 decoding is a modern superpower worth mastering.

As cloud-native systems continue to evolve, deep, dynamic, and decentralized observability powered by eBPF will no longer be optional—it will be essential.

Read more on- https://keploy.io/blog/community/decoding-http2-traffic-is-hard-but-ebpf-can-help

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