Project 14: BPF-based Load Balancer (L4 XDP)

A Layer 4 load balancer using XDP that distributes incoming TCP connections across backend servers using consistent hashing—the foundation of technologies like Cilium and Katran.

Quick Reference

Attribute	Value
Primary Language	C (libbpf)
Alternative Languages	Rust (aya)
Difficulty	Level 5: Master
Time Estimate	4-6 weeks
Knowledge Area	Networking / Load Balancing / Infrastructure
Tooling	libbpf, XDP
Prerequisites	All previous projects completed, deep networking knowledge

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What You Will Build

A Layer 4 load balancer using XDP that distributes incoming TCP connections across backend servers using consistent hashing—the foundation of technologies like Cilium and Katran.

Why It Matters

This is production-grade eBPF. You’ll implement connection tracking, NAT, consistent hashing, and health checking—all at XDP speeds. This is how Facebook, Cloudflare, and Netflix handle millions of connections.

Core Challenges

• Connection tracking → maps to conntrack maps, 5-tuple hashing
• Consistent hashing → maps to Maglev hashing or similar
• NAT and checksum updates → maps to rewriting headers correctly
• Health checking → maps to backend state management

Key Concepts

• XDP Load Balancing: “Learning eBPF” Chapter 8 - Liz Rice
• Consistent Hashing: Maglev: A Fast and Reliable Software Network Load Balancer
• Katran Architecture: Facebook Katran Blog

Real-World Outcome

$ sudo ./xdp-lb eth0 --vip 10.0.0.100:80

XDP Load Balancer running
VIP: 10.0.0.100:80

$ sudo ./xdp-lb backend add 192.168.1.10:8080 --weight 3
$ sudo ./xdp-lb backend add 192.168.1.11:8080 --weight 2
$ sudo ./xdp-lb backend add 192.168.1.12:8080 --weight 1

Backends:
  192.168.1.10:8080  weight=3  health=OK   conns=15234
  192.168.1.11:8080  weight=2  health=OK   conns=10156
  192.168.1.12:8080  weight=1  health=OK   conns=5078

Statistics:
  Total connections: 30,468
  Active connections: 234
  Packets/sec: 145,678
  Throughput: 1.2 Gbps
  Drop rate: 0.001%

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Implementation Guide

1. Reproduce the simplest happy-path scenario.
2. Build the smallest working version of the core feature.
3. Add input validation and error handling.
4. Add instrumentation/logging to confirm behavior.
5. Refactor into clean modules with tests.

Milestones

• Milestone 1: Minimal working program that runs end-to-end.
• Milestone 2: Correct outputs for typical inputs.
• Milestone 3: Robust handling of edge cases.
• Milestone 4: Clean structure and documented usage.

Validation Checklist

• Output matches the real-world outcome example
• Handles invalid inputs safely
• Provides clear errors and exit codes
• Repeatable results across runs

References

• Main guide: LEARN_BPF_EBPF_LINUX.md
• “Learning eBPF” by Liz Rice