A new data‑capture pipeline has replaced the legacy iptables‑based flow logger on AWS Lambda workers. The replacement uses eBPF programs attached to traffic‑control hooks and a per‑network Rust tagger to emit the same Amazon Ion records while supporting IPv6 and cutting per‑packet overhead.
Why the previous solution broke at scale
The original design consisted of a kernel‑side extension that counted packets and matched them to tenant sandboxes, paired with a userspace daemon that read those counters, batched them, serialized them as Ion, and uploaded the files. This worked for a modest number of VMs but failed when Lambda packed thousands of Firecracker microVMs onto a single bare‑metal host.
- Rule explosion: each microVM added iptables entries. A host with a few thousand microVMs accumulated over a hundred thousand rules, forcing a linear walk for every packet and inflating latency as the host grew busier.
- Missing IPv6 support: the kernel module only understood IPv4, so the moment dual‑stack was required the system could no longer provide a complete ledger.
Both issues violated the two non‑negotiable requirements for Lambda flow logs: complete, correctly attributed records and negligible resource impact.
eBPF flow logging architecture
The new pipeline is built from three cooperating components:
- Privileged host loader: a single process per host loads the eBPF programs, configures the TC hook on each virtual network device, and spawns a tagger for every network namespace (i.e., each microVM).
- eBPF capture: tiny programs attached to the TC hook observe every packet, emit a compact event into a per‑CPU ring buffer, and do nothing else—no copying, blocking, or rewriting.
- Rust tagger: an unprivileged userspace process, one per network, reads events from the ring buffer, enriches them with the microVM identifier, and writes byte‑for‑byte identical Ion records to the existing billing/flow‑log pipeline.
Because the eBPF code only watches traffic, the CPU path is minimal. The Rust tagger runs in userspace, allowing easy updates without kernel changes, and the overall design natively supports IPv6 because the TC hook sees both address families.
Operational and security considerations
Switching to eBPF introduces new operational responsibilities:
- Program lifecycle management: the privileged loader must ensure that eBPF bytecode is verified and that updates are rolled out atomically across hosts.
- Ring‑buffer sizing: insufficient buffer depth can cause event loss; monitoring must track drop counters and adjust sizes as workload patterns evolve.
- Process isolation: the tagger runs without elevated privileges, reducing the attack surface compared to the previous kernel module that required broader access.
- Compatibility testing: because the output format is unchanged, downstream consumers need no changes, but integration tests should verify that the new path produces identical records under load.
From a security perspective, the eBPF programs are read‑only observers, which limits the risk of inadvertent packet manipulation. However, the privileged loader still holds the ability to inject code into the kernel, so its access controls and audit logging must be hardened.
Related CloudNinjas coverage: hands-on guides.
What This Means For Practitioners
For engineers building or operating serverless platforms, the shift to eBPF and Rust demonstrates a viable path to high‑density, low‑overhead telemetry. Evaluate whether your own multi‑tenant workloads suffer from rule‑based bottlenecks or lack IPv6 visibility, and consider a similar observer‑only eBPF approach. Pay particular attention to program verification, ring‑buffer health, and the separation of privileged loading from unprivileged processing to keep the new pipeline both performant and secure.