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[GH-ISSUE #6021] Relay protocol selection (WS vs QUIC) + per-pair throughput ceiling (~25 Mbps with 76% Go runtime overhead) #11462
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opened 2026-08-05 01:29:46 -04:00 by saavagebueno
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Reference: DYNR/netbird#11462
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Originally created by @dlf-dds on GitHub (Apr 28, 2026).
Original GitHub issue: https://github.com/netbirdio/netbird/issues/6021
We've been doing a load-test campaign on a self-hosted netbird deployment (v0.70.0 daemon + v0.70.0 relay, official
netbirdio/relay:latestimage, t3.micro relay VPS in eu-central-1 / il-central-1, two peer-pairs behind separate AWS NAT Gateways forcing relay routing) and surfaced two related observations that we'd like to raise upstream. Both are reproducible.Original prompt for the investigation: hyper-derp's announcement post (https://hyper-derp.dev/blog/hyper-derp-announcement/), which benchmarks Netbird's relay code as part of the author's preamble. Our findings below partially confirm and partially refine the claims in that post against our own deployment.
1. Daemon picks WebSocket exclusively even when QUIC is available
The relay binary listens for both WebSocket (TCP) and QUIC (UDP) on the same port (
:33073):The netbird daemon binary contains the
quic-golibrary (verified viastrings | grep quic-go). Yet across our entire deployment (38 active peer connections during the observation window) 100% of relay connections are WebSocket; 0% are QUIC. Every entry in the relay log isWS client connected from <ip>, none areQUIC client connected from <ip>.Questions for the maintainers:
netbird up --helpshows none; we foundQUIC_GO_DISABLE_GSOandQUIC_GO_DISABLE_ECN(quic-go library tunables), but nothing controlling daemon-side protocol selection.prefer_quictoggle would let deployments take advantage of QUIC's congestion-control and HOL-blocking-resistance properties where the network supports UDP.We'd be happy to send a PR if there's appetite — please point us at the protocol-selection codepath if so.
2. Per-pair throughput caps at ~25 Mbps with 76% of CPU time in Go runtime overhead
iperf3-over-WireGuard between two peers forced into the relay path consistently caps at ~25-30 Mbps single-flow, regardless of:
tcp_rmem/tcp_wmemtuned to 16 MB on peers — only ~10% improvement)--network=hostequivalent — single-flow throughput identical to containerized)rmem_max(strace -cshows ZEROsetsockoptcalls — relay relies on Linux TCP autotuning, doesn't cap itself)strace -c -f -p <relay-pid>for a 20-second window during sustained load shows:76% of the relay process's measured CPU time is in
futex+nanosleep— Go runtime mutex contention and scheduler park/unpark. Only ~24% is actual network I/O syscalls. Relay process CPU peaked at 33% on the 2-vCPU instance — not CPU-bound at the processor level. This empirically aligns with the "fighting the Go runtime" framing in the hyper-derp post linked above.We confirmed inter-thread futex contention is part of the picture by sweeping
GOMAXPROCS:GOMAXPROCSSetting
GOMAXPROCS=1on a 2-vCPU relay yields ~25% improvement — collapses to a single OS thread, eliminates inter-thread futex traffic.Also worth flagging: when the relay starts with QUIC enabled, quic-go logs:
The quic-go library tries to setsockopt the UDP receive buffer to 7 MB but is capped by Linux's default
net.core.rmem_max=212992(208 KB). For deployments that DO use QUIC, this is likely a meaningful per-flow cap — could be worth either a deployment-doc note or adjusting the relay container's expectations.Questions for the maintainers:
GOMAXPROCS=1improvement been observed by others, and is it documented anywhere we missed?recvmmsg/sendmmsg) orkTLSoffload, which our profiling suggests would help the 24% I/O slice?Reproducer
The above is summarized from a multi-day RCA campaign — happy to share specific reproducer commands, full strace output, full iperf3 ramps, or run additional measurements if any of this is helpful. Please reply on this issue and we'll provide whatever level of detail is useful.
Thanks for the project!
@jfrconley commented on GitHub (May 28, 2026):
Not affiliated with netbird, but you should never do benchmarking of any kind on a burstable instance. t3.micro is going to burn through the burst credits very quickly and then throttle like mad. You should be using a non-burstable compute tuned instance for this.
You probably got better performance on single thread because you burned through the burst limit slower. Until these results can be validated on a non-burstable instance, they should be considered invalid. This isn't to say that the netbird relay is particularly performant, just that these results as presented are not useful in proving that.
The linked article is interesting, with what appears to be good data. The LLM sounding prose does concern me though...
@jfrconley commented on GitHub (May 29, 2026):
Upon follow up, un-scientific testing of my own CPU usage I can confirm two things:
Additionally, QUIC seems to be working fine for my testing. I already had net.core.rmem_max set appropriately.
Testing from hetzner dedicated AMD instance in hetzner with 3 vcpu, I consistently get 200-230 mbps and cpu usage of the relay container is at 200% (I run an unconsolidated container deployment). When setting GOMAXPROCS=1 I get roughly the same bandwidth but with only 100% cpu usage.
I see a couple of issues with this. For one, cpu usage (effective cost) to bandwidth is simply not economical. Cloudflare realtime turn would be an order of magnitude cheaper assuming you rely heavily on relay traffic. Likely faster as well. I had already suspected this was the case and only adopted the relay once external WebRTC was marked as "legacy". I have some doubts about the wisdom of the custom relay approach.
Second, even when this gets fixed there must be a mechanism for metering this usage to relay clients. Allowing a single client to blow out your entire relay budget doesn't make any sense. A default of 40mbps per peer seems reasonable to me.
@dlf-dds commented on GitHub (May 31, 2026):
Thanks for digging in, and especially for the dedicated-box numbers — that's the most useful part of this.
On burstable: fair, and I'll concede it for the single-flow figure specifically. But I don't think the
burst-credit mechanism explains the GOMAXPROCS result, and two things cut against it:
t3.micro's CPU credits. More importantly, throughput dropped as CPU dropped — down to ~14% at 16 streams.
Credit throttling does the opposite: it pins CPU at baseline while you try to push harder. What I saw is
the TCP-over-TCP head-of-line-blocking signature — WireGuard's UDP-shaped retries fighting the outer
TLS-over-TCP retransmit, buffers ballooning (12 MB → 520 MB in two minutes), throughput collapsing.
bandwidth, half the CPU) on a non-burstable dedicated AMD box. If burst credits were the cause it wouldn't
show up there. It matches an strace I ran showing ~76% of relay time in the Go scheduler (futex +
nanosleep) — inter-thread contention that GOMAXPROCS=1 removes by collapsing to a single OS thread.
And your 200–230 Mbps single-flow actually answers an open question I had. My 31.8 Mbps matched the t3.nano
peer network baseline exactly, so I couldn't tell whether I was measuring the relay or the peer NIC. Your
number says it was the peer NIC — the relay clears 200+ on adequate hardware. So the headline isn't "the
relay caps at 32 Mbps," it's "the relay burns a lot of CPU per Mbps and falls over under multi-flow." Which
is your point, and I agree with it.
So I'd push back on "results should be considered invalid": the CPU-isn't-the-bottleneck-at-multi-flow
finding, the multi-flow collapse, and the GOMAXPROCS win are all hardware-independent, and you confirmed
two of them on bare metal yourself. The one absolute number worth re-running on non-burstable peers is the
single-flow ceiling — and you've basically handed me that already.
GOMAXPROCS=1 is a free ~25% on a 2-vCPU relay until the data plane gets reworked, so worth setting
regardless.
Agree on per-peer metering — one peer saturating a shared relay is a real problem, and a sensible default
cap would help.
On Cloudflare Realtime TURN: agree it's cheaper if you can offload relaying to a third party. Some
deployments can't (trust/sovereignty constraints), so a self-hosted relay still has a reason to exist — it
just needs to stop being this expensive per Mbps.
@Silex commented on GitHub (Jul 15, 2026):
Chiming in with data from an independent setup — we hit the same per-pair ceiling, and I think we found the main root cause, with a relatively simple fix.
Setup: two Linux peers (1 Gbit NICs, ~5 ms RTT between them through the relay), stock netbird 0.74.2, a dedicated relay VPS running the stock
netbirdio/relayimage, relay forced. Baseline: ~950 Mbit/s P2P between the same two peers, but only ~95–100 Mbit/s single-flow through the relay.Root cause: nothing in the relayed data path ever sizes its UDP socket buffers — your strace observation ("zero setsockopt calls") is exactly it. Every socket runs at the OS default (
net.core.rmem_default, typically ~208 KiB). The counterintuitive part: the drops that matter don't happen on the relay at all — they happen in the sending peer's own kernel, on the local UDP socket netbird uses to pull packets out of WireGuard. A single fast flow overruns that ~208 KiB buffer, the kernel drops, the tunnelled TCP sees unexplained loss, and its congestion window collapses to ~95 Mbit/s. We confirmed this by watching per-runnetstat -sudeltas on all three hosts: the UDP drop counters move on the sender — not on the relay, not on the receiver.Fix + numbers (single iperf3 flow, cubic, receiver-side Mbit/s, completely stock sysctls):
Retransmissions on the tunnelled TCP go from hundreds per 30 s run to zero. The change sizes the relay-path sockets from inside netbird (
SO_RCVBUFFORCE/SO_SNDBUFFORCEwhen privileged — which the daemon typically is — with portableSetReadBuffer/SetWriteBufferas fallback), so peers need no sysctl tuning.PR to fix this issue and gain roughly 1.5-2x perfs is https://github.com/netbirdio/netbird/pull/6774
Other things we tried along the way, some of them also with huge gains (see other PRs)
NB_RELAY_TRANSPORT=ws|quic(shared/relay/client/transport.go) to pick the transport explicitly. Interesting twist: once the buffers are fixed, WS consistently outperformed QUIC in our runs (227 vs 183 Mbit/s with batched reads) — QUIC datagrams are capped by path MTU so they can't carry coalesced frames, and quic-go's receive datagram queue drops silently under bursts.