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A five-hour soak at 136 times normal rate dropped nothing on a 1 GB free-tier VM, and the run's 56-second outlier traces to 45 minutes of package-metadata refresh that CPU and memory graphs read as healthy.
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Compiled by The EngineerSomething wrong?How this is made
The memory reading is the part worth taking away from this run. Container memory fell from 252 MiB to 88 MiB in a single sample, and the first hypothesis was an OOM restart [16]. Docker disagreed: restarts=0, oomkilled=false, exit=0, seven weeks of container uptime, and no OOM in dmesg on a host up 54 days [17]. The drop was the kernel reclaiming page cache, which docker stats charges to the container [18]. Host free memory rose in the same window, 317 MB to 396 MB, precisely because reclaim was running under write pressure [22]. An alert threshold on free memory would have fired in the good direction [23].
What moved was iowait: 2.66% at 06:10, 20.20% at 06:30, 34.24% at 06:40, still 29.12% at 06:50 [20]. Dirty pages peaked at 41,316 kB [20]. User CPU over the same window went from 1.65% to 4.09% [21]. The journal names the cause: apt-news.service and packagekit.service started within a second of each other at 06:04, and PackageKit did not deactivate until 06:49 [19]. That is 45 minutes on a shared-core VM with a slow persistent disk [19][25], or 16% of the run [6]. The most expensive thing that happened to this workflow engine in five hours was its host reading the news.
Divide 10,577 by 1,673 and you get 6.32, so the published 6.3x tail improvement is a p95 figure measured against the seven-day baseline [8][10][11][1]. At p99 the gain is smaller: 3.1x against seven days and 4.7x against thirty [2]. The 56.7-second outlier is described as 93x the median for its bucket [15]; 93 is what the run-wide median of 610 ms gives you, while that bucket's own p50 was 715 ms, which makes it 79x [3]. Neither correction moves the direction.
The figure I would plan against sits in the same bucket. During the disk storm, with iowait above 34%, that half hour's p95 was 4,727 ms [15]. The identical workflow's p95 in ordinary idle operation over the prior seven days was 10,577 ms [8], so the loaded, disk-contended box was still 2.2x better at p95 than the quiet one [4]. Four sends out of 2,880 were refused, 0.14%, and they errored at the client rather than being accepted and then dropped, which is the distinction the harness exists to measure [6][5][1].
The explanation offered for the inversion is cold path: at 4.5 events an hour the instance is idle essentially always and each arriving request wakes something up, while a five-second cadence never lets anything go cold [3][12]. The author labels that a hypothesis rather than a finding, and says the claim is the table, not the reason [13]. Take it at face value. The table is one box, one workflow, 0.17 events per second, which the author says tells you nothing about 50 per second [5].
For the improvement to transfer, two things have to be true of your box: the p99 has to be dominated by wakeup cost on an idle instance rather than queue depth, and the host has to be one where a maintenance unit can take the disk for three quarters of an hour. Where both hold, the ugly tail on a low-traffic self-hosted service is an idleness cost and adding load would reduce it [14]. The graph that catches the real stall is iowait, which the author notes is absent from most default dashboards [23].
Ranked by verification strength, evidence, and original report placement.
Results: 2,880 fired, 2,876 accepted, 4 refused at send (loud, client errored), 0 accepted then lost silently.
The 06:30 thirty-minute bucket: 273 fired, 0 refused, p50 715 ms, p95 4,727 ms, worst 56,726 ms, described as 56.7 seconds and 93x the median for that bucket.
The benchmark harness exists to measure how often automation platforms silently drop webhook events.
The self-hosted part of the harness runs on a Google Cloud e2-micro: 1 GB RAM, 0.25 vCPU baseline, 2 GB swap, free tier, $0/month.
The instance handles about 108 events a day, roughly 4.5 an hour, and has been up since July.
The author held one event every 5 seconds against the box for 4 hours and 42 minutes, 2,880 events, 136x its normal rate, sampling host telemetry every 15 minutes.
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Raw telemetry, one operator
The numbers arrive with their own provenance: per-bucket counts, docker stats output, quoted journal timestamps and a sar table at ten-minute granularity, and the 06:04 to 06:49 package window lines up with both the iowait climb and the single 56-second request. What holds this short of strong is that one person ran it once on one machine, nobody re-ran it, and the harness discarded the error strings for the four refused sends, so a small slice of the run has no cause attached to it at all.
A single box
Deployment here is literally one instance: an n8n container up seven weeks on a free-tier e2-micro handling about 108 events a day. There is no second operator or second provider, and the soak was never replicated; the author closes by saying one box with one trivial workload transfers nothing to a heavy one.
Caveated below the evidence
The loudest number in the story is 136x, and the author spends his next paragraph deflating it: 0.17 events a second is a trickle held for a long time. He also refuses to call the cold-path explanation anything more than a hypothesis and names the cheap experiment he skipped. Meanwhile the result most likely to matter to other people, that a standard CPU-and-RAM dashboard reported a healthy machine through 45 minutes of 34% iowait and a 56-second request, is stated more quietly than the telemetry warrants.
His own harness, his own box
The credibility this run builds accrues to the author's own benchmark harness, and the machine that came out looking capable is the one he pays nothing for and administers himself. Cutting the other way: no vendor is named as sponsor, the run exists to answer a criticism of his earlier burst test, and the passage he gives most detail to is his own missing error logging.
Internally consistent, externally untested
Timestamps, counters and percentiles cross-check each other inside the piece, which is more than most single-author benchmarks offer, and the author corrects his own OOM theory with evidence rather than dropping it. Confidence stays mid-range because the causal claim about idleness is untested by his own account, one loose multiple slipped into the outlier description, and five hours on one shared-core VM cannot separate this machine's slow persistent disk from small hosts generally.