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High Concurrency · Code review · Those easily-missed type details in high-concurrency-review

45
HCr/high-concurrency-review·posted by li_ming·2 days agoReview

Those easily-missed type details in high-concurrency-review

Most high-concurrency-review articles stop at "how to use it" and never cover "when not to use it". This is an attempt at the second half.

One last trap: in container environments remember to adjust the memory-related parameters in step. Otherwise the host limit and the process expectation disagree, and the symptom is intermittent, unreproducible failure.

Performance44%
Maintainability28%
Ecosystem and community17%
Hiring difficulty11%

77 votes total

19 comments

19 comments

M
Zzhu_zong·2 days ago

Agreeing with the above. One addition: with this option enabled the GC count in your metrics doubles, so adjust the alert threshold at the same time or it will keep firing.

466
Nnikic·5 hours ago

Worth learning from this debugging approach. We went straight at the logs and took a much longer route.

258
Llinlin·3 minutes ago

A question: what changes in a container with a 512Mi memory limit? That is how we run it in production.

245
Wwinter·5 hours ago

Has anyone run a controlled experiment? I did, reducing it to a single variable, and the difference was 4% — within noise. So I suspect the main cause is something else.

77
Lli_ming·3 minutes ago

Thanks for sharing real numbers — far more useful than the articles that only cover concepts.

44
Rran_bo·2 hours ago

One counter-example: below high-concurrency-review 7.4 the semantics of that code are different, so do not copy it verbatim. We got burned in staging and rolled back once.

305
Nnikic·2 hours ago

Agreeing with the above. One addition: with this option enabled the GC count in your metrics doubles, so adjust the alert threshold at the same time or it will keep firing.

35
Cchen_dev·5 hours ago

Sharing our numbers, 8 cores 16GB, same scenario:

| Concurrency | P50 | P99 |
|---|---|---|
| 200 | 12ms | 88ms |
| 500 | 31ms | 340ms |

P99 clearly collapses at 500 concurrency, which lines up with your knee point.

74
Ttang_hao·28 minutes ago

We have run this in production for two years without hitting it. That said, we never reached this scale, so our experience is not really evidence here.

40
Zzhou_yiOP·yesterday

There is actually a simpler fix that needs no architecture change: move this check up to the gateway and the problem disappears. The cost is one extra lookup at the gateway.

498
Cchen_dev·just now

Can you give a minimal reproduction? I ran it locally for ten minutes and could not reproduce on macOS with the latest version.

161
Ttang_hao·3 minutes ago

Has anyone run a controlled experiment? I did, reducing it to a single variable, and the difference was 4% — within noise. So I suspect the main cause is something else.

126
Ttang_hao·2 hours ago

This matches what we see in production. We only hit it past 3k QPS; the earlier load tests showed nothing — the test traffic was too clean, with no long-tail requests.

19
Wwinter·2 days ago

Saved. I am reworking this area this week — this saves a lot of wrong turns.

304
Lli_ming·3 minutes agoedited

Worth learning from this debugging approach. We went straight at the logs and took a much longer route.

8
Rrase·12 minutes agoedited

Sharing our numbers, 8 cores 16GB, same scenario:

| Concurrency | P50 | P99 |
|---|---|---|
| 200 | 12ms | 88ms |
| 500 | 31ms | 340ms |

P99 clearly collapses at 500 concurrency, which lines up with your knee point.

19
Sslow_query·just now

This is not a high-concurrency-review problem, it is a usage problem. The docs say this API is not thread-safe and you must lock around it yourself.

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Kkite·1 hour ago

I just read the high-concurrency-review source — the author actually explains the reasoning in a comment, roughly "so that it degrades into predictable behaviour in extreme cases".

1
Oops_wang·2 days agoedited

Can you give a minimal reproduction? I ran it locally for ten minutes and could not reproduce on macOS with the latest version.

237

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