Kafka · English · Cut our kafka-en build from 4 minutes to 40 seconds with these 5 changes

68
KAr/kafka-en·posted by ran_bo·6 hours agoPostmortem

Cut our kafka-en build from 4 minutes to 40 seconds with these 5 changes

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

Worth noting: the official docs do cover this, just in a very inconspicuous spot. I only found it reading the source comments, where the author explains the reasoning — roughly "so that it degrades into predictable behaviour in extreme cases".

// Minimal reproduction: you must use a real long-tail distribution here.
// Uniform load-test traffic will never trigger this.
func (s *Server) handle(ctx context.Context) error {
    conn, err := s.pool.Acquire(ctx)
    if err != nil {
        return fmt.Errorf("acquire: %w", err)
    }
    defer conn.Release()

    return s.do(ctx, conn)
}

What genuinely surprised me was the tail. The average looked great while P99 jumped by an order of magnitude past some threshold. The cause was not kafka-en itself but our upstream connection reuse — the load test traffic was too clean and hid the long-tail requests.

On trade-offs, my view is this: if nobody on the team owns this area long-term, do not introduce a second mechanism. With two coexistence you first have to work out which one is even in play when things break, and that costs far more than the performance you saved.

We also fixed monitoring along the way: replaced average-based alerts with percentiles and split them per endpoint. False alerts dropped by about seventy percent and the on-call rotation visibly cheered up.

29 comments

29 comments

M
Ttang_hao·2 days ago

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

518
Oops_wang·1 hour agoedited

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

392
Bbob_chen·28 minutes 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.

307
Aalice_dev·1 hour ago

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

18
Wwinter·28 minutes 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.

248
Hhuang_keOP·3 minutes ago

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

28
Sswoole_leeMod·2 hours 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.

211
Kkite·28 minutes ago

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

213
Hhuang_keOP·28 minutes ago

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.

6
Zzhou_yi·1 hour agoedited

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.

516
Hhuang_ke·2 days ago

I see point 3 differently. The trade-off depends on your read/write ratio: read-heavy with little writing means caching actually widens the inconsistency window.

196
Bbob_chen·2 days 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.

59
Aalice_devOP·just now

I see point 3 differently. The trade-off depends on your read/write ratio: read-heavy with little writing means caching actually widens the inconsistency window.

145
Rran_bo·2 hours 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.

165
Zzhu_zong·5 hours ago

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

8
Hhuang_ke·3 minutes 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.

164
Llinlin·2 days ago

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

37
WwinterOP·2 hours ago

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

87
Ddev_zhou·2 days ago

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

60
Mmike_xu·2 hours agoedited

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

8
Cchen_dev·2 days ago

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

76
Aalice_dev·12 minutes ago

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

37
Zzhu_zong·1 hour ago

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

23
Hhuang_ke·12 minutes 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.

12
Oops_wang·2 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.

6
Ddev_zhou·2 days 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.

6
Llinlin·2 days ago

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

181
Bbob_chenMod·2 days ago

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

1
Oops_wang·3 minutes ago

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

1

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