Monitoring · Advanced · Those easily-missed type details in monitoring-pro

1.6K
MOr/monitoring-pro·posted by swoole_lee·3 days agoHelp

Those easily-missed type details in monitoring-pro

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

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.

// 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)
}

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".

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.

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.

337 comments

337 comments

· first 120 loaded
M
Zzhou_yiOP·2 hours ago

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

513
KkiteOP·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.

452
Ttang_haoMod·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.

5
Kkernel_panic·2 days ago

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

511
Mmike_xuMod·just now

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

450
Llinlin·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.

174
Zzhu_zongOP·1 hour agoedited

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

16
Sswoole_lee·28 minutes 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.

487
Rrase·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.

378
Kkite·2 days agoLevel 6

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

20
Sslow_query·2 days agoeditedLevel 6

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.

1
Ddev_zhou·2 days ago

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

362
Nnikic·2 days agoLevel 6

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

278
Kkernel_panic·2 days agoLevel 6

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.

6
Hhuang_ke·2 days 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.

213
Kkernel_panicMod·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.

105
Cchen_dev·2 days agoLevel 6

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

167
Cchen_dev·2 days agoLevel 6

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.

167
Rrase·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.

12
Wwinter·2 days agoLevel 6

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.

156
Ttang_haoOP·2 days agoLevel 6

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
Mmike_xu·just nowLevel 6

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

35
Lli_ming·yesterday

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

2
Llinlin·2 days agoLevel 6

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

178
Ddev_zhou·2 days ago

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

35
Cchen_dev·2 days ago

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

10
Rran_bo·2 days agoeditedLevel 6

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

34
Aalice_dev·3 minutes ago

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

46
Zzhou_yi·2 days ago

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

1
Kkernel_panic·2 days 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.

444
Ddev_zhou·yesterday

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

421
Rran_boMod·2 days ago

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

269
Oops_wang·2 days 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.

412
Ttang_hao·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.

376
Kkite·2 days ago

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

346
Cchen_dev·2 days agoedited

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.

343
Sslow_query·12 minutes ago

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

325
Zzhou_yi·3 minutes ago

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

305
Rran_bo·2 days ago

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

252
Oops_wang·2 days ago

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

394
Sslow_queryMod·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.

252
Zzhou_yi·2 days ago

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

240
Aalice_dev·yesterday

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

501
Zzhou_yi·2 days ago

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

7
Ttang_hao·just now

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

239
Rran_boOP·2 days 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.

245
Rran_bo·2 days 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.

216
Sslow_query·2 days ago

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

112
Sswoole_lee·2 days ago

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

55
Oops_wang·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.

39
Ddev_zhou·1 hour 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.

192
Bbob_chen·2 days 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.

26
Rrase·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.

11
WwinterOP·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.

112
Zzhou_yi·2 days agoedited

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

170
Lli_ming·2 days ago

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

166
Aalice_devOP·2 days ago

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

101
Oops_wang·2 days 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.

158
Sswoole_lee·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.

136
Nnikic·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.

29
Ddev_zhou·2 days 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.

134
Sswoole_leeOP·3 minutes ago

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

72
Mmike_xu·2 days 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.

126
Mmike_xu·3 minutes ago

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

120
Mmike_xu·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.

115
Rran_bo·2 days ago

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

90
Sslow_queryOP·3 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.

44
Rran_boOPMod·12 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.

409
Wwinter·2 days ago

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

452
Rran_boOP·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.

83
Kkite·2 days ago

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

95
Sswoole_lee·12 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.

90
Ddev_zhou·2 days 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.

84
Cchen_dev·2 days 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.

79
Lli_ming·5 hours ago

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

244
Kkite·2 hours ago

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

96
Ddev_zhou·5 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.

78
Sslow_query·2 days ago

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

58
Rran_boOP·12 minutes ago

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

124
Sswoole_leeMod·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.

48
Oops_wang·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.

1
Zzhu_zong·12 minutes ago

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

159
RraseMod·12 minutes ago

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

44
Ddev_zhou·just now

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.

41
Cchen_dev·28 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.

39
Mmike_xu·yesterdayedited

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.

38
Kkite·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.

150
Nnikic·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.

10
Ddev_zhou·2 days ago

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

20
Sswoole_lee·2 days ago

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

18
Kkite·2 days ago

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

18
Zzhu_zong·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.

17
Hhuang_keMod·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.

208
Nnikic·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.

14
Sslow_query·2 days ago

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

11
Cchen_dev·2 days ago

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

5
Sswoole_lee·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.

496
Cchen_devOP·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.

492
Hhuang_keMod·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.

226
Oops_wangMod·2 days 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.

4
Mmike_xu·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.

36
Oops_wang·2 days 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.

210
Kkernel_panic·2 days 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.

4
Lli_ming·1 hour ago

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

3
Bbob_chen·2 days ago

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

3
Zzhou_yi·2 days 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.

3
Llinlin·just now

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

1
Ddev_zhou·28 minutes ago

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

402
Aalice_dev·just now

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.

52
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.

1
Wwinter·2 days 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.

104
Ddev_zhou·2 days ago

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

211
Mmike_xuMod·1 hour ago

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

4
Ddev_zhouMod·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.

483
Lli_mingOP·2 days agoedited

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.

109
Zzhu_zong·1 hour agoedited

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

1
Hhuang_ke·5 hours ago

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

309
Rran_bo·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.

1
Zzhou_yi·2 days 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.

1
Llinlin·2 days ago

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

6

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