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Monitoring · Advanced · Choosing monitoring-pro: I turned 5 options into a side-by-side comparison

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MOr/monitoring-pro·posted by rase·2 days agoOpen source

Choosing monitoring-pro: I turned 5 options into a side-by-side comparison

Some background first. Our setup is monitoring-pro plus three downstream services, seven figures of daily requests, peaking around nine in the evening.

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 monitoring-pro itself but our upstream connection reuse — the load test traffic was too clean and hid the long-tail requests.

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18 comments

18 comments

M
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.

484
Llinlin·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.

478
Lli_ming·12 minutes ago

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

387
Hhuang_ke·just now

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

218
Nnikic·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.

187
Sswoole_lee·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".

125
Lli_ming·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.

185
Rran_bo·2 hours ago

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

238
Oops_wang·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.

184
Mmike_xu·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.

438
Aalice_dev·yesterday

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.

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Llinlin·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.

111
Sslow_query·28 minutes agoedited

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

81
Zzhou_yi·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.

43
Mmike_xu·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.

26
Sslow_query·28 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".

22
Wwinter·just now

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

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Llinlin·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.

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