LLM Community · Help: llm fails to start intermittently in containers, logs inside

236
LLr/llm·posted by dev_zhou·32 minutes agoDiscussion

Help: llm fails to start intermittently in containers, logs inside

It took me two weeks of on-and-off digging and plenty of wrong turns. Writing the process down as it happened so the next person spends less time.

-- The query that broke: a full scan over 20M rows.
-- A composite index took P99 from 1.8s down to 42ms.
SELECT id, title, created_at
  FROM posts
 WHERE community_id = ?
   AND status = 1
 ORDER BY score DESC
 LIMIT 20;

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.

The first thing was to collapse the variables. We were changing config and upgrading the version at the same time, and afterwards nobody could say which change caused what. We rolled back to moving one variable at a time, re-ran three times, and only then did the curve settle. Tedious, but not skippable.

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.

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.

67 comments

67 comments

M
Rrase·2 days ago

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

520
Llinlin·2 days ago

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

450
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.

411
Kkite·2 days ago

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

367
Wwinter·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
Sslow_query·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.

352
Ttang_hao·12 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.

310
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.

301
Aalice_dev·just now

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

222
Ddev_zhou·2 days agoedited

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

51
Llinlin·2 days ago

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

293
Hhuang_keOP·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.

188
Kkernel_panic·5 hours 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.

207
Rran_bo·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.

69
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.

199
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.

137
Kkernel_panicOP·yesterday

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

4
RraseMod·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.

55
Hhuang_ke·12 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.

49
Nnikic·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.

49
Mmike_xu·just now

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

48
Mmike_xuOP·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.

8
Sslow_query·2 hours ago

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

43
Hhuang_ke·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.

493
Kkernel_panic·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.

30
Kkite·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.

351
Wwinter·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.

199
Rrase·12 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.

22
Sswoole_lee·12 minutes ago

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

12
Sslow_query·1 hour 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.

420
Hhuang_keOP·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.

154
Hhuang_keOP·2 hours ago

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

2
RraseMod·2 days agoedited

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.

313
Mmike_xu·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.

10
Bbob_chen·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.

99
Cchen_dev·2 days ago

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

169
Zzhu_zong·3 minutes agoedited

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.

45
Mmike_xu·2 days agoLevel 6

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

18
Rran_bo·just nowedited

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.

24
Ddev_zhou·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.

174
Ddev_zhou·2 days ago

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

60
Ddev_zhou·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.

348
Bbob_chen·2 days ago

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

8
Zzhou_yi·28 minutes ago

One counter-example: below llm 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
Rrase·2 days agoedited

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

367
Llinlin·2 hours ago

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

77
Kkernel_panic·5 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.

5
Sswoole_lee·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.

5
Cchen_dev·2 days ago

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

3
Oops_wang·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.

1
Wwinter·2 hours agoedited

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

37
Sswoole_lee·1 hour ago

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

61
Llinlin·2 days ago

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

343
Mmike_xu·2 days ago

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

171
Cchen_dev·1 hour agoedited

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

157
Rrase·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
Cchen_devOP·2 days agoLevel 6

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.

114
Nnikic·2 days ago

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

4
Sslow_query·2 hours ago

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

1
Sslow_query·2 days ago

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

385
Rran_bo·2 days agoedited

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

325
Oops_wang·12 minutes ago

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

240
Wwinter·5 hours 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.

89
Zzhu_zong·2 days agoLevel 6

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.

1
Sswoole_lee·2 days agoedited

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.

1
Oops_wang·2 days ago

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

240
Cchen_dev·2 days ago

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

1

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