Vue · Advanced · War story: vue-pro timezone handling almost cost us a full day of billing

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.

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.

One counter-example: below vue-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.

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

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.

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.

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

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

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

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.

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.

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.

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

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

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

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.

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

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

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.

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.

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.

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.

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

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

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

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

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.

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

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.

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.

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

One counter-example: below vue-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.

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.

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

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

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

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.

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.

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.

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