tmux · Advanced · I built a small tool with tmux-pro — code is open, feedback welcome

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

One counter-example: below tmux-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.

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

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.

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.

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

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

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.

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.

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.

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

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

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 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.

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

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

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

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.

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

I just read the tmux-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.

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

I just read the tmux-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.

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.

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.

One counter-example: below tmux-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.

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

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.

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.

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

One counter-example: below tmux-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.

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.

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.

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.

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 is not a tmux-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.

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.

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 tmux-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 tmux-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.

One counter-example: below tmux-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.

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.

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

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

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.