Clean Architecture · Chinese · clean-architecture-zh logging: what separates "readable" from "usable"

One counter-example: below clean-architecture-zh 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 just read the clean-architecture-zh source — the author actually explains the reasoning in a comment, roughly "so that it degrades into predictable behaviour in extreme cases".

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 clean-architecture-zh 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.

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.

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

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

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.

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 clean-architecture-zh 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.

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

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

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

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.

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

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

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.

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

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.

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.

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

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

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

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.

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.

I just read the clean-architecture-zh 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 clean-architecture-zh 7.4 the semantics of that code are different, so do not copy it verbatim. We got burned in staging and rolled back once.

This is not a clean-architecture-zh 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.

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

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.

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

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.

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.