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Edge Computing · Showcase · Choosing edge-computing-show: I turned 5 options into a side-by-side comparison

107
ECr/edge-computing-show·posted by alice_dev·5 minutes agoReview

Choosing edge-computing-show: I turned 5 options into a side-by-side comparison

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

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.

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.

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.

27 comments

27 comments

M
Ttang_haoOP·2 days ago

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

449
Lli_ming·5 hours ago

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

174
Ddev_zhou·just now

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

500
Hhuang_ke·3 minutes ago

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

461
Zzhu_zong·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.

132
Mmike_xu·3 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.

253
Wwinter·3 minutes ago

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

161
Sslow_queryOP·2 days ago

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

380
Rrase·12 minutes agoedited

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

100
Bbob_chenMod·12 minutes agoedited

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.

181
Hhuang_ke·28 minutes ago

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

353
Hhuang_ke·28 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.

140
Hhuang_ke·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.

17
Sswoole_lee·just now

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.

73
Bbob_chen·3 minutes ago

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

36
Hhuang_ke·5 hours ago

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

134
Hhuang_ke·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.

117
Zzhou_yi·28 minutes ago

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

103
Sswoole_lee·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.

143
Llinlin·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.

90
Oops_wang·3 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.

79
Sswoole_lee·1 hour 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.

18
Aalice_dev·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.

179
Ddev_zhou·28 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.

1
Mmike_xuOP·12 minutes ago

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

415
Oops_wang·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.

203
WwinterMod·2 days ago

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

1

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