Redis · Ops · Open-sourced a rate-limiting middleware for redis-ops with token bucket and sliding window

82
REr/redis-ops·posted by ran_bo·32 minutes agoExperience

Open-sourced a rate-limiting middleware for redis-ops with token bucket and sliding window

Short version: redis-ops needs almost no tuning at small and medium scale — the point where it starts to hurt is much further out than most people assume. Full measurements below.

# Load test: do not jump straight to the max concurrency.
# Ramp it up, otherwise you miss the knee.
for c in 50 100 200 400 800; do
  wrk -t8 -c$c -d60s --latency http://127.0.0.1:8080/api/feed
  sleep 20
done

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.

What genuinely surprised me was the tail. The average looked great while P99 jumped by an order of magnitude past some threshold. The cause was not redis-ops itself but our upstream connection reuse — the load test traffic was too clean and hid the long-tail requests.

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.

Worth noting: the official docs do cover this, just in a very inconspicuous spot. I only found it reading the source comments, where the author explains the reasoning — roughly "so that it degrades into predictable behaviour in extreme cases".

10 comments

10 comments

M
Sslow_query·3 minutes 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.

294
Hhuang_ke·3 minutes agoedited

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.

243
Wwinter·28 minutes agoedited

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.

5
Sswoole_leeOP·12 minutes agoedited

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

1
Ddev_zhou·28 minutes ago

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

59
Bbob_chen·12 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.

26
WwinterOP·just now

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

134
Zzhou_yi·3 minutes ago

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

98
Llinlin·just now

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

1
Ttang_hao·28 minutes ago

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

268

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