Fortran · Resources · This fortran-resources bug hid for three years before anyone reported it

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FOr/fortran-resources·posted by mike_xu·32 minutes agoAnnouncement

This fortran-resources bug hid for three years before anyone reported it

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

// Minimal reproduction: you must use a real long-tail distribution here.
// Uniform load-test traffic will never trigger this.
func (s *Server) handle(ctx context.Context) error {
    conn, err := s.pool.Acquire(ctx)
    if err != nil {
        return fmt.Errorf("acquire: %w", err)
    }
    defer conn.Release()

    return s.do(ctx, conn)
}

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".

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.

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.

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.

8 comments

8 comments

M
Lli_ming·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.

369
Oops_wang·just nowedited

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

124
Ttang_hao·28 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.

107
Kkernel_panic·2 hours ago

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

181
Nnikic·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.

277
Oops_wang·3 minutes ago

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

217
Sswoole_lee·28 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.

112
Mmike_xu·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.

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