# Performance baseline

Numbers from `build/secs_bench --requests 20000 --concurrency 16` on
Docker / Ubuntu 24.04 inside Docker Desktop on macOS (M-series), single
io_context thread.  A rough capacity-planning envelope, not a
lab-grade benchmark — re-run on target hardware before sizing.

## Round-trip throughput / latency

| Scenario                         | Ops     | Elapsed |   Ops/sec  |  p50 µs |  p95 µs |  p99 µs |
|----------------------------------|--------:|--------:|-----------:|--------:|--------:|--------:|
| S1F1/F2 (header-only)            |   20000 |    0.14 |    ~140000 |      74 |     103 |     161 |
| S1F3/F4 (32 SVIDs)               |   20000 |    0.25 |     ~79000 |     165 |     186 |     260 |
| S6F11 push (W=0)                 |   20000 |    0.03 |    ~572000 |     n/a |     n/a |     n/a |

A real fab tool sustains tens to a few hundred S6F11 events/second.
Throughput is not the bottleneck on this stack; latency tail under
contention is.

## Memory footprint

A `ProcessJob` + `ControlJob` pair (no persistence enabled) is around
**~450 bytes** of heap (1000 pairs ≈ 0.45 MiB, measured on a fresh
process).  With persistence enabled add ~200 bytes of in-memory journal
path tracking per record.

| Active entity        | Approx bytes / instance |
|----------------------|------------------------:|
| PJ + CJ pair         |                    ~450 |
| Carrier (no slots)   |                     ~80 |
| Carrier slot         |                     ~24 |
| Substrate            |                    ~120 |
| Spool entry          | ~40 + encoded body size |

A busy fab tool tracking 50 carriers × 25 slots, 200 substrates, 20
active PJ+CJ pairs comes in well under 1 MiB of model state.  RSS will
be dominated by the binary itself + asio's buffers (~10-20 MiB),
not the model.

## How to re-run

```sh
docker compose run --rm builder /app/build/secs_bench \
    --requests 50000 \
    --concurrency 32 \
    --svid-count 32 \
    --store-pairs 10000
```

Output is markdown.

## What this does NOT measure

- **Real network**.  Loopback TCP has no MTU fragmentation, no
  retransmits, no jitter.  Production HSMS over a fab control LAN will
  see higher tail latency.
- **Persistence write amplification**.  The bench runs with persistence
  disabled.  Each store mutation with persistence enabled is one
  atomic-rename to disk; on rotational media that limits you to a few
  hundred mutations/sec.  SSD-backed deployments are fine.
- **Concurrent S6F11 enable filtering**.  Real CEID emission gates on
  the host's enable/disable list — this bench fires raw S6F11s.
- **Multi-session HSMS-GS** dispatch overhead — single-session only.
- **TLS-tunneled sockets** (via stunnel/sidecar) — these add ~50 µs
  per round-trip on modern hardware.