89ca72d471
Two threads landing together — the doc edits interleave so they ship in a single commit. 1. **vectord substrate fix verified at original scale** (closes the 2026-05-01 thread). Re-ran multitier 5min @ conc=50: 132,211 scenarios at 438/sec, 6/6 classes at 0% failure (was 4/6 pre-fix). Throughput dropped 1,115 → 438/sec because previously-broken scenarios now do real HNSW Add work — honest cost of correctness. The fix (i.vectors side-store + safeGraphAdd recover wrappers + smallIndexRebuildThreshold=32 + saveTask coalescing) holds at the footprint that originally surfaced the bug. 2. **Materializer port** — internal/materializer + cmd/materializer + scripts/materializer_smoke.sh. Ports scripts/distillation/transforms.ts (12 transforms) + build_evidence_index.ts (idempotency, day-partition, receipt). On-wire JSON shape matches TS so Bun and Go runs are interchangeable. 14 tests green. 3. **Replay port** — internal/replay + cmd/replay + scripts/replay_smoke.sh. Ports scripts/distillation/replay.ts (retrieve → bundle → /v1/chat → validate → log). Closes audit-FULL phase 7 live invocation on the Go side. Both runtimes append to the same data/_kb/replay_runs.jsonl (schema=replay_run.v1). 14 tests green. Side effect on internal/distillation/types.go: EvidenceRecord gained prompt_tokens, completion_tokens, and metadata fields to mirror the TS shape the materializer transforms produce. STATE_OF_PLAY refreshed to 2026-05-02; ARCHITECTURE_COMPARISON decisions tracker moves the materializer + replay items from _open_ to DONE and adds the substrate-fix scale verification row. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
199 lines
9.9 KiB
Markdown
199 lines
9.9 KiB
Markdown
# Multi-tier load test — 100k workers, 6 scenarios, real validators
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J's request: a much more sophisticated test using the 100k corpus
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from the Rust legacy database, exercising the new EmailValidator +
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FillValidator, plus profile-swap and other realistic coordinator
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workflow scenarios.
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## Setup
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- **Corpus**: 100,000 workers from
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`/home/profit/lakehouse/data/datasets/workers_100k.parquet`,
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ingested into Go vectord via `staffing_workers -limit 100000`
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(~55 minutes). Index: `workers` on persistent stack, dim=768.
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- **Persistent Go stack** on `:4110+:4211-:4219` (11 daemons,
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3-layer isolation from smoke harness).
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- **Bun frontend** at `:3700` (not used by this test — direct hits to
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Go gateway).
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- **Validator pool**: 200 in-process workers (`test-w-XXX` IDs)
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with matched city/state/role pairs across 35 unique combos.
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- **Tool**: `scripts/cutover/multitier/main.go` — 6-scenario
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harness with weighted random scenario selection per goroutine.
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## Six scenarios + weights
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| Scenario | Weight | Steps | Validators |
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|---|---:|---|---|
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| `cold_search_email` | 35% | search → email outreach + validate | EmailValidator |
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| `surge_fill_validate` | 15% | search → fill proposal (2 workers) → FillValidator → record | FillValidator |
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| `profile_swap` | 15% | original search → swap with `ExcludeIDs` → no-overlap check | (none — substrate-only) |
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| `repeat_cache` | 15% | same query × 5 → cache effectiveness measure | (none) |
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| `sms_validate` | 10% | search → SMS draft (≤160 chars, contains phone for SSN false-positive test) → validate | EmailValidator (kind=sms) |
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| `playbook_record_replay` | 10% | cold search → record → warm search w/ `use_playbook=true` | (none — exercises learning loop) |
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## Results — sustained 5-minute run, conc=50
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| Scenario | Runs | Fail% | p50 | p95 | p99 | max |
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|---|---:|---:|---:|---:|---:|---:|
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| `cold_search_email` | 117,406 | **0.0%** | 2.22ms | 5.37ms | 8.61ms | 452ms |
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| `surge_fill_validate` | 50,091 | 98.8% | 5.02ms | 13.14ms | 44.02ms | 681ms |
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| `profile_swap` | 50,263 | **0.0%** | 4.45ms | 9.65ms | 14.04ms | 461ms |
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| `repeat_cache` | 50,576 | **0.0%** | 11.73ms | 21.03ms | 29.92ms | 453ms |
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| `sms_validate` | 33,524 | **0.0%** | 2.13ms | 5.24ms | 8.48ms | 467ms |
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| `playbook_record_replay` | 33,397 | 96.8% | 391ms | 477ms | 719ms | 1,018ms |
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| **TOTAL** | **335,257** | — | — | — | — | — |
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**1,115 scenarios per second** sustained over 5 minutes. **4 of 6
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scenarios at 0% failure** across 251,769 successful workflows.
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Cache effectiveness (repeat_cache scenario, 5 sequential queries
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each): 50,576 × 5 = **252,880 cached searches**, all returning the
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same top-K with no failures. The matrixd retrieve path scales fine
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on the 100k corpus.
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## Resource footprint at 100k corpus
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| Daemon | CPU% | RSS | Note |
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|---|---:|---:|---|
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| persistent-vectord | 76% | **1.23GB** | linear with 100k vectors (vs 82MB at 5k) |
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| persistent-matrixd | 75% | 26MB | bottleneck at conc=50+ (1 core pegged) |
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| persistent-gateway | 30% | 26MB | proxy + auth |
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| persistent-embedd | 21% | 97MB | embed cache + Ollama bridge |
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| persistent-storaged | 11% | 82MB | rehydrate I/O active |
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| (5 other daemons) | ~0% | ~25MB each | idle |
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| **Total** | — | **~1.7GB** | |
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Compare to Rust gateway under similar load: **14.9GB RSS**. Even at
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100k workers, Go uses **~10× less memory** with explicit per-daemon
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attribution.
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## What the test exposed (substrate finding)
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The two scenarios that hit `/v1/matrix/playbooks/record`
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(surge_fill_validate, playbook_record_replay) failed at 96-98% rate.
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Failure stack identified: **coder/hnsw v0.6.1 nil pointer in
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`layerNode.search` (graph.go:95)** triggered during HNSW Add to the
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small-state playbook_memory index.
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**Reproduction:**
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1. Empty playbook_memory index (length=0)
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2. First record succeeds (length=1)
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3. Subsequent record under concurrent load → coder/hnsw panics
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4. Repeated concurrent records → index transitions through
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degenerate states where entry node is nil
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**Root cause:** coder/hnsw v0.6.1 doesn't handle the len=0/1
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edge case correctly when the graph has been Delete'd-then-Add'd.
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The vectord wrapper has a partial guard (resets graph on len=1
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during re-add) but doesn't catch every degenerate state.
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**Workaround applied:** added a `recover()` guard in
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`internal/vectord/index.go` BatchAdd — panics now return errors
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instead of killing the request handler. Daemon stays up; clients
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get HTTP 500 with a clear "DELETE the index to recover" hint.
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**Operator recovery:** when `/v1/matrix/playbooks/record` starts
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returning 500s, run:
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```bash
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curl -X DELETE http://localhost:4215/vectors/index/playbook_memory
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```
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Next record will recreate the index fresh.
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**Proper fix (deferred):** either (a) upstream patch to coder/hnsw,
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(b) write a different small-index Add path that always rebuilds
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from scratch when len < threshold, or (c) switch playbook_memory
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to a different vector store (Lance? in-memory map for the
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playbook-corpus shape, since playbook entries are small).
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## What the test confirmed (production-readiness)
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Across 335k scenarios in 5 minutes:
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1. **Search at 100k corpus is fast** — p99 8.6ms on cold path,
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matching the 5k corpus characteristics. HNSW search is
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`O(log n)` so 20× corpus growth barely registered.
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2. **Validator integration works at load** — 117,406 EmailValidator
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passes in cold_search_email + 33,524 in sms_validate. The
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in-process validators don't bottleneck.
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3. **Profile swap with ExcludeIDs is correct** — 50,263 swaps,
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zero overlap detected between original + swap result sets.
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The ExcludeIDs filter holds.
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4. **Embed cache effectiveness verified** — repeat_cache scenario
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(5 sequential queries each) yielded 252,880 cached searches
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with no failures and consistent latencies. Cache hit rate is
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high enough that 100k-corpus search costs match 5k-corpus
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search costs in p50.
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5. **SMS-shape phone-number false-positive guard works** —
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33,524 SMS drafts containing "Call 555-123-4567" (phone shape
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that ALMOST matches SSN-shape NNN-NN-NNNN) all passed the
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EmailValidator's flanking-digit guard.
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6. **Cross-daemon HTTP overhead is negligible** —
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matrixd→vectord→embedd round-trips at ~2-12ms p50 across
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scenarios.
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## What this DOES NOT cover
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- **Real coordinator demand patterns** — bodies rotated round-robin;
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real workloads have arrival-rate variability + burst clustering.
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- **Multi-host horizontal scale** — single-machine load.
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- **Sustained for hours** — 5-minute window; long-tail leaks
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(file handles, goroutine pools, MinIO connections) not tested.
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- **Concurrent ingest + load** — the 100k ingest finished BEFORE
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the test ran. Mixed read/write at scale is a separate probe.
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- **Real Bun frontend in path** — direct-to-Go for max throughput.
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Bun adds ~5x latency overhead per the earlier `g5_load_test.md`.
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## Repro
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```bash
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# Stack must be up:
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./scripts/cutover/start_go_stack.sh
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# Ingest 100k workers (one-time, ~55 min):
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./bin/staffing_workers -limit 100000 \
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-parquet /home/profit/lakehouse/data/datasets/workers_100k.parquet \
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-gateway http://127.0.0.1:4110 -drop=true
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# Reset playbook_memory if it's in a degenerate state:
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curl -X DELETE http://127.0.0.1:4215/vectors/index/playbook_memory
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# Build + run multitier:
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go build -o bin/multitier ./scripts/cutover/multitier
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./bin/multitier -gateway http://127.0.0.1:4110 -concurrency 50 -duration 300s
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# Stderr is parseable JSON for CI integration.
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```
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## Decisions tracker delta
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Add to `docs/ARCHITECTURE_COMPARISON.md` Decisions tracker:
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| Date | Decision | Effect |
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| 2026-05-01 | playbook_record under load triggers coder/hnsw v0.6.1 nil-deref | **Recover guard added** in BatchAdd; daemon stays up. **Real fix open**: upstream patch OR small-index custom Add path OR alternate store. |
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| 2026-05-01 (later) | **Real fix landed.** vectord lifts source-of-truth out of coder/hnsw via `i.vectors map[string][]float32` side store; `safeGraphAdd`/`safeGraphDelete` recover panics; warm-path Add falls back to rebuild on failure; `rebuildGraphLocked` reads from the panic-safe side map. Re-ran multitier 60s/conc=50: **0 failures across 19,622 scenarios** (was 96-98% on 2/6). p50 on previously-failing scenarios moves 5ms (instant fail) → 551ms (real Add work — honest cost of correctness). Memory cost: ~2× for vectors. STATE_OF_PLAY captures the architecture invariant. |
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| 2026-05-02 | **Full-scale verification.** Re-ran multitier at the original failure-surfacing footprint (5min @ conc=50). Result: **132,211 scenarios at 438.5/sec, 0 failures across all 6 classes.** Throughput dropped from pre-fix 1,115/sec → 438/sec because previously-broken scenarios (96-98% fail) now do real HNSW Add work instead of fast nil-deref panics. Healthy tails: `surge_fill_validate` p50=28.9ms / p99=1.53s, `playbook_record_replay` p50=504ms / p99=2.32s — small-index rebuild kicking in under sustained churn, working as designed. **Substrate fix scales beyond the 19.6k-scenario probe; closing the open thread.** |
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## Conclusion
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**Pre-fix (2026-05-01):** 335,257 scenarios in 5min, 4/6 classes at 0%
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failure, 2/6 hit a coder/hnsw v0.6.1 nil-deref under playbook record
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churn. Operator recovery via DELETE + recreate.
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**Post-fix (2026-05-02):** 132,211 scenarios in 5min @ conc=50,
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**6/6 classes at 0% failure**. Throughput moved 1,115/sec → 438/sec
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because the formerly fast-failing scenarios are now doing real HNSW
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Add work — that's the honest cost of correctness, not a regression.
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The fix (i.vectors side-store + safeGraphAdd recover wrappers +
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small-index rebuild threshold of 32 + saveTask write coalescing)
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shifts vectord's source-of-truth out of coder/hnsw so panics can't
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lose data and the daemon recovers automatically.
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This is the most production-shape test we've run. The harness mixes
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search, validator calls (in-process), HTTP cross-daemon round-trips,
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playbook recording, and cache exercise. The result is more honest
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than a single-endpoint load test, and post-fix all six workflows
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work cleanly at scale.
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