DOCS: comprehensive benchmark results from full perf test suite

Ran Go benchmarks (3x count) across api, crawler, item model, and web
middleware packages. Also ran frontend-vanilla perf tests. Documented
findings including stream allocation overhead, image proxy cost, and
middleware latency. Added potential improvement recommendations.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

1 files changed, 99 insertions, 0 deletions

diff --git a/DOCS/benchmarks.md b/DOCS/benchmarks.md
index 78b024a..56e903a 100644
--- a/DOCS/benchmarks.md
+++ b/DOCS/benchmarks.md
@@ -19,3 +19,102 @@ The `make check` workflow consists of:
 4. `npm test -- --run` (Frontend)
 
 The goal of keeping the check under 15 seconds for a fast local feedback loop has been achieved.
+
+---
+
+## Go Backend Benchmarks
+
+**Environment:** Linux arm64, Go, SQLite
+**Date:** 2026-02-16
+**Methodology:** `go test -bench=. -benchmem -count=3`
+
+### API Handlers (`api/`)
+
+| Benchmark | ops | ns/op | B/op | allocs/op |
+|---|---|---|---|---|
+| HandleStream | 6,664 | 168,344 | 380,350 | 1,423 |
+| HandleStreamWithSearch | 6,200 | 192,454 | 381,033 | 1,432 |
+| HandleItemUpdate | 24,469 | 48,513 | 8,597 | 46 |
+| HandleFeedList | 51,320 | 22,846 | 10,308 | 117 |
+
+**Findings:** Stream endpoints (~170us) are dominated by SQLite query + JSON serialization. Search adds ~14% overhead via FTS. Item updates and feed listing are fast (~48us and ~23us respectively). The ~380KB/op allocation for stream is from serializing item content; this could be reduced by excluding `full_content` in list views.
+
+### Crawler (`internal/crawler/`)
+
+| Benchmark | ops | ns/op | B/op | allocs/op |
+|---|---|---|---|---|
+| ParseFeed | 12,157 | 98,513 | 92,216 | 1,643 |
+| CrawlFeedMocked | 1,497 | 782,713 | 169,491 | 2,233 |
+| GetFeedContent | 9,720 | 122,448 | 46,986 | 190 |
+
+**Findings:** Feed parsing (~98us) is fast. Full crawl cycle (~783us mocked) is dominated by HTTP round-trip + DB write. Content fetching (~122us) includes HTTP + HTML sanitization.
+
+### Item Model (`models/item/`)
+
+| Benchmark | ops | ns/op | B/op | allocs/op |
+|---|---|---|---|---|
+| ItemCreate | 21,397 | 55,924 | 1,415 | 22 |
+| ItemCreateBatch100 | 216 | 5,574,677 | 139,213 | 2,100 |
+| Filter_Empty | 62,834 | 19,005 | 13,096 | 82 |
+| Filter_15Items | 7,429 | 159,417 | 373,392 | 1,771 |
+| Filter_WithFTS | 6,406 | 184,237 | 374,120 | 1,779 |
+| Filter_WithImageProxy | 5,348 | 216,287 | 496,533 | 2,491 |
+| FilterPolicy | 104,919 | 11,444 | 17,768 | 150 |
+| RewriteImages | 182,242 | 6,453 | 11,048 | 97 |
+| ItemSave | 28,552 | 41,641 | 592 | 11 |
+| Filter_LargeDataset | 8,623 | 139,067 | 361,769 | 1,186 |
+
+**Findings:** Image proxy adds ~35% overhead to filtering (216us vs 159us) due to URL rewriting of `<img>` tags. Batch inserts scale linearly (~56us/item). The `FilterPolicy` HTML sanitizer is fast at ~11us. Full-text search adds minimal overhead (~15%) to filtering.
+
+### Web Middleware (`web/`)
+
+| Benchmark | ops | ns/op | B/op | allocs/op |
+|---|---|---|---|---|
+| GzipMiddleware | 100,623 | 11,881 | 11,999 | 25 |
+| SecurityHeaders | 484,862 | 2,402 | 6,185 | 22 |
+| CSRFMiddleware | 495,804 | 2,395 | 6,028 | 23 |
+| FullMiddlewareStack | 362,329 | 3,237 | 8,745 | 34 |
+
+**Findings:** The full middleware stack adds only ~3.2us per request. Gzip compression is the most expensive middleware (~12us) due to compression work, but is only applied to compressible responses. CSRF and security headers are near-zero cost (~2.4us each).
+
+---
+
+## Frontend Performance Tests (Vanilla JS / v3)
+
+**Environment:** Vitest + jsdom
+**Date:** 2026-02-16
+
+### Store Operations
+
+| Test | Threshold | Status |
+|---|---|---|
+| setItems (500 items + event dispatch) | < 10ms | PASS |
+| setItems append (500 to existing 500) | < 10ms | PASS |
+| setFeeds (200 feeds) | < 5ms | PASS |
+| Rapid filter changes (100 toggles) | < 50ms | PASS |
+| Rapid search query changes (100) | < 50ms | PASS |
+| 50 listeners on items-updated | < 10ms | PASS |
+
+### Rendering
+
+| Test | Threshold | Status |
+|---|---|---|
+| createFeedItem (100 items) | < 50ms | PASS |
+| createFeedItem (500 items) | < 200ms | PASS |
+| createFeedItem (1000 items) | < 100ms | PASS |
+| DOM insertion (100 items) | < 200ms | PASS |
+| DOM insertion (500 items) | < 500ms | PASS |
+
+**Findings:** All frontend performance tests pass well within their thresholds. The vanilla JS approach with direct DOM manipulation and simple event emitter pattern keeps operations fast. Store updates with 500+ items and event dispatch remain under 10ms.
+
+---
+
+## Potential Improvements
+
+1. **Stream endpoint allocations**: The ~380KB/op for stream could be reduced by excluding `full_content` from list views and only fetching it on demand (already partially implemented via the scrape endpoint).
+
+2. **Image proxy overhead**: The 35% filtering overhead from image rewriting could be cached or deferred to the client side.
+
+3. **Batch operations**: The item batch insert benchmark shows good linear scaling; could be leveraged for bulk import operations.
+
+4. **Gzip middleware**: At ~12us, it's the most expensive middleware. Consider pre-compressing static assets and only applying runtime gzip to API responses.