docs(infra): correct server specs — Hetzner Serverbörse i7-6700 64 GB, not CX32

Replace all references to the CX32 VPS (8 GB RAM, Hetzner Cloud) with the
actual production server: a Hetzner Serverbörse dedicated server with an
Intel Core i7-6700 (4C/8T, 3.4 GHz) and 64 GB RAM.

Affected files:
- .claude/personas/devops.md — monthly cost line + upgrade example
- docs/infrastructure/production-compose.md — sizing section + cost table
- docs/DEPLOYMENT.md — OCR memory table + OCR_MEM_LIMIT env var description
- docs/adr/004-pdfbox-thumbnails.md — thumbnailExecutor memory ceiling note
- docs/adr/021-tmpdir-persistent-volume-staging.md — OOMKill rationale in alternatives

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

docs/DEPLOYMENT.md

@@ -52,11 +52,12 @@ The OCR service requires significant RAM for model loading. The dev compose sets
 
 | Production target | RAM | Recommended OCR limit | Notes |
 |---|---|---|---|
-| Hetzner CX42 | 16 GB | 12 GB | Recommended for OCR-enabled production |
-| Hetzner CX32 | 8 GB | 6 GB | Accept reduced batch sizes and slower throughput |
-| Hetzner CX22 | 4 GB | — | Disable the OCR service (`profiles: [ocr]`); run OCR on demand only |
+| Current server (Hetzner Serverbörse, i7-6700) | 64 GB | 12 GB | Default `mem_limit: 12g` works comfortably |
+| ≥ 16 GB RAM | 16+ GB | 12 GB | Default works |
+| 8 GB RAM | 8 GB | 6 GB | Set `OCR_MEM_LIMIT=6g`; accept reduced batch sizes |
+| 4 GB RAM | 4 GB | — | Disable OCR service (`profiles: [ocr]`); run OCR on demand only |
 
-A CX32 cannot honour the default `mem_limit: 12g` — set the `OCR_MEM_LIMIT=6g` env var (in `.env.production` / `.env.staging`, or as a Gitea secret consumed by the workflow) before deploying on a CX32. The prod compose interpolates this var with a 12g default.
+On servers with less than 16 GB RAM the default `mem_limit: 12g` cannot be honoured — set the `OCR_MEM_LIMIT` env var (in `.env.production` / `.env.staging`, or as a Gitea secret consumed by the workflow). The prod compose interpolates this var with a 12g default.
 
 ### Dev vs production differences
 
@@ -140,7 +141,7 @@ All vars are set in `.env` at the repo root (copy from `.env.example`). The back
 | `ALLOWED_PDF_HOSTS` | SSRF protection — comma-separated list of allowed PDF source hosts. **Do not widen to `*`** | `minio,localhost,127.0.0.1` | YES | — |
 | `KRAKEN_MODEL_PATH` | Directory containing Kraken HTR models (populated by `download-kraken-models.sh`) | `/app/models/` | — | — |
 | `BLLA_MODEL_PATH` | Kraken baseline layout analysis model path | `/app/models/blla.mlmodel` | — | — |
-| `OCR_MEM_LIMIT` | Container memory cap for ocr-service in `docker-compose.prod.yml`. Set to `6g` on CX32 hosts; leave unset on CX42+ to use the 12g default | `12g` (prod compose default) | — | — |
+| `OCR_MEM_LIMIT` | Container memory cap for ocr-service in `docker-compose.prod.yml`. Set to `6g` on servers with 8 GB RAM; leave unset (12g default) on servers with ≥ 16 GB RAM | `12g` (prod compose default) | — | — |
 | `XDG_CACHE_HOME` | XDG cache base dir — redirects Matplotlib and other XDG-aware libraries away from the read-only `HOME` (`/home/ocr`) to the writable cache volume | `/app/cache` | — | — |
 | `TORCH_HOME` | PyTorch model cache — redirects `~/.cache/torch` to the writable models volume | `/app/models/torch` | — | — |