mo ea3e59cf9c feat: Trino federation + Hadoop external tables + LLM data catalog
Trino Federation tab (3 sub-views):
- Federated: catalog landscape + a single cross-source SQL that joins
  PostgreSQL + MySQL + MongoDB (region scorecard) — the federation proof,
  computed in the background and cached (large full scans take ~2 min).
- Hadoop Lake: all federated business data materialized as external Iceberg
  tables on HDFS (iceberg.hadoop.*_ext, ~120k rows each) with live, fast
  business analytics (revenue by region/channel, top customers, HR by
  department, supply by type, telemetry averages). Includes a one-click
  "rebuild external tables" job.
- Data Dictionary: every business table + column with masked / visible PII
  badges and categories.

Backend trino_federated.py: /catalogs, /marquee(+refresh), /lake,
/materialize(+status), /dictionary. Name-based PII detection flags raw PII
in derived/lake tables as visible vs physically-masked curated layer.

LLM context: platform_context now emits a full BUSINESS DATA CATALOG section
(tables, columns, types, source row counts, federated scorecard) with exact
per-column masked/visible status, so the assistant knows the data in detail
and what is masked vs not.
2026-06-28 18:01:25 +00:00

ATC Command Center

Autonomous agent hub for the Dell ATC lab — Ops Floor UI, FastAPI backend, 5 operator agents.

Quick start

docker compose up -d --build

Open: http://10.0.21.33/

Stack

  • ui — React dashboard + operator sprites (cap + headset)
  • api — FastAPI (status, feed, prompts, WebSocket)
  • redis — live event bus
  • caddy — reverse proxy (:80)

VM 304 (MCP)

  • IP: 10.0.21.33 (DHCP on VLAN 20 / br_20)
  • Proxmox VMID 304 on atc-gpu
  • SSH: root / Dell2026!

Gitea

http://atc-mgt01.dell-atc.lan:3001/mo/atc-agents

ATC Command Center — Gitea layout

This repo follows the same pattern as mo/atc-GPU and mo/Lakehouse.

Repo Path on VM304 Purpose
mo/atc-agents /opt/atc-agents Command Center UI + API + docker-compose
mo/atc-data-quality /opt/atc-data-quality DQ API + RAG API
mo/atc-GPU GPU lab VM303 vLLM, model-manager
mo/Lakehouse lake01 / docker hosts Kafka, Spark, Trino, ObjectScale config

This repo structure

atc-agents/
├── api/                 FastAPI backend
├── ui/                  React dashboard
├── caddy/               Reverse proxy routes
├── config/              Deploy reference (mirrors production)
│   ├── command-center/  docker-compose, Caddyfile, .env.example
│   ├── data-quality/    Link to mo/atc-data-quality
│   └── jupyter/         JupyterLab service snippet
├── docs/                Runbooks
├── scripts/             deploy.sh
└── docker-compose.yml   Production stack (clone with atc-data-quality sibling)

Deploy

git clone http://atc-mgt01.dell-atc.lan:3001/mo/atc-agents.git /opt/atc-agents
git clone http://atc-mgt01.dell-atc.lan:3001/mo/atc-data-quality.git /opt/atc-data-quality
cp config/command-center/.env.example /opt/atc-agents/.env   # edit secrets
./scripts/deploy.sh

Open: http://10.0.21.33/

Services (port 80 via Caddy)

Route Service
/ React UI
/api/* Agents API
/dq/* Data Quality API
/rag/* Knowledge Chat / RAG
/jupyter/* JupyterLab (S3 env preconfigured)
:5001 Docling UI (direct)
S
Description
Kopie van mo/atc-agents (fde-forgejo)
Readme 756 KiB
Languages
Python 49.2%
TypeScript 48.4%
CSS 1.6%
Shell 0.5%
JavaScript 0.1%