Organization (company.com)
├── Folder: ML-Production
│   ├── Project: ml-prod-serving    ── 추론 서비스
│   ├── Project: ml-prod-data       ── 데이터 파이프라인
│   └── Project: ml-prod-monitoring ── 모니터링
├── Folder: ML-Development
│   ├── Project: ml-dev-sandbox     ── 실험/PoC
│   └── Project: ml-dev-training    ── 학습 클러스터
└── Folder: Shared-Services
    ├── Project: shared-networking   ── VPC, DNS
    └── Project: shared-security     ── KMS, Secret Manager

from google.cloud import aiplatform

# Vertex AI 초기화
aiplatform.init(
    project="ml-prod-serving",
    location="us-central1",
    staging_bucket="gs://ml-staging-bucket"
)

# 학습 작업 제출
job = aiplatform.CustomTrainingJob(
    display_name="my-training-job",
    script_path="train.py",
    container_uri="us-docker.pkg.dev/vertex-ai/training/pytorch-gpu.2-1:latest",
    requirements=["transformers", "datasets"],
    machine_type="a2-highgpu-1g",
    accelerator_type="NVIDIA_TESLA_A100",
    accelerator_count=1,
)

-- 학습 데이터 피처 집계 예시
SELECT
  user_id,
  COUNT(*) as total_actions,
  AVG(session_duration) as avg_duration,
  APPROX_QUANTILES(response_time, 100)[OFFSET(95)] as p95_latency
FROM `ml-prod-data.analytics.user_events`
WHERE event_date BETWEEN '2025-01-01' AND '2025-12-31'
GROUP BY user_id