Agentic AI Platform Architecture
Overall system architecture of a production-grade Agentic AI Platform — 6 runtime layers and 3 cross-cutting planes
Overall system architecture of a production-grade Agentic AI Platform — 6 runtime layers and 3 cross-cutting planes
EKS-based 5-stage pipeline that automatically promotes Langfuse traces to training data and connects GRPO/DPO preference tuning with Canary deployment.
End-to-end ML lifecycle management with Kubeflow + MLflow + vLLM + ArgoCD GitOps
Custom model deployment, fine-tuning pipelines, MLOps orchestration, continuous training pipelines
AI platform monitoring, observability, evaluation, compliance, and domain-specific operations guide
A hybrid ML architecture that trains on SageMaker and serves on EKS
HuggingFace 리더보드 스캔부터 벤치마크 재현, 인스턴스별 성능 프로파일링, 멀티 타깃 배포 가이드 생성, 글로벌 스팟 캐파 확보까지 — 오픈 웨이트 모델 온보딩을 7단계 파이프라인으로 자동화하고 사람은 승인 게이트에만 개입하는 아키텍처를 제시합니다