Agentic AI Platform Architecture
Overall system architecture of a production-grade Agentic AI Platform — 6 runtime layers and 3 cross-cutting planes
7 docs tagged with "mlops"
View all tagsAutomated Deployment and Management Pipeline Architecture for Open-Weight Models
An architecture that automates open-weight model onboarding through a seven-stage pipeline, from HuggingFace leaderboard scanning and benchmark reproduction to instance performance profiling, deployment guide generation for multiple targets, and global Spot capacity acquisition, with human involvement at approval gates
Continuous Training Pipeline
EKS-based 5-stage pipeline that automatically promotes Langfuse traces to training data and connects GRPO/DPO preference tuning with Canary deployment.
MLOps Pipeline on EKS
End-to-end ML lifecycle management with Kubeflow + MLflow + vLLM + ArgoCD GitOps
Model Lifecycle
Custom model deployment, fine-tuning pipelines, MLOps orchestration, continuous training pipelines
Operations & Governance
AI platform monitoring, observability, evaluation, compliance, and domain-specific operations guide
SageMaker-EKS Hybrid ML Architecture
A hybrid ML architecture that trains on SageMaker and serves on EKS