Integrations & Cost

Published 2026-04-20·Updated 2026-07-13·2 min read

AI documentation guide

Overview

Covers external AWS service integrations and cost analysis. Includes SageMaker-EKS hybrid training and inference patterns, Langfuse, Prometheus, AMP/AMG-based Observability stack deployment, coding tools (Aider, Cline, Cursor) cost analysis, and other platform peripheral integrations.

What This Section Covers

• SageMaker-EKS Integration -- Hybrid architecture patterns combining SageMaker training with EKS inference
• Monitoring Stack Setup -- Langfuse Helm deployment, AMP/AMG, and OTel integration
• Open-Weight Model Deployment Guide -- Self-hosting decisions from token economics and data sovereignty perspectives
• Coding Tools Cost Analysis -- Cost structure comparison of Aider, Cline, and Cursor

Related Documents

• Inference Gateway Deployment -- Gateway infrastructure configured before these integrations
• Model Lifecycle -- Where SageMaker and monitoring integrations fit in training/deployment pipelines
• Agent Monitoring -- Operating the observability stack after deployment

Document List

SageMaker-EKS Integration

A hybrid ML architecture that trains on SageMaker and serves on EKS

Monitoring

Hands-on setup guide for integrated monitoring with Prometheus to AMP, AMG, Langfuse, and Bifrost OTel

Cost & IDE

Aider, Cline, Continue.dev integration + Bedrock vs Kiro vs self-hosting cost comparison

Open-Weight Model Deployment

A customer-facing decision guide for evaluating and choosing self-hosted open-weight LLM deployment from the perspectives of token economics and data sovereignty.