In-depth system walkthrough: cloud-native A.I. document processing (app.ilograph.com)

A new in-depth system walkthrough uses Ilograph diagrams to map a cloud-native AI document-processing stack and related architectures. The package documents a serverless back-end deployed on AWS, a containerized distributed load‑testing system on AWS, and an adapted on‑premises Stack Overflow architecture (circa 2016–2019) by Nick Craver. Diagrams call out request dependencies, DNS and network flow, code organization, authentication flows, and operational artifacts such as history, exports, and shareable links — giving a full-picture view of how requests traverse the system and where scaling, security, and failure domains live. For AI/ML teams building document ingestion and processing pipelines, these diagrams are a practical blueprint: they highlight serverless patterns and containerized load testing practices useful for autoscaling, latency management, and cost control, while also surfacing auth and SSO considerations (SAML 2.0 available on paid plans). The walkthrough also doubles as a collaboration case study — Ilograph’s team workspace capabilities (editor/viewer limits, API access, diagram exports, and audit history) make it easier to codify architecture, run distributed tests, and hand off reproducible infrastructure designs to ops or compliance teams.