Veterans Track · Software Architecture Series

Introduction to AI Architectures

A practical architecture reference for experienced engineers, architects and technical leaders covering ML systems, deep learning, generative AI, MLOps, data engineering and AI infrastructure.

Audience

Architects & Engineers

Coverage

AI · ML · LLM · MLOps

Format

Architecture Compendium

Data

Features

Training

Evaluation

Serving

Monitoring

AI Architecture

ML System Design

End-to-end architecture from data ingestion to production inference

Data Collection & Ingestion

Feature Engineering

Model Training

Evaluation & Validation

Deployment & Serving

Monitoring & Feedback

AI Architecture

Deep Learning Architectures

CNNs, RNNs, Transformers, GANs, VAEs and Diffusion Models

CNN Architecture

RNN / LSTM

Transformer Architecture

GAN

VAE

Diffusion Models

Graph Neural Networks

State Space Models

AI Architecture

LLMs & Generative AI

RAG, fine-tuning, prompt engineering and agentic patterns

RAG Architecture

Vector Databases

LoRA / QLoRA

Prompt Engineering

ReAct Pattern

LLM Evaluation

Agentic AI

AI Architecture

Data Engineering for AI

Lakehouse, feature stores and streaming pipelines

Medallion Architecture

Feature Store Design

Batch vs Stream Processing

Data Quality Checks

Data Lineage

Data Versioning

AI Architecture

MLOps & Model Serving

Model registry, deployment, CI/CD and production monitoring

MLOps Maturity Model

Model Registry

Online Serving

Batch Inference

Drift Detection

Experiment Tracking

AI Architecture

AI Infrastructure

Scalable compute and deployment patterns for AI systems

GPU Clusters

Distributed Training

Kubernetes

Ray / Spark

Inference Optimization

Observability

AI Architecture Pattern Comparison

Common deployment patterns used in production AI systems.

Pattern	Use Case	Latency	Tools
Online Serving	Real-time predictions	Low	Triton, BentoML, TF Serving
Batch Inference	Bulk scoring	Hours	Spark, Ray, Databricks
Streaming Inference	IoT and event streams	Medium	Kafka, Flink, Kinesis
Edge Inference	Mobile and embedded AI	Very Low	TFLite, ONNX, CoreML