EAAPLEnterprise AI Architecture Pattern Library

Pattern Library

Enterprise AI Architecture Patterns

117 patterns across 13 architecture domains. Filter by category, maturity, or regulatory framework.

8 patterns(1 filter active)
Observability & MonitoringProven

EAAPL-OBS001 · AI Telemetry Architecture

AI systems present unique observability challenges that traditional APM tooling does not…

Observability & MonitoringProven

EAAPL-OBS002 · Prompt Monitoring

Prompts sent to large language models in production are the primary control…

Observability & MonitoringProven

EAAPL-OBS003 · Hallucination Detection

Large language models fabricate plausible-sounding content with confidence.

Observability & MonitoringProven

EAAPL-OBS004 · AI Incident Management

AI system failures are qualitatively different from traditional software failures.

Observability & MonitoringProven

EAAPL-OBS005 · Model Drift Detection

AI models degrade silently.

Observability & MonitoringProven

EAAPL-OBS006 · AI Cost Observability

AI inference costs have a fundamentally different cost structure than traditional compute:…

Observability & MonitoringProven

EAAPL-OBS007 · Distributed AI Tracing

AI pipelines are not single API calls.

Observability & MonitoringProven

EAAPL-OBS008 · AI Performance Benchmarking

AI system quality degrades silently between benchmarking events.