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Monitoring & Observability Guide

Master the observability of AI systems in production with OpenTelemetry, the industry standard for 2026. Learn to instrument LLM applications with traces for prompts, embeddings, and tool calls, build dashboards for latency and cost, design alerting strategies, implement AI-specific monitoring (prompt quality, token usage, model drift), and debug production issues like hallucinations and cost spikes. Integrates with LangSmith and monitoring backends.

64

Lessons

8

Modules

🎓

Bootcamp access

Lo que aprenderás

✓Understand observability for AI systems vs generic monitoring (logs, metrics, traces)
✓Instrument key metrics: latency (TTFT, TTI), cost (tokens, USD/request), errors, output quality
✓Set up OpenTelemetry and trace prompts, embeddings, and tool calls (industry standard 2026)
✓Build dashboards for AI operations (latency percentiles, cost trends, error breakdown)
✓Design alerting strategies for AI (cost spikes, latency SLO breaches, error rate)
✓Implement AI-specific monitoring: prompt quality, token usage, model drift, hallucination detection
✓Integrate LangSmith with OpenTelemetry for LLM flow debugging
✓Debug production AI issues: hallucinations, cost spikes, latency with runbooks and trace analysis

¿Para quién es?

  • •AI Engineers with deployed systems who need to observe, monitor, and debug in production
  • •Backend developers operating AI APIs who need dashboards and alerts for SLA
  • •Tech leads preparing AI systems to scale with visibility into cost, latency, and quality
  • •Teams adopting OpenTelemetry as the instrumentation standard for AI systems
  • •Developers who want to differentiate with production-grade AI observability skills

Requisitos

  • •Production Best Practices Guide (#13) — testing, guardrails, structured logging
  • •Docker Essentials (#15) — containerization
  • •Deployment & Cloud Infrastructure (#17) — deployed AI systems (local, cloud, or serverless)
  • •Python intermediate, FastAPI or equivalent
  • •At least one AI system running in production or near-production staging

Course content

1Módulo 1: Observability para AI Systems — Guía para el Creador8 lessons
2Módulo 2: Métricas Clave para AI — Guía para el Creador8 lessons
3Módulo 3: OpenTelemetry Setup e Instrumentación — Guía para el Creador8 lessons
4Módulo 4: Dashboards y Visualización — Guía para el Creador8 lessons
5Módulo 5: Estrategias de Alerting — Guía para el Creador8 lessons
6Módulo 6: Monitoring AI-Específico — Guía para el Creador8 lessons
7Módulo 7: Debugging Production AI Issues — Guía para el Creador8 lessons
8Módulo 8: Proyecto Integrador — Observability Stack — Guía para el Creador8 lessons
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