GuideAdvanced
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
- English · Spanish
- available in
- Yes
- certificate
- Free
- access
Outcomes
What you'll be able to do
- 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
Before you start
What you need to bring
It's for you if...
- 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
Requirements and materials
- 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
Content
The syllabus, module by module
Open any of them to see its lessons.
Where it fits
This guide is part of something bigger
It's studied inside these programs, with support and dates.
Common questions
What people usually ask
No limit. It's a free guide: come in whenever you like, as often as you like.
No. Modules run from easier to harder, but you can jump to the one you need. Progress is saved per lesson.
Whatever is needed is listed under “What you need to bring”, above. If nothing is listed there, you can start from zero.
In the Club's WhatsApp group, and every two weeks there's a live with an instructor where questions get worked through.
Yes. It's issued automatically once you finish every lesson, with a verifiable code you can share on LinkedIn.
No. This guide is self-paced with no dates. The bootcamp is live, by cohort, with work someone reviews.
Start whenever you like
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