Udemy - LLM Observability and Cost Management - Langfuse, Monitoring

LLM Observability and Cost Management: Langfuse, Monitoring

https://WebToolTip.com

Published 1/2026
Created by Paulo Dichone | Software Engineer, AWS Cloud Practitioner & Instructor
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 28 Lectures ( 2h 35m ) | Size: 1.77 GB

Production-Ready LLM Monitoring with Langfuse, Cost Optimization, Tracing, Alerting & Real-World Debugging Patterns

What you'll learn
✓ Implement production-grade LLM observability using Langfuse and understand tracing concepts
✓ Reduce LLM API costs by 50-80% using semantic caching, model routing, and prompt optimization
✓ Debug LLM applications in minutes using traces, spans, and proper instrumentation patterns
✓ Set up cost alerts and monitoring dashboards that catch budget issues before they escalate
✓ Build production-ready code patterns for token tracking, cost calculation, and PII redaction

Requirements
● Basic Python programming skills (variables, functions, classes)
● Familiarity with LLM APIs (OpenAI, Anthropic, or similar) - you should have made at least a few API calls before
● A code editor (VS Code recommended) and Python 3.9+ installed