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Udemy - LLM Observability and Cost Management - Langfuse, Monitoring

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Udemy - LLM Observability and Cost Management - Langfuse, Monitoring (Size: 1.8 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Introduction
  1. Introduction.mp4 19.2 MB
  2 - The Business Case Why Observability = Money
  1. Section 2 Business Case for LLM Observability (Description).html 921.6 B
  1. Section 2 Business Case for LLM Observability.html 16.4 KB
  3 - Understanding LLM Costs - Where Your Money Goes
  10. The Hidden Cost Multiplier.mp4 27.1 MB
  2. Section 3 Understanding LLM Costs (Description).html 819.2 B
  2. Section 3 Understanding LLM Costs.html 18.4 KB
  4 - Observability Platform Selection - Langfuse and Hands-on
  11. Observability Platform Selection.mp4 15.2 MB
  12. Setting Up Langfuse.mp4 65.2 MB
  13. Setting up Langfuse and Creating First Trace.mp4 52.5 MB
  13. langf-obs py.py 614.4 B
  14. Langfuse Data Model.mp4 42.3 MB
  15. Hands-on First LLM Trace - Deep Dive.mp4 53.2 MB
  15. first-trace-llm py.py 512 B
  16. Langfuse API Levels - Code Demonstrations.mp4 116.1 MB
  16. decorator-trace-llm py.py 1.7 KB
  3. Section 4 Observability Platform Selection - Langfuse and Hands-on.html 18.2 KB
  5 - Instrumenting Your LLM Application
  17. Production Instrumented LLM Use Case - Hands-on.mp4 220.2 MB
  17. instrumented-llm py.py 5.2 KB
  18. Instrumenting a Multi-Step RAG Pipeline - Langfuse Observability - Full Handson.mp4 406 MB
  18. rag-pipeline-obs py.py 7.1 KB
  19. Framework Integration LangChain.mp4 159.2 MB
  19. instrumentation-langchain py.py 921.6 B
  6 - Cost Optimization Strategies That Work
  20. Cost Optimization Strategies - Overview.mp4 32.6 MB
  21. Prompt Optimization - Handson.mp4 23.5 MB
  21. prompt-optimazation py.py 921.6 B
  22. Semantic Caching.mp4 129.2 MB
  22. semantic-cache py.py 9.3 KB
  23. Smart Model Routing.mp4 86 MB
  23. model-routing py.py 4.4 KB
  24. Cost Optimization Summary.mp4 7.4 MB
  7 - Monitoring, Alerting Debugging
  25. A-webhook-site-for-simulation.url 0 B
  25. Setting up Alerts that Matter.mp4 70.6 MB
  25. alert-webhook py.py 1.9 KB
  8 - Production Patterns Security
  26. Security and Compliance Patterns.mp4 66.4 MB
  26. pii-redaction py.py 2.7 KB
  27. Production Patterns Implementations - Real-world.mp4 4.8 MB
  9 - Wrap up and Next Steps
  28. Course Recap and Next Steps.mp4 9.5 MB
  8. Understanding LLM Costs.mp4 131.9 MB
  9. Where Costs Hide - RAG and Agent Pipeline.mp4 23 MB
  3. Observability and Cost Management - Overview.mp4 11.2 MB
  4. The Hidden Costs of LLM Applications.mp4 9.6 MB
  5. Traditional vs LLM Observability.mp4 9 MB
  6. The Three Pillars for LLMs.mp4 6.7 MB
  7. ROI Calculator - Making the Business Case.mp4 12.5 MB
  2. Get Course Code.html 5.7 KB

Description


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

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