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Predicting and Preventing System Outages - Chaos Engineering 2025

Conf42 via YouTube

Overview

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This conference talk from Conf42 Chaos Engineering 2025 explores how to predict and prevent system outages using chaos engineering principles in AI systems. Learn about the history and evolution of chaos engineering, understand AI system architecture and potential failure points, and discover how to design effective chaos experiments specifically for AI environments. Explore practical techniques including adversarial attacks, GPU failure simulations, data pipeline latency testing, corruption simulations, and model drift testing. Gain insights into implementing chaos engineering principles in organizations, the tools available, and the challenges and future directions of this discipline in AI contexts. The 30-minute presentation provides a comprehensive framework for making AI systems more resilient through controlled failure testing and proactive outage prevention strategies.

Syllabus

00:00 Introduction to Chaos Engineering in AI
01:51 What is Chaos Engineering?
02:16 History and Evolution of Chaos Engineering
04:12 AI System Architecture and Potential Failures
06:53 Chaos Engineering in AI Context
08:14 Designing Chaos Experiments for AI
10:34 Making AI Systems Stronger Through Chaos
11:33 Adversarial Attacks and GPU Failure Simulations
14:28 Data Pipeline Latency and Corruption Simulations
18:07 Model Drift and Fallback Testing
20:16 Chaos Engineering Principles and Tools
24:00 Implementing Chaos Engineering in Organizations
25:35 Challenges and Future of Chaos Engineering in AI
27:48 Key Takeaways and Conclusion

Taught by

Conf42

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