Build Reliable Systems with Chaos Engineering - MLOps Podcast #237

Explore the world of Chaos Engineering in this 47-minute podcast episode featuring Benjamin Wilms, CEO & Co-Founder of Steadybit. Dive into the concept of building reliable systems under unpredictable conditions, understanding how Chaos Engineering can benefit both large corporations and smaller startups. Learn about the emerging trend of Data Chaos Engineering, its comparison to ML Resilience, and how it can be integrated into machine learning systems. Discover the importance of testing system vulnerabilities, addressing data distribution issues across time zones, and the value of expertise in fixing complex systems. Gain insights on implementing Chaos Engineering in pre-CI/CD steps, automating experiments for deployments, and the significance of strong integration with observability tools for repeatable experiments. This comprehensive discussion covers everything from the basics of Chaos Engineering to its practical applications in modern software development and MLOps practices.

[] Benjamin's preferred coffee
[] Takeaways
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[] Chaos Engineering tldr
[] Complex Systems for smaller Startups
[] Chaos Engineering benefits
[] Data Chaos Engineering trend
[] Chaos Engineering vs ML Resilience
[17:57 - ] AWS Trainium and AWS Inferentia Ad
[] Chaos engineering tests system vulnerabilities and solutions
[] Data distribution issues across different time zones
[] Expertise is essential in fixing systems
[] Chaos engineering integrated into machine learning systems
[] Pre-CI/CD steps and automating experiments for deployments
[] Chaos engineering emphasizes tool over value
[] Strong integration into observability tools for repeatable experiments
[] Invaluable insights on chaos engineering
[] Wrap up