Screaming in the Cloud
Shifting from Observability 1.0 to 2.0 with Charity Majors
Apr 2, 2024
CTO and Co-founder of Honeycomb.io, Charity Majors, discusses shifting from Observability 1.0 to 2.0 with Corey. They cover the hidden costs of observability, the impact of AI in computing, and simplifying observability for developers. They also explore the evolution of observability tools, the challenges of managing rising costs in Kubernetes, and embracing AI for troubleshooting in complex distributed systems.
33:00
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Quick takeaways
- Transitioning to observability 2.0 centralizes data for efficient system debugging and insights.
- Balancing metrics and logs in observability tools is critical to manage costs and extract meaningful insights.
Deep dives
Observability 1.0 vs. Observability 2.0
The shift from observability 1.0 to 2.0 focuses on moving from a world of multiple sources of truth to a centralized source of truth. In observability 1.0, systems are held in your head, leading to difficulties in correlation and understanding. Conversely, observability 2.0 emphasizes structured data blobs where metrics, traces, and logs are derived, allowing easy slicing and dicing for insights. By transitioning to a single source of truth, users can experience enhanced value and more efficient system debugging.
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