The author suggests a three-step process to achieve true predictability through observability. First, identify which elements of the enterprise should not be observed to reduce noise. Second, determine what does need to be observed and use historical datasets to configure observability platforms effectively. Finally, identify and address the root causes behind negative trends and behaviors. The author concludes that a careful transition from monitoring to observing can empower organizations to leverage AI in their IT services and ensure business performance.
Key takeaways:
- The concept of "observability" in IT services is gaining traction, but its actual adoption is questionable compared to its promise of building predictable IT services.
- Transitioning from a monitoring approach to an observational one involves moving away from reliance on alerts and thresholds and instead focusing on metrics, trends, and behaviors.
- For successful observability, it is necessary to identify which elements of the enterprise should be observed, determine what needs to be observed, and have the ability to identify the root causes behind negative trends and behaviors.
- The shift from monitoring to observing can empower organizations to leverage AI in the delivery of their IT services and help guarantee business performance.