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William Cappelli
William Cappelli

Willam Cappelli is an Observability Strategist at Splunk. Widely recognised as a key interpreter and shaper of software market and technology trends, William wrote the first papers defining AIOps, APM, and DEM while serving as a VP of Research at Gartner and then, as a CTO at Moogsoft developed the broadly accepted five dimensional model for AIOps. In his spare time, he studies and translates Dharma language texts.

DevOps 4 Min Read

Observability and Machine Learning [Part 1]

Let's take a look at the general relationship between Observability and ML and how ML can aid in the conversion of raw telemetry into genuine signals of events or state changes.
DevOps 6 Min Read

Observability and Telecommunications Network Management [Part 1]

When considering the management of telecommunications networks, it might make sense to directly consider the observable data streams available to the practitioner instead of a model-based approach. Learn more in this blog.
DevOps 5 Min Read

The Importance of Traces for Modern APM [Part 2]

In the second part of this blog we will explore how increased entropy forces us to rethink what is required for monitoring.
DevOps 6 Min Read

Observability Shifts Right

Observability first emerged as a focal point of interest in the DevOps community in the 2017 time-frame. Aware that business was demanding highly adaptable digital environments, DevOps professionals realised that high adaptability required a new approach to IT architecture.
DevOps 5 Min Read

Observability for Sustainability

For the past 20 years, the various stakeholder communities that together constitute the IT industry have attempted to address sustainability. Could observability help in practicing sustainable IT and improving the carbon footprint reduction in its operations?
DevOps 5 Min Read

Correlation Does Not Equal Causation - Especially When It Comes to Observability [Part 1]

Observability has been tied up with causality from its origins in the mathematical realm of control theory in the early 1960s. But what precisely does the term ‘causality’ denote? In how does correlation come into play when it comes to observability? Read on to find out more.