John Feminella, Nuvalence
Observability has always been a cornerstone for understanding and maintaining complex digital systems. Our familiar friends of metrics, logs, and traces have been enriched over the years with more powerful tools for greater understanding. Now, a new emerging superpower for practitioners has been added to that toolbox: generative AI.
In this talk, we'll cover several new generative AI patterns of interest that we've found to be of particular relevance to observability practitioners in production settings. We'll show how even relatively basic generative AI scaffolding can be extraordinarily helpful for practitioners, how to leverage this in your day-to-day work, and how to get started right now. By the end of the talk, we hope to leave you with a mix of practical advice and solid theoretical grounding.
John Feminella, Nuvalence
John Feminella is a technology leader, occasional public speaker, and curiosity advocate. At Nuvalence, he helps enterprises transform the way they write, operate, and deploy software and organize software organizations so that businesses and people alike can be more effective. Before that, he led technology organizations at Pivotal, VMware, and ThoughtWorks; helped build the world's largest database of pollutants and air emissions; authored a distributed-sensor technology; and helped design FedNow, an instant-payments network.
author = {John Feminella},
title = {Using Generative {AI} Patterns for Better Observability},
year = {2024},
address = {San Francisco, CA},
publisher = {USENIX Association},
month = mar
}