Data-intensive applications have attracted considerable attention in recent years. Business organizations are increasingly becoming data-driven and therefore look for novel ways to collect, analyze, and leverage the data at their disposal. The goal of this chapter is to overview some recurring performance management activities for data-intensive applications, examining the role that artificial intelligence (AI) and machine learning are playing in enhancing practices related, among others, to configuration optimization, performance anomaly detection, load forecasting, and auto-scaling for these software systems.
Alnafessah, A., Russo Russo, G., Cardellini, V., Casale, G., Lo Presti, F. (2021). AI‐Driven Performance Management in Data‐Intensive Applications. In N. Zincir-Heywood, M. Mellia, Y. Diao (a cura di), Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning (pp. 199-222). Wiley [10.1002/9781119675525.ch9].
AI‐Driven Performance Management in Data‐Intensive Applications
Russo Russo, Gabriele;Cardellini, Valeria;Lo Presti, Francesco
2021-09-01
Abstract
Data-intensive applications have attracted considerable attention in recent years. Business organizations are increasingly becoming data-driven and therefore look for novel ways to collect, analyze, and leverage the data at their disposal. The goal of this chapter is to overview some recurring performance management activities for data-intensive applications, examining the role that artificial intelligence (AI) and machine learning are playing in enhancing practices related, among others, to configuration optimization, performance anomaly detection, load forecasting, and auto-scaling for these software systems.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
