AI-driven analytics for predictive observability
Using AI and machine learning in today’s dynamic cloud environments provides advantages over traditional monitoring tools due to the scalability and complexity of modern applications. They facilitate the analysis of historical and real-time data to forecast potential issues before they affect the application or system. This proactive approach is called predictive observability.
In this section, we discuss the capabilities of Azure Monitor to provide predictive observability and how tools such as Microsoft Copilot for Azure bring a new level of automation and intelligence to observability, helping organizations manage their cloud environments more effectively.
The components required for AI-driven analytics with Azure Monitor are as follows:
- Data collection and aggregation: Predictive observability begins with comprehensive data collection from multiple sources, including logs, metrics, traces, and events from across...
