AI-Driven Monitoring: Predictive Analytics: Uses machine learning algorithms to analyze historical data and predict potential failures or performance drops before they happen. This proactive monitoring helps to reduce downtime by addressing issues before they impact business operations. Anomaly Detection: Automatically detects abnormal patterns in system behavior, network traffic, or application performance, alerting administrators to investigate further. This is particularly useful for spotting unusual security activities or system inefficiencies. User Experience Monitoring: Real-User Monitoring (RUM): Tracks how real users interact with websites and applications, measuring response times, load times, and user behavior. This helps businesses improve the end-user experience by pinpointing performance bottlenecks. Synthetic Monitoring: Simulates user transactions, such as logins or purchases, to monitor the availability and performance of web applications. Synthetic tests are useful f