Autonomous Incident and Root Cause Detection

Focusing on using ML to catch and characterize incidents faster with zero configuration. Zebrium will look into solving the monitoring space problem of what is happening in productions. We all want to reduce MTTR in a complex environment. Zebrium’s solution will help teams recognize important incidents to focus on by ingesting data.

Zebrium and PagerDuty in this webinar as we explore and demonstrate:

• Current state of monitoring and logging tools
• Machine learning techniques for anomaly detection in logs and metrics
• Deep dive on the Zebrium implementation of multi-layer ML for Incident and root cause detection
• Live demo of the technology showing two use cases:

a) Zebrium ML detects and finds root cause of a problem using logs and metrics
b) A third-party tool detects a problem and Zebrium ML finds the root cause

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