Automatically Identify Root Cause, In Plain English,
Without Digging Through Logs
When critical business services go down, metrics can alert you to the issue, but identifying the root cause requires a time-consuming search through log files.
ScienceLogic Zebrium does this heavy lifting for you, automatically ingesting and analyzing thousands of log files from your applications and infrastructure in real-time—identifying root cause of incidents so you can fix incidents faster.
Diagnose Issues 10x Faster with Automated Root Cause Analysis
When an application breaks, it’s a race against time to fix. Customers are frustrated, and critical resources are pulled from other work. ScienceLogic Zebrium eliminates much of the manual work required to diagnose root cause.
- Use machine learning (ML) on log files in real-time to identify root cause
- Dramatically reduce time to know what is actually broken
- No manual model training required – unsupervised ML produces results in less than 24 hours
Identify Unknown Problems or Anomalies Before They Cause Incidents
The complexity of modern applications makes it challenging for any person to know what could break at any given time.
- Identify unusual or novel issues and associated root cause, even when you or your monitoring tool don’t know what to look for or expect
- Correlate unusual behavior with recent changes and performance metrics so you can understand potential business or service impact.
Understand What is Happening, Even if You Don’t Speak Log
Because no two logs are alike, looking through logs is like deciphering a foreign language–even for experienced developers. Some words may look familiar, but each log has its own unique vocabulary and syntax.
- Distill billions of log lines down to the few most salient to isolate root cause
- Get plain English root cause summaries based on natural language model
- See the most important keywords from logs that describe the root cause
See Zebrium Insights Wherever You Work
Customer Success Stories
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