AI Powered Log Management, Monitoring & Observability

Zebrium uses machine learning to automatically catch software problems and show you root cause.

And it's also a full-blown log management and monitoring platform.

Two minute Zebrium video

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We Catch Problems and their Root Cause

Autonomous monitoring uses machine learning to catch incidents and show you root cause. No more staring at dashboards and hunting for root cause.

It works with any app - all you have to do is install a lightweight log and metric collector. You never have to define a manual alert rule again.

 

how zebrium works

Incident Detection and Characterization

Autonomously Detected Incident

With zero human effort (no config, no alert rules, no pre-training, etc.), Zebrium automatically finds incidents in you logs and metrics (see How it Works for more details).

Each incident is presented as a clear set of events and charts showing root cause and symptoms.

Click here for  detailed examples of Zebrium detected incidents

Augment Incidents Created by Other Tools

If you already have other tools (e.g. Incident Management system, monitoring, observability, APM, etc.), Zebrium can help in two ways:

  • Zebrium's ML-driven autonomous incident detection can catch the long tail tail of unknown issues that other tools miss.
  • Zebrium can take an existing incident that is generated by another tool, and augment it with details of root cause

To learn more see How it Works.

Zebrium works augments incidents with root cause even when detected by 3rd party

How Zebrium Compares to Other Log Management and Monitoring Tools

The Evolution of Observability Tools

The evolution of observability tools

 

Logging, metrics and observability tools were built around aggregation, dashboarding, search and rule-based alerts. Some have evolved to include anomaly detection (outlier detection) - mostly in metrics. This kind of anomaly detection can be  useful when drilling-down on a problem, but it tends to suffer from too many false positives.

Zebrium detects anomalies in logs and metrics but also uses a layered machine learning approach to find hotspots of abnormally correlated anomalous patterns. This results in extremely accurate "Incident Recognition" - the ability to detect unknown incidents and characterize their root cause. 

And Zebrium is also a full-blown log management and monitoring platform with all the features you'd expect.

Log Management and Monitoring

Remember - Zebrium's ML Incident and Root Cause detection automatically finds what you previously needed to search for!  But, if you need it, the platform also offer rich functionality to get more context on an incident or to drill-down into your logs and metrics.

For logs: we provide an aggregated explorer with full regex search, filtering, one-click charting, drill down, alerting and more. It's designed specifically for Developers and DevOps.

For metrics:  easily select and chart any metric with a click and easily view correlations across different time-series. We also include full Grafana functionality  for dashboarding directly within the UI.

log explorer

 

chart metrics and see correlations

 

 

security

Security

We adhere to industry best practices for security including: encryption of data in flight,  AES-256 encryption of data at rest, granular removal of sensitive records or fields, secure isolation of customer data and an option for a dedicated instance and VPC. All customer data will be deleted upon termination of service or by request. Read our security policy here.

Supported Platforms

kubernetes linux docer ECS syslog cloudwatch

VMware, Windows and more coming soon.

Getting Started is Free and Easy

Spend just two minutes of your time and you'll be amazed at what we detect!

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