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Let machine learning find root cause 10x faster

ML-driven RCA using logs and metrics

 

Use standalone or with existing monitoring and logging. No training. Value in minutes.

 

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Machine learning that finds root cause automatically - video

Slash resolution time by 90%

Zebrium ML-driven RCA uses machine learning to proactively find root cause.

When an incident occurs and you don't know the root cause, Zebrium gives you a root cause report that describes the problem as a summary of relevant log lines and correlated metric anomalies. No more staring at dashboards and hunting through logs. 

Zebrium reduces MTTR vs other approaches

Works with existing tools and processes

Monitoring & APM

If you already use monitoring, APM or other tools to detect software incidents, let Zebrium automatically provide details of root cause.  Zebrium root cause reports can be viewed inside the Zebrium UI or in your incident management tool. 



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Logging & observability

You can continue to use your existing logger for aggregation and search, but let Zebrium find root cause without the need for any manual hunting. And if you use the Elastic Stack, you can see root cause right inside Kibana. 



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Incident management

Zebrium tightly integrates with PagerDuty, Opsgenie, Slack and more to automatically add root cause reports to incidents created by any other tool (e.g. monitoring or help desk software).




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Standalone

When a problem occurs, simply scan the Zebrium incident list (or select the time it occurred) and Zebrium will show you an incident report with details of root cause. You can also use Zebrium as a fully featured log manager with search, filtering, alerting and more.
 

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Take the 30 minute challenge

Try Zebrium by setting up and breaking a microservices demo app.

Detailed step-by-step instructions and video will guide you through the process.

 

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