Sick of building and maintaining alert rules as new failure modes are discovered? Let our machine learning catch your software incidents without any manual work. It works by finding hotspots of abnormally correlated log and metric anomalies and achieves reliable and accurate detection within an hour of first use.
Today, the best DevOps teams have automated everything. But tracking down root cause is still manual, causing Mean-Time-To-Resolution to get worse as software complexity grows. Zebrium changes this by using machine learning to uncover the root cause. This means faster MTTR and less hunting for root cause!
Zebrium is integrated with PagerDuty and Slack and and can augment any type of incident detection tool (e.g. existing monitoring, APM, logger, help desk, etc.).
So, next time dinner is interrupted by an alert from your incident response tool, just relax! Zebrium can instantly show you the relevant log lines and metric charts that describe root cause without any work. No more missed dinners hunting through logs and charts.
Cutting MTTR doesn’t just mean happier users – it also saves precious SRE, DevOps and developer hours currently spent chasing down incidents and hunting for root cause. On top of that, our customers typically save 30-50% in logging/monitoring software costs by switching to us. Cost efficiency comes from our underlying relational structure that achieves higher efficiency for retention and queries compared with traditional text search based logging tools.