The move towards cloud and microservices has caused an explosion in the number of possible software failure modes. Traditional rules-based monitoring suffers from alert fatigue while trying to catch the long tail of “unknown” issues that keep cropping up. It also fails to identify root cause for problems it detects, impacting Mean-Time-To-Resolution (MTTR) while precious engineering hours are lost hunting through logs and dashboards.
Zebrium’s vision is to drive down MTTR and the troubleshooting burden on engineering teams by delivering an autonomous incident and root cause detection platform that applies unsupervised machine learning to real-time streams of logs and metrics.
Existing tools use fragile human-built rules to detect incidents. If an incident occurs that doesn't have a rule, you won't be alerted. And if a rule is too general you will get over-alerted. Zebrium takes away this pain by using unsupervised machine learning to autonomously detect incidents.
Incident resolution can be painful. Customers anxiously wait as key employees spend countless hours pouring over logs, dashboards and traces trying to figure out what went wrong. Zebrium minimizes downtime by automatically identifying and taking you straight to root cause.
The Zebrium platform does not require pre-learning, manual configuration or human-built rules. All that's needed are your existing logs. Getting started takes less than 2 minutes.
Too good to be true? Try it now.
Ajay is a strong advocate for creating products that "just work" to address real-life customer needs. As Zebrium CEO, he is passionate about building a world class team focused on using machine learning to build a new kind of log monitoring platform. Ajay led Product at Nimble Storage from concept to annual revenue of $500M and over 10,000 enterprise customers. Ajay started his career as an engineer and has also held senior product management roles at NetApp and Logitech.
Larry is the founder and CTO of Zebrium. He started Zebrium with the vision that machine learning could be used to automatically detect software problems by structuring and learning patterns in logs and metrics. Before Zebrium, Larry was Chief Data Scientist at Nimble Storage, founding that company's data science team and architecting/implementing their peta-scale platform for automation and analytics. He also started NetApp's Engineering Informatics Group as Senior Engineer, invented Glassbeam's ETL-focused SPL technology as CTO/Co-Founder, and received a leadership award from the International Congress on Neural Networks as graduate student.
Rod is known as the as the pioneer of using data science and analytics to analyze logs and metrics. Prior to Zebrium he joined Nimble Storage as an early employee and created the InfoSight predictive analytics platform. This resulted in a proactive support model that eliminated the need for Level-1 and 2 support engineers by automating the resolution of 86% of support cases. Prior to Nimble, he co-founded Glassbeam as VP Engineering. Rod began his career in this field when he built the NetApp Support Automation team using AutoSupport product telemetry in 1999.
With over 20 years of experience across a diverse range of roles, Gavin has the passion and experience to define and build a new market category for Zebrium. Prior to Zebrium, he was VP of Product and Solutions Marketing at Nimble Storage where he was responsible for redefining the company’s category and positioning. He has also held senior product management, business development and technical evangelist roles in Australia and the U.S.
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