While DevOps teams have many tools to automatically detect software problems, finding the root cause is still a painful process of drilling-down on dashboards and digging through logs. Our vision for Root Cause as a Service is a world where root cause is automatically surfaced directly in the tools you are already using.
Our mission is to build technology that can find the best possible root cause indicators in logs (the same ones a skilled engineer would have eventually found through manual hunting). And to do this without any rules or manual training.
With traditional tools, finding incident root cause can take hours, requiring skill, experience, intuition and brute force, as engineers dig through logs to piece together what happened. Zebrium changes this by using unsupervised machine learning on logs to automaticity find the best possible root cause indicators.
When you have a problem, you shouldn't have to go to another tool to see the root cause (RC). If you're looking at a monitoring dashboard, you should see RC there; if you use an incident management tool, RC should automatically appear in the incident's details. Root Cause as a Service works with almost any kind of DevOps tool.
The Zebrium platform does not require manual training or human-built rules. All that's needed is to start sending your logs. And it achieves accuracy within 24 hours.
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.
We are looking for exceptional data scientists, machine learning experts, DevOps engineers and UX/UI developers. If you're interested in joining an early stage company that is leading the way in a new and important market category, please contact us at firstname.lastname@example.org