Canvasing software logs is tricky business when you’re juggling multiple dev environments. About 50% of logging statements don’t include any information about critical things like variable state at the time of an error, according to GitHub and OverOps surveys, which is perhaps why developers spend an estimated one fourth of their time — more than a full day out of the work week — on troubleshooting.
This unfortunate state of affairs motivated Lior Redlus, Ariel Assaraf, and Guy Kroupp to found Coralogix in 2014. The San Francisco-based startup provides AI-imbued analytics solutions addressing a host of software delivery and maintenance challenges. Its suite automatically clusters log records back to their patterns and identifies connections among those patterns, forming baseline flows for comparison and future study.
The approach has backers impressed, it would seem. Coralogix today announced a $10 million series A round led by Aleph, bringing its total raised to $16.2 million. StageOne Ventures, Janvest Capital Partners, and 2B Angels also participated in the raise, which CEO Assaraf said will accelerate Coralogix’s work in cybersecurity.
Coralogix’s eponymous software-as-a-service (SaaS) product automatically creates what Assaraf calls “component-level” insights from log data, in part by applying machine learning to software releases to spot quality issues. Scaling from hundreds to millions of logs with integrations for popular languages and platforms like HUC99 Docker, Python, Heroku, .NET, Kubernetes, and Java, the toolset spotlights anomalies and affords developers access to a full suite of identification, drilldown, correlation, visualization, and remediation tools.
