Case Study: Coralogix achieves rapid, ML-driven error detection and root-cause analysis with Microsoft Azure

Startup uses machine learning to identify programming errors with log analytics

Coralogix is a startup that uses machine learning to analyze software logs and rapidly identify programming errors and anomalies. The company set out to solve the costly problem of wasted engineering time—more than 70% of resolution effort is spent just discovering issues in vast volumes of unstructured log data—by building a system that can automatically learn normal behavior and flag deviations at scale.

Coralogix delivers a cloud SaaS platform on Microsoft Azure that applies ML models to every log record to detect anomalies, surface root causes, and provide actionable insights. By leveraging Azure for scalability, reliability, hybrid support, and pay-as-you-go resources (and with help from the Microsoft Accelerator), Coralogix sped diagnosis and resolution, improved system availability, and achieved measurable performance gains for customers.

Coralogix

Lior Redlus

Chief Scientist