Red Hat offers flexible and feature-rich software systems and services. Configuring these systems is a complicated task. For e.g., the configuration file for SSSD service has more than 100 configuration entries with different sub-entries. Currently, in most cases, misconfigurations are detected by manually specified rules. This process is tedious and not scalable to a wider problem. Red Hat Insights collects metadata about the configuration of multiple systems and uses rules to proactively identify threats to security, performance, and stability across systems. In this project, we propose data-driven methods to detect misconfigurations by discovering frequently occurring patterns in configuration files.
Red Hat Intern: Sanket Badhe