At Groww, I identified a bottleneck in the pull request review process: reviewers and engineering managers had to manually navigate SonarQube to verify code quality metrics before approving changes. This slowed reviews and reduced visibility into the overall health of active projects. To streamline this workflow, I designed and developed a Slack bot that integrated Slack APIs and Slack Block Kit with SonarQube to automatically fetch and present key quality metrics - including code smells, bugs, vulnerabilities, security hotspots, and test coverage - for every active project. I also implemented logic to compare metrics across pull request builds, highlighting regressions and improvements before code reached production. To improve ownership and collaboration, the bot automatically routed project-specific reports to the appropriate engineering teams through dedicated Slack channels. By embedding actionable code quality insights directly into developers' existing workflow, the solution eliminated the need for manual SonarQube checks, reduced pull request review turnaround time by up to two hours, and helped engineering teams identify quality regressions earlier. The project improved development efficiency while reinforcing consistent code quality standards across multiple teams.
