Bhuvanesh Nagarajan

Skilled Python developer adept at crafting automation scripts and optimizing SQL queries for enhanced efficiency. Collaborative team player committed to achieving outstanding results. Currently broadening expertise with Go lang to further enhance project capabilities. Possesses a strong foundation in Python and databases, with a dedication to continuous learning and contribution to project success. Known for innovative problem-solving and proactive approach to challenges.

• Go The Complete Guide

• AUDIT TOOL FORTIGATE

I played a pivotal role in the FortiGate project, where I managed the reception of numerous .conf configuration files across various operating system versions. Upon receiving these files, I orchestrated the generation of HTML reports, leveraging Python to implement diverse criteria for report generation. This involved the development of 40 Python modules, each executing distinct operations. Additionally, I integrated PostgreSQL database functionality to facilitate data insertion and retrieval for dynamic HTML report generation. Notably, I spearheaded the creation of the licensing component, ensuring compliance with licensing requirements. Subsequently, I compiled all modules into a binary executable, achieving seamless deployment. This project was exclusively developed in Python, harnessing its extensive capabilities to deliver a comprehensive solution.

• SECURITY AUDIT CHECKPOINT

In this checkpoint, HTML files containing firewall configuration data are received within a zip archive. Selenium WebDriver is used to extract the data, and BeautifulSoup parses it. The extracted data is then inserted into a PostgreSQL database. Modules for data processing and updating the database have been created. PyInstaller generates a binary, enabling the creation of an HTML report summarizing the configuration data.

• AUDIT CHECKPOINT FORTIGATE:

For future enhancement and improved compatibility and performance,  integrated FortiGate and Checkpoint systems for streamlined data  processing. Previously, data was managed in CSV format and stored in  PostgreSQL databases. To expedite data processing, transitioned to  MongoDB with JSON format. Leveraging Python for seamless integration,  ensuring efficient data management and processing.