I have developed a comprehensive monitoring system for Control-M job statuses using the Flask framework. I also utilized the Spring Boot framework to create REST APIs, facilitating cross-departmental communication for tracking Accruals status in a finance application. Additionally, I automated a file-to-database data loading process, significantly reducing processing time from 40 to 10 minutes and optimizing workflow. Implemented Docker containers for automated data refreshing, ensuring synchronization with the master database and maintaining data integrity. Leveraging the functional knowledge of applications and strong debugging skills, I achieved a 100% resolution SLA for client requests in finance applications.

Revamped an existing software application using Spring Boot and MongoDB, enhancing the development process and significantly reducing ongoing maintenance requirements.

As a Digital Intern, I designed and implemented a robust log analysis solution using the ELK Stack (Elasticsearch, Logstash, and Kibana). I played a key role in writing grok patterns to parse streams of logs fetched by Logstash, ensuring accurate extraction of relevant information. The parsed logs were stored in Elasticsearch, and I utilized Kibana to build interactive visualizations and dashboards. This approach provided real-time insights into application issues, eliminating the need for manual log file inspection and enhancing efficiency in issue identification and resolution.