Debajit Das

With extensive experience in engineering, I specialize in cutting-edge technologies and collaborative projects across AWS, Azure, and GCP. I excel in building, deploying, and supporting IaaS and PaaS solutions on Linux/Unix/Windows platforms. Proficient in CI/CD pipelines, Jenkins, GitLab, Ansible, Terraform, and various build tools, I drive efficient and reliable software delivery. My advanced skills in machine learning enable me to leverage models for predictive analytics, automate workflows, and enhance data-driven decision-making.

1) Automated Error Detection & Error Correction using GenAI and Model creation(AI Bug Buster) in GitLab, 07/01/24- Present, 

- Problem: In the rapidly evolving landscape of software development, efficient error management is crucial for maintaining project timelines and ensuring product reliability, yet manual error detection and resolution in platforms like GitLab or Jenkins often prove to be time-consuming and error-prone 

Solution: 1) Leverages advanced generative AI and LLM models to automate error detection and correction processes 2) Analyzes GitLab logs in real-time to identify patterns indicative of errors. 3) Suggests or applies fixes based on model predictions, streamlining the error management process. 

-Filed this idea for Patent. 

2) Automated Test Executions in Gitlab and Jenkins, 08/01/23, Present, 

- Problem: All test cases were executed manually through the user interface, one by one. This approach was time-consuming, prone to human error, and limited the scalability of the testing process. 

- Solution: A GitLab pipeline has been implemented to automate the build and test processes. With this pipeline in place, all builds and test executions are conducted sequentially and independently. And visualize the reports in Grafana. This automation ensures more efficient testing, reduces the potential for errors, and enhances the overall scalability and reliability of the development workflow. 

3) ChatBot for Grafana and DevOps, 07/01/24, Present, 

- Problem: Developing and managing applications across various DevOps tools such as GitLab, Kubernetes, Ansible, and Terraform presents significant challenges. Teams often encounter inefficient monitoring processes that delay issue resolution, limited access to automation resources, and fragmented workflows that hinder productivity. 

- Solution: Developing an intelligent ChatBot integrated with Grafana and key DevOps tools like GitLab, Kubernetes, Ansible, Terraform etc. This ChatBot will not only provide seamless monitoring also offer on-demand access to code snippets, configuration templates, and automation scripts. By serving as a unified interface, the ChatBot will enhance operational efficiency, streamline workflows, and empower teams with instant access to essential code resources. This is also selected in Process Innovation.

• Already Filed a Patent on AI Powered Bug Buster
• Getting Silver and Bronze Batch for individual contribution for the car line BR590
• Awarded for implemented patent for ADAS, CIVIC and Zonal Controller team.

North America, 02/01/24, 03/01/24, During the visit to North America, I presented my research work and a project on visualizing reports for all test cases. The presentation was highly praised by all members of MBRDNA, resulting in the acquisition of three new projects for the India team (MBRDI). Additionally, the audience expressed interest in implementing the same visualization approach in their own projects.

• English, 80/100
• Hindi, 80/100
• Bengali, 80/100