Error Log Management Software (Smart India Hackathon National Grand Finalist)

System administrators deal with large numbers of error logs on a day-to-day basis. Reading through, understanding, and implementing the best course for the action of each log is a herculean task which at its essence is a repetitive and time-consuming task that can waste valuable human resources. This project aims to automate the process of dealing with error logs by developing an end-to-end system that can analyze error logs generated by a system or a server. The system will then determine the most important logs, read through an appropriate forum for solutions, and provide links to the most relevant solutions that the system admin should undertake. The system can also predict if a severe error log will occur so that precautionary measures can be adopted. The system is built using ELK Stack with the machine learning tasks being performed by Kibana. This project was developed as part of a 36-hour national level hackathon where my team of 6 was one of the grand finalists out of 150,000 other submissions.