Log Analyzer for Update Manager 
Shiva Sagar Shetty1, Poonam G2, Sadhana Ashar3
1Shiva Sagar Shetty*, Computer Science Department, RVCE, Bengaluru, India.
2Dr. Poonam G, Computer Science Department, RVCE, Bengaluru, India.
3Sadhana Ashar, ISSDC, HPE, Bengaluru, India.
Manuscript received on April 11, 2020. | Revised Manuscript received on May 15, 2020. | Manuscript published on June 30, 2020. | PP: 328-330 | Volume-9 Issue-5, June 2020. | Retrieval Number: E9507069520/2020©BEIESP | DOI: 10.35940/ijeat.E9507.069520
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Performing System updates is a very tricky and complicated task. You have to update new software on the same old hardware. This may introduce many errors in the system. For example a windows update on a single PC is generally prone to failures. Further updating a server is more challenging job. As a server can support many Operating systems their components, firmware’s and software’s etc, there are many possibilities that a server update may initiate many errors in the system. Thus, this paper proposes a tool that can go through all those thousands of log files generated during an update of a server and finds out where exactly the update went wrong. The paper describes about building a tool to perform log analysis from the scratch. It describes about developing parsers at the backend, building a user interface at the frontend and deploying the tool on to network. The proposed work supports building a Docker for the backend. Docker is a platform as a service product that uses OS-level virtualization to deliver software in packages called containers. The tool takes compressed log file as input. The tool analyses the structure of log file and then parses the contents of the log file according to its structure. Finally the proposed tool generates a report in JSON (JavaScript Object Notation) as well as CSV (Comma-Separated Values) format and that report consists of all the required fields to identify and classify the error that was responsible for failure during system update. This report is sent to concerned software development team to fix the defect that occurred in the update.
Keywords: Log Analyzer, Powerful parsers, well-built backend, Web App framework.