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We as software developers or researchers very often get stacktrace error messages while we are trying to write some code or install some packages. Many times these error messages are very obscure and verbose; do not make much sense to us. There is a good chance that someone else has also faced similar issues probably shared similar stacktrace in various online developers' forums. However traditional google searches or other search engines are not very helpful to find web pages with similar stacktraces. In order to address this problem, we have developed a web interface; a better search engine: as an outcome of this research project where users can find appropriate stack overflow posts by submitting the whole stacktrace error message. The current developed solution can serve real-time parallel user queries with top-matched stack overflow posts within 50 seconds using a server with 300GB RAM. This study provides a comprehensive overview of the NLP techniques used in this study and an extensive overview of the research pipeline. This comprehensive result, limitations, and computational overhead mentioned in this study can be used by future researchers and software developers to build a better solution for this same problem or similar large-scale text matching-related tasks.