Technical debt (TD) is a metaphor in the field of software development that reflects the validation of short-term advantages to long-term effects. The term refers to shortcuts in software development that lead to poor software design and architecture. Also, it negatively impacts the maintainability, efficiency, and extensibility of the system. There are many TD types that are not all with the same level of importance to be paid off. While they don’t have the same impact on the system development, TD prioritization is mandatory. Using DevOps practices, like the Automated Continuous Integration/Continuous Deployment (CI/CD) pipelines in cloud computing, can be helpful in improving the quality of software systems by prioritizing the TDs. This prioritization allows the developers to deal with every issue discovered. In this research paper, the coding TD is taken into consideration, and a dataset (as a source code file, written in C programming language) is analyzed using a tool called SonarCloud. This tool serves as a cloud-based DevOps tool for maintaining clean codes. It has demonstrated its ability to prioritize Technical Debt based on the analysis results.