<p>Container orchestration platforms have become essential for managing cloud-based containerized applications. While numerous studies have explored their usage, compared different tools, and investigated scaling techniques, there is a noticeable lack of discussion regarding the importance of effective resource utilization and its potential to enhance performance benefits based on the specific needs of applications. Our research is dedicated to addressing this critical gap through resource utilization-based container orchestration. This study involves categorizing the currently available container orchestration solutions and examining performance-focused container orchestration in conjunction with monitoring tools designed to track performance indicators and identify research trends. Our primary objective is to bridge the existing knowledge gap by elucidating how optimized resource utilization can result in significant performance improvements for cloud applications. Through this research, we aim to emphasize the significance of considering resource utilization as a pivotal factor in the design and implementation of container orchestration solutions. Ultimately, our work aims to contribute to the development of more efficient cloud-based applications across diverse domains, including but not limited to Big Data, machine learning, and behavioral-based applications.</p>