The 21st century has been characterized by advancements in technology, one of them being the development and growth of DevOps as set of practices that combines software development and IT operations. DevOps is concerned with combining both the Development and Operations teams to increase cross-functional communication and the speed at which software solutions are delivered to the market. Management thinker, Peter Drucker, is often quoted as saying that ‘you cannot manage what you cannot measure. By this, Drucker meant that an organisation cannot know if it is successful unless it defines and tracks success. With a clearly established metric for success, an organization can quantify progress and adjust their process to produce more desired outcomes. DevOps metrics are therefore used to measure the efficiency of DevOps pipeline, identify, and remove defects in the process and aid in measuring the successful organization. Despite the rise of DevOps as a set of practices, tools, and philosophical cultures that aid in delivering software to the market faster, the literature shows little empirical research in the area of DevOps metrics and their capabilities, and this warranted further study to identify opportunities for improvements. In pursuit of identifying opportunities for improvements in DevOps metrics, the thesis has used a systematic literature review in analysing and coming up with crucial DevOps metrics to be considered for specific improvement suggestions. The review also looked at the maturity models used to measure the growth of DevOps and examined the existing relationship between the business Objectives and Key Results (OKRs), DevOps capabilities, and their metrics. The thesis emphasizes on how these capabilities can be improved to accelerate the maturity of the DevOps pipeline and make teams rise in effectiveness. The suggestions for improvements are realized by presenting findings that outline the critical ideas collected during research and then discussion, which places this study within the existing literature and then offers recommendations for improving the state of DevOps. The discussion section includes several maturity models and identifies costs for measuring and monitoring DevOps. Through the measuring and monitoring of DevOps metrics, the organization is able to foresee the cost of growing and developing their DevOps teams alongside their benefits. Finally, the thesis concludes with an outline and explanation of the main ideas and recommendations on how to post excellent results on DevOps practices.