As distributed systems scale, optimizing energy efficiency becomes increasingly critical yet challenging. This paper introduces a continuous process for improving energy efficiency that leverages three iterative steps — measure, monitor, and mitigate — forming a feedback loop. Utilizing state-of-the-art tools and best practices, we empirically demonstrate targeted optimizations. Our experiments highlight common pitfalls as well as the expected optimization opportunities and offer practical guidance for avoiding them. Our experiments reveal common pitfalls and highlight expected optimization opportunities, providing practical guidance in using our process. Additionally, we present an extensible monitoring platform designed to collect, analyze, and visualize energy consumption and performance metrics, facilitating the selection of informed optimization techniques. This approach is tailored for engineers and researchers seeking efficient and adaptable energy efficiency optimization strategies. By implementing this structured process, significant improvements in energy efficiency can be achieved, maximizing optimization impact relative to invested resources while maintaining system performance and reliability.