Tonal is the ultimate strength training system, giving you the expertise of a personal trainer and a full gym in your home. Through user interviews and social media feedback, we identified a consistent challenge: members found it difficult to measure their progress in their fitness journey. To address this, we developed the Training Goal (TG) ecosystem, a four-part solution that introduced new preference options to capture users' fitness aspirations, implemented weekly metrics that accumulate as members complete workouts, defined personalized weekly targets to guide progress, and enhanced workout details to show how each session contributes toward individual goals.We present how we leveraged Spark, MLflow, and Workflows within the Databricks ecosystem to compute TG metrics, manage model development, and orchestrate data pipelines. These tools allowed us to launch the TG system on schedule, supporting scalability, reliability, and a more meaningful, personalized way for members to track their progress.