This case study examines Headspace's need for a cloud-based solution to improve patient data management and access. The report analyzes the non-functional requirements of the system, including functionality, usability, reliability, performance, and security, emphasizing the importance of data confidentiality. It recommends a hybrid cloud solution, highlighting its strengths in security and cost-effectiveness while acknowledging potential weaknesses such as data movement and implementation costs. The study further explores Software Development Life Cycle (SDLC) approaches, comparing predictive and adaptive methods, and recommends the predictive approach for Headspace. The document concludes by summarizing the key findings and recommendations, providing a framework for Headspace to implement a secure and efficient cloud-based system for managing patient records.