META X CMU MHCI CAPSTONE
Capturing the knowledge of today to build the data centers of tomorrow.
How can we improve the capture, delivery, and execution of information, to enable engineers within and across data centers to perform at a higher level and learn from others’ experiences?
Exploring the knowledge system and identifying the knowledge gaps in Meta's Data Centers today
Data centers are vast, complex ecosystems with a number of stakeholders, teams and equipment. Operating and maintaining these spaces take multiple complex systems and procedures. Through workshops, semi-structured interviews and secondary research, we unpacked the different parts of the data centers and identified the design principles important to Meta. With privacy and efficiency being at the core of a data center, we narrowed down the important challenges to scalability they face today.
Leveraging AI to empower engineers by democratising all the knowledge in Meta's Data Centers
After 3 months of research, we synthesized our findings to direct our design. Through co-creation sessions, rapid prototyping and adopting an agile design methodology, we explored various design interventions from policy, AR, hearables and voice interaction. Through continuous testing, we identified what ideas work and don’t work and how we could leverage the positives of the various ideas to develop our final solution.
The journey of our project has been a very critical learning experience and has challenged us at every phase. Read more about our process, how we went about untangling this incredibly complex ecosystem, and where we plan on even going from here.