DisDeL, presented at the 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, is an OpenWhisk package that addresses many limitations of serverless computing when running deep learning and other data-intensive applications, including memory constraints and job failures due to timeouts. This is joint work between PEARL Director Dimitrios S. Nikolopoulos and collaborators Kevin Assogba, Moiz Arif and M. Mustafa Rafique from the College of Computing and Information Sciences at RIT.