Next-generation sequencing (NGS) workloads require more data than ever before. However, it isn't just storage infrastructure that needs to be expanded, but also computing resources to run processes on this data, which can quickly add up costs that exceed most research organizations' budgets. At this point, the NGS compute demand exceeds the infrastructure capacity.
Cloud computing offers a great solution to these issues, offering pay-as-you-go pricing and access to virtually limitless compute capacity. Still, there are a few concerns about using cloud compute for genomics workloads, including moving the entire data set into cloud and rewriting applications to access data using object storage protocols instead of existing NAS.