While the LMDS is hosted in house, the frameworks provided could be used for platforms deployed to commercial cloud providers, such as Amazon Web Services or Microsoft Azure. Third party cloud providers alleviate concerns over server maintenance and hardware failure. However, each commercial cloud platform requires bespoke training to use, which may be a niche skill for computational materials science researchers. Concerns may be raised over vendor lock in, as such services may become more expensive or less reliable in the future. Further, the monthly billing cycle commercial cloud providers often demand is not compatible long term with the fixed consumable budgets that are typically provided as part of a research grant. Depending on funding and available hardware, a commercial cloud provider may be the best solution for rapid delivery. If the mission critical up time that is guaranteed by server hardware is not a driving design choice, then many computational research groups may find they already have the necessary resources to hand, as this architecture may be run on an underused workstation.