In the context of MLOps, the benefits of using a multi-tenant system are manifold. Machine learning engineers, data scientists, analysts, modelers, and other practitioners contributing to MLOps processes often need to perform similar activities with equally similar software stacks. It is hugely beneficial for a company to maintain only one instance of the stack or its capabilities--this cuts costs, saves time, and enhances collaboration. In essence, MLOps teams on multi-tenant systems can be exponentially more efficient because they aren't wasting time switching between two different stacks or systems. Adoption of multi-tenant systems is growing, and for good reason.