LLMOps: Definitions, Framework and Best Practices

Operationalizing large language models is unlike traditional AI solutioning. As the vestiges of the MLOps paradigm serve as a reminder of the sophistication that surfaces at scale, Generative AI, while mitigating a few of those challenges, brings a few of its own. This is where LLMOps (Large Language Model Operations) comes into the picture. LLMOps is a subset of FMOps (Foundation Model Operations) that builds on the principles of MLOps (Machine Learning Operations) and helps enterprises deploy, monitor, and retrain their LLMs seamlessly. This paper provides a comprehensive definition of LLMOps and a robust framework and highlights best practices accrued through our experience building solutions in different domains. Finally, this work attempts to provide guidance for AI practitioners who want to operationalize their GenAl applications seamlessly.