Operations managers play a critical role in the MLOps life cycle. Without the proper infrastructure, the number of CPU nodes, or security checks, models, and applications built by data science and development teams are more likely to fail – if they even reach the deployment phase.
That’s why operations managers should be brought into the MLOps process from the beginning. Doing so can yield many benefits. For example, operations managers may be able to point out infrastructure compatibility issues as applications are being developed. This can save developers and scientists from having to go back and revise their work when development is almost complete. When an operations manager is involved, projects can run more smoothly, efficiently, and at speed – right from the start.
