As the world is moving towards cloud deployments, enterprises of all sizes are trying to figure out the best ways to optimize their workloads using the available set of resources. This often involves evaluating their portfolio of workloads and applications and identifying the best cloud or non-cloud venue to host each.
The decision process is based on multiple considerations, including performance, integration issues, economics, competitive differentiation, solution maturity, risk tolerance, regulatory compliance considerations, skills availability, and partner landscape.
We'll talk about all the above and some practical ideas on how to go about such a journey specifically from an AI and ML perspective. Finally, we'll also look at a few example deployments with H2O, Sparkling Water, and Driverless AI.