Deploying AI and Machine Learning in the Enterprise
IT is facing a new set of challenges with AI and machine learning emerging in enterprises. Not only must they maintain secure environments, but they need to be agile and support the innovation needs of the ever-demanding business. Therefore, Enterprise IT often finds it difficult to securely provision requisite data on-premises for machine learning purposes. In addition, the cost of compute and storage can increase if there is uncontrolled access due to a lack of appropriate infrastructure monitoring solutions surrounding machine learning models. Today, H2O.ai solves this situation by providing H2O Enterprise Puddle, a secure and convenient way for IT to manage instances for the data scientists on a virtual private cloud.
Key Benefits of Enterprise Puddle
Lower the Barrier to Machine Learning
Enterprise Puddle offers a secure and convenient way to launch H2O.ai platforms, H2O open source and H2O Driverless AI, on virtual private clouds through Microsoft Azure, AWS and GCP.
Environments are secure and run in customer virtual private cloud (VPC). Both data and experiments are secured. This allows for IT to easily manage resources, users, permissions effectively and easily.
Enterprise Puddle helps manage total costs by controlling instance types, turning off idle instances and managing entitlements for users. It provides a rich dashboard for DevOps to monitor metrics and stats of resource usage.
Creates Flexibility for Data Scientists
This an easy way to update new versions so that data scientists have ready access to the latest versions of H2O.ai platforms. Furthermore, Enterprise Puddle provides an easy self-serve ability for data scientists to start and connect to H2O.ai platforms.
How Enterprise Puddle Works (with Microsoft Azure VPC)