Neptune runs on Kubernetes, ensuring that the process of establishing and closing the VM is smooth. By using the templates provided by Helm, Neptune reduces the time needed to run new machines and start the experiment, as everything is done in real time. Users need not pay to run a machine while it is being established, but only for resources when they are being used.
Neptune enables data scientists to run multiple experiments simultaneously, with every experiment launched on a separate machine with multiple GPUs, designed specially to run the machine learning process. By leveraging the distributed MooseFS, Neptune ensured that all the VMs share access to the training dataset, making additional storage for every machine unnecessary.
By using Kubernetes, the app is infrastructure-agnostic and may be established in both a private or public cloud. Neptune be run on a laptop, using cloud resources, or bare-metal infrastructure.
Neptune was developed for internal use by CodiLime to support its own data science team. As it proved supremely convenient, effective and scalable, the company decided to launch it as an independent product, and later spun the company off.