Quick Install - On VM, On-premises or on your own system;
Quick Install - With Azure CLI or GCP CLI;
Organize work in self-service teams with GDPR-compliant data storage and processing.
Add GPUs to your cluster and users can use them as needed - with quotas.
Start small on a single VM and scale to clusters of 1000s of CPUs/GPUs and PBs of data.
Run Jupyter notebooks as jobs or use PyCharm plugin. Install libraries with, conda/pypi.
Runs on commodity hardware; support for Ubuntu/Debian and Redhat/Centos.
Use Hopsworks to build paid services on it. If, however, you modify the code, you should release it as AGPL-V3.
• Centos/RHEL 7.x or Ubuntu 18.04;
• at least 32GB RAM,
• at least 8 CPUs,
• 100 GB of free hard-disk space,
• outside Internet access (if this server is air-gapped, contact Logical Clocks for support).