Shonan Dataworks ML Cloud™
A Secure Machine Learning Laboratory
Shonan Dataworks ML Cloud™ is a powerful, Jupyter notebook-based machine-learning laboratory platform, purpose-built to support secure data-science research collaboration. It provides a controlled environment for researchers and enterprise teams to explore, build and deploy advanced ML models with confidence.
Our Vision: A Collaborative ML Laboratory
Standardized data-science workspaces
Each user is provisioned with a secure, isolated JupyterHub environment, offering familiar tools in a controlled cloud setting.
Transparent collaboration
Built-in content management and versioning enable seamless collaboration between internal teams and external researchers, with clear change tracking and history.
Simple project administration
Through an intuitive interface, administrators can allocate computing resources, manage libraries and data sources, and coordinate research participants.
Reproducible research
The platform ensures that experiments can be precisely replicated, thanks to consistent program code, library versions and execution environments.
Utilization insights
A customizable dashboard delivers detailed analytics on platform usage to help optimize research resource planning.
Administrative Control
Rigorous data security
Each dataset and workspace is assigned a security level, ensuring only authorized users with adequate security clearance can access sensitive information.
Resource allocation management
Administrators control the distribution of CPU, GPU and software resources through a centralized dashboard.
Team-based research structure
Projects are organized into ML Teams, with Team Admins overseeing participants, data and assets.
Audit transparency
Every action, from user access, research activity, team management to system configuration setting, is comprehensively logged for accountability and compliance.
Robust Security Features
Principle of least privilege
Fine-grained permissions grant users access only to the resources they need.
Secure platform access
OAuth integration and cloud-native authentication allow secure storage and management of user directories.
Isolated cloud environmental control
Infrastructure-as-Code provisions discrete test, staging and production environments, keeping projects segmented.
Configurable login policies
Administrators define password complexity, expiry and reuse rules to meet corporate standards.
Brute-force detection & alerts
Automated rate limiting and notification of repeated failed login attempts protect against intrusion.
Advanced Cloud Resource Management
Dynamic resource allocation
Server resources are provisioned on demand for research execution and automatically released when idle.
Real-time environment monitoring
Health dashboards track CPU/memory usage and alert administrators when thresholds are exceeded.
Billing transparency
A billing dashboard tracks cloud resource consumption, enabling cost control and budget forecasting.
