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European technologies in security and space
Commissioner Andrius Kubilius' visit to CloudFerro highlights the importance of European technologies for Europe's security and operational readiness
Public Cloud · AI & Machine Learning
Managed Notebooks
A sovereign, zero-setup JupyterLab environment for data science and ML — scalable, compliant, and integrated with CloudFerro's AI stack.
- EU Sovereign
- Zero setup
- Instant AI workspace
Product Features
Ready-to-use AI workspace for data science
A fully managed, sovereign, interactive development environment for data science and AI/ML workloads.
Ready-to-use JupyterLab environment
A fully managed JupyterLab workspace hosted in EU-based data centres — no installation, no configuration, no environment tuning. Open your notebook and start working immediately.
Python & pre-installed ML libraries
Popular ML and data science libraries come pre-installed and pre-configured: PyTorch, TensorFlow, RAPIDS, scikit-learn, and geospatial toolkits — ready on first launch.
Persistent home directory & scalable storage
Your work is preserved between sessions in a persistent home directory. Scale attached storage as your datasets grow, without reprovisioning or losing state.
Secure, isolated workspaces with managed updates
Secure authentication, identity integration, and fully isolated per-user workspaces. CloudFerro manages environment updates, patches, and dependency maintenance automatically.
From data to experimentation without setup
Accelerate AI research and data science by eliminating setup, configuration, and infrastructure overhead — focus fully on experimentation and model development.
Interactive development without setup
Run code step-by-step, visualise instantly, and iterate fast. Zero installation means your team is productive from the first login — no environment conflicts, no dependency hell.
Sovereign by design
All computation and data remain fully within EU-based infrastructure in Poland and Germany. GDPR-compliant by default.
Fast path to production
Notebook outputs feed directly into CloudFerro's MLOps services and pipelines. Move seamlessly from experimentation to production deployment without re-engineering your workflow.
No maintenance overhead
We manage the environment, dependencies, security patches, and updates. Your team focuses entirely on data science and model development — not infrastructure operations.
typical use cases
From data exploration to model training
INTEGRATIONS
Works natively with the CloudFerro AI ecosystem
Jupyter Notebooks integrate seamlessly with CloudFerro compute, storage, MLOps, Managed Kubernetes, and GenAI services — a complete path from experimentation to production inside one sovereign European cloud.
Storage (Object / Block / File)
Native access to all CloudFerro storage types and the EO data catalogue — query datasets without downloading or copying data.
MLOps Services (MLflowTM, AirflowTM, Spark)
Push experiments, models, and pipeline outputs to CloudFerro MLOps services for tracking, orchestration, and large-scale processing.
Managed Kubernetes
Deploy trained models and notebook-derived artefacts to production Kubernetes clusters without leaving the CloudFerro ecosystem.
Identity & Access Management
Centralised authentication, single sign-on, and role-based access control ensure secure, isolated workspaces for every user.
Scope description
Technical Specification
Managed, ready-to-use JupyterLab environments pre-configured with ML and geospatial libraries. Native access to CloudFerro storage. Optional GPU-backed notebooks. Fully hosted in EU data centres for sovereignty and compliance.
Environment
JupyterLab — fully managed, zero-setup
Languages
Python
Compute flavors
CPU-backed VM instances on demand
Storage access
Object · Block · File storage + EO data repositories
Locations
Łódź (LCJ)
Billing
Per-hour usage · fixed-term contract available
FAQ
Frequently Asked Questions
Didn’t find the answer you were looking for? Get in touch if you need more information or would like to speak with our team.
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