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PUBLIC CLOUD · AI & MACHINE LEARNING
Workflows
A fully managed, sovereign platform for automating and orchestrating data and ML workflows — scalable, reliable, and deeply integrated with CloudFerro's compute and storage ecosystem.
- Open-source foundation
- Usage-based pricing
- EU Sovereign
Product Features
Orchestration for complex data and ML workflows
A managed workflow orchestration platform for automating data pipelines and ML workflows within a sovereign European cloud.
DAG-based data & ML orchestration
Define, schedule, and manage complex workflows as DAGs, including ETL/ELT pipelines, ML preprocessing, model training, and batch analytics.
Scalable Kubernetes-based execution
Run containerised tasks on Kubernetes-backed workers that scale with your workloads. Distribute compute-intensive pipelines without manually tuning the cluster.
Built-in monitoring, logs & retries
Monitor DAG runs, inspect task logs, configure retries, and manage alerts through the platform UI for greater control over every workflow execution.
Workflow versioning & dependency management
Manage DAG versions and dependencies between pipelines, roll back workflow definitions, and use integrated error handling to maintain reliable execution.
Automate data and ML workflows end to end
Accelerate and standardise data operations with a fully managed platform that reduces overhead and maintains full compliance.
Fully managed orchestration
No environment installation, no Kubernetes administration, no dependency management. CloudFerro handles all infrastructure, updates, patches, and maintenance so your team focuses entirely on building pipelines.
Designed for large data pipelines
Kubernetes-backed workers scale automatically to match the size of your workloads — from small scheduled jobs to large-scale EO data processing and ML training pipelines.
Deep ecosystem integration
Works natively with CloudFerro Compute, Storage, Managed Notebooks, MLflowTM, and Managed Kubernetes, a single, coherent platform for the entire data and ML pipeline lifecycle.
Enterprise reliability
Built-in monitoring, retry logic, error handling, alerting, and predictable scheduling give operations and data teams the confidence to run mission-critical workflows in production.
Typical Use Cases
What can you automate with CloudFerro Workflows?
INTEGRATIONS
Orchestrate the full CloudFerro AI ecosystem
CloudFerro Workflows integrates natively with CloudFerro compute, storage, MLOps, Managed Kubernetes, and Managed Notebooks, a single orchestration layer for your entire data and ML pipeline lifecycle.
MLOps Pipelines (MLOps Studio)
Orchestrate end-to-end ML workflows — trigger MLOps Studio pipelines from DAGs for training, evaluation, and model deployment.
AI Experiments
Log experiments, track model metrics, and push artefacts to MLflowTM registries directly from pipeline steps.
AI Compute
Trigger GPU-backed compute tasks as workflow tasks for model training, inference, and large-scale EO processing workloads.
Managed Notebooks
Execute notebook-based experiments and preprocessing jobs from DAGs — bridging interactive development with automated production pipelines.
Object / Block Storage
Native access to all CloudFerro storage types and EO datasets — ingest, transform, and write pipeline outputs without data movement overhead.
Managed Kubernetes
Deploy containerised pipeline tasks as Kubernetes pods — enabling isolated, reproducible, and scalable workflow step execution.
Scope description
Technical Specification
A fully managed, privacy-first Generative AI platform with OpenAI-compatible APIs, hosted 100% in Europe for total sovereignty.
Orchestrator
Fully managed workflow orchestration
Execution backend
Kubernetes-backed scalable workers
Scheduling
DAG-based · cron · event-driven triggers
Storage access
Object · Block · EO data repositories
Locations
Poland (WAW) · Germany (FRA)
Billing
Usage-based (compute + storage) · reserved capacity 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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EO Products & Services
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Start working in a managed JupyterLab environment without setup. Use preconfigured ML and data science libraries, choose CPU or GPU-backed notebooks.
AI & Machine Learning
Managed GenAI Services
Use a fully managed, privacy-first GenAI service with OpenAI-compatible endpoints, hosted on 100% European infrastructure with processing in Poland.
Storage
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Manage object storage containers and buckets for S3/Swift-compatible data access.
Compute
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Run event-driven functions, lightweight workflows and scheduled tasks without provisioning servers.