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PUBLIC CLOUD · Containers & Serverless
Managed Kubernetes
CloudFerro Managed Kubernetes offers a container orchestration solution smoothly integrated with our European public cloud.
- Fully managed control plane
- Built-in cluster backups
- Self-healing clusters
Built on OpenStack and designed cloud-native from the ground up, the Service helps you run production-grade Kubernetes clusters with integrated cloud storage and networking. Kubernetes enables fast deployment of highly scalable applications, systems, and workloads, reducing both infrastructure and development overhead. Data scientists can also use Kubernetes on CloudFerro clouds to run complex workflows, with integrated access to EO data.
Whether you’re deploying microservices, data platforms, or batch workloads, CloudFerro Kubernetes Service helps you get from “idea” to production-grade application deployments faster.
Pain points
Kubernetes unlocks speed and portability, but self-managing clusters can quickly become a time sink.
Provisioning
Provisioning takes too long when clusters depend on manual setup and templates are hard to maintain.
Control plane
Operational risk grows when one wrong change can destabilize the control plane or break upgrades.
Scaling
Capacity falls short without a robust, scalable solution.
Integrations
Cloud integration is harder than it looks (load balancers, persistent volumes, networking, GPU).
From OpenStack Magnum to Managed Kubernetes
CloudFerro currently provides two alternatives for running Kubernetes Service clusters.
Recommended
Managed Kubernetes
- Dedicated Managed Kubernetes interfaces (GUI, CLI, IaC)
- CloudFerro operates and monitors the control plane to reduce operational risk
- Designed to prevent unsafe cluster changes by reconciling to the desired state
- Built with enterprise applications in mind, where no downtime throughout cluster’s lifecycle is priority
- New projects, migration of existing applications
Legacy
OpenStack Magnum
- OpenStack interfaces (GUI, CLI, IaC)
- More responsibility remains on the user side; you control the underlying VMs that run the cluster
- Higher chance that a problematic change or VM issue affects the cluster
- Sufficient and mostly tailored for workflow-based operations (e.g. data processing)
- Existing applications, running on Magnum; specific scenarios of use
For new deployments we recommend Managed Kubernetes. If you run clusters on Magnum today, you can continue operating them while planning a transition.
Availability: Poland (Warsaw) and Germany (Frankfurt) Cloud locations.
built into the Service
Cloud-Native Features
CloudFerro Cloud integrations
Native integration with CloudFerro networking and storage: the ability to use LoadBalancer-type services with public IP addresses exposed; shared storage classes available for use from within Kubernetes (PVC).
Autohealing (node recovery)
When a cluster node becomes unhealthy, the auto-healer automatically replaces it with a new server to restore capacity and keep workflows running.
GPU-enabled node pools
Node pools with GPU flavors, pre-configured and integrated to deliver GPU acceleration.
Autoscaling
Autoscaling and node-level healing to keep capacity aligned with demand and reduce manual intervention.
Pricing that matches how you use Managed Kubernetes
You pay for compute, storage and networking resources used to run your cluster.
There’s no additional charge for setting up and running the Kubernetes service.
EO data access remains available at no extra cost (where applicable).
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.
Other Products
Compute
Virtual Machines
Run and scale public cloud workloads in EU-based OpenStack data centres. Configure CPU, RAM, storage and OS, manage lifecycle actions.
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.
EO Products & Services
Managed Notebooks
Start working in a managed JupyterLab environment without setup. Use preconfigured ML and data science libraries, choose CPU or GPU-backed notebooks.
Databases
Managed Databases
Managed instances of PostgreSQL, MySQL, MariaDB, Valkey, and MS SQL Server. Automated backups, failover, and monitoring.
Storage
Object Storage
Manage object storage containers and buckets for S3/Swift-compatible data access.
Containers & Serverless
Functions
Run event-driven functions, lightweight workflows and scheduled tasks without provisioning servers.
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