On this page5 sections
When do you need it?
- Applications need common operating rules across multiple servers.
- Cluster setup and maintenance need a shared process.
- You are moving applications to a new cluster environment.
- Model workloads need compute cards available in the cluster.
- The team running the cluster needs hands-on training.
What do we take on?
Setup
We prepare network, storage and access rules around your applications.
Migration
We move applications around their dependencies and operational needs.
Day-to-day operations
We track version upgrades, access and capacity.
GPU workloads
A GPU is a processor for compute-heavy work; we connect these cards to the cluster and configure how they are shared.
Training
We prepare hands-on training for the team that will run the cluster.
Tooling
| Environment | Kubernetes option |
|---|---|
| Microsoft Azure | AKS |
| AWS | EKS |
| Google Cloud | GKE |
| On-premises | RKE2 |
Technical articles
Frequently asked questions
Should we move to Kubernetes?
We make that decision after reviewing application dependencies and operational requirements. We assess the current environment and your team's needs before choosing a target.
Do you work in the cloud or in our own data center?
We work in both. Supported environments are listed in the tooling section on this page.
Do you run GPU workloads?
Yes, we connect compute cards for model workloads to the cluster. Where hardware supports it, we split cards into independent partitions for different workloads.
Can you operate the cluster after setup?
Yes, we can take on day-to-day operations through managed DevOps. That work covers cluster maintenance, release workflows and capacity monitoring.
Do you also train our team?
We prepare hands-on training in cluster operations. The content is tailored to participants’ current knowledge and the environment you use.