Provision
Repeatable installation and configuration of a supported Kubernetes environment.
Development objectiveAnvil / Private AI infrastructure
Active developmentMake the cluster a foundation. Not a project of its own.
Anvil is being developed to automate private Kubernetes infrastructure for AI workloads. The focus is repeatable provisioning and a lifecycle that an existing IT team can understand and operate.
Inside Anvil
See the infrastructure take shape.
Application screenshots · development build
Screens captured from Anvil during development. They show the interface and in-progress operations, not a general-availability release.
Cluster overview
View full size ↗ (opens in a new tab)Cluster status, platform services, and infrastructure health in the development environment.
From supported hardware to AI workloads
Start with a defined deployment path.
AI infrastructure combines familiar responsibilities—compute, networks, storage, identity—with model-serving and GPU requirements. Anvil’s role is to bring those responsibilities into a supported operational environment.
Initial scope centers on a defined hardware and software configuration. Compatibility, installation behavior, and lifecycle operations need to be validated before they become published support commitments.
Discuss your deployment requirements →AnvilProvisioning & lifecycle control
Control planeSupported configuration
AI workerSupported configuration
AI workerSupported configuration
Networking Health signals
Illustrative topology. Actual sizing depends on the workload and validated deployment profile.
Product focus
Plan for day two from day one.
Operate
Cluster health and essential platform services with clear operator visibility.
Development objectiveMaintain
Documented update, backup, recovery, and rollback procedures validated against supported configurations.
Development objectiveScope & readiness
A credible starting point. A deliberate roadmap.
Initial validation priorities
- One repeatable installation path
- A published hardware compatibility matrix
- Defined networking and GPU configuration
- Cluster health and operational runbooks
- A complete demonstration with an AI workload
Later-stage objectives
- Disconnected installation and update lifecycle
- Multi-site fleet administration
- Broader hardware and GPU coverage
- Expanded resilience and upgrade automation
These are roadmap directions, not current availability or performance guarantees.
Build with us
Start with one useful workflow.
Bring your infrastructure, your operational constraints, and a problem worth solving. Together, we can define a focused pilot and what success should look like.