Customer cloud · Kubernetes

Offer managed clusters as an operator-owned service.

Customers create Kubernetes environments for applications, training and inference using approved shapes, locations, projects and policies from your catalogue.

Discuss your requirementsCustomer cloud overview
Scheduler · placementVM · m.large × 4→ Hall AKubernetes · 6 nodes→ Hall AGPU job · 4× accelerator→ Hall BHall A · CPU + GPUHall B · acceleratorsgpugpugpugpugpugpugpu18 nodes · 7 accelerators · placement follows quota and residencyVMS · CONTAINERS · KUBERNETES · GPU · STORAGE · NETWORK — ONE CATALOGUE
Product
Managed cluster
Catalogue-defined
Use
App, AI & data
Approved workload patterns
Placement
Estate-aware
Location and capacity policy
Access
Team-ready
Projects and credentials
Scope

A customer service around the cluster lifecycle.

LayerOne connects the cluster request to infrastructure placement, tenant governance and metering.

Cluster profiles

Publish approved control-plane and worker configurations.

Accelerator workers

Attach eligible GPU capacity for training and inference profiles.

Project networking

Create the cluster inside the customer project and approved network model.

Service metering

Attribute cluster and underlying resource usage to the tenant and plan.

Operating workflow

A repeatable cluster service from request to retirement.

Customers select an approved profile; the platform carries the operational context.

  1. 01

    Choose a profile

    Select purpose, location and worker configuration.

  2. 02

    Assign the project

    Apply team access, network and quota context.

  3. 03

    Create the cluster

    Place the service on eligible capacity and issue credentials.

  4. 04

    Operate and scale

    Manage workers and lifecycle through portal or API.

Two connected responsibilities

Operator control and customer action stay explicit.

Operator responsibility

What platform teams define

  • Cluster profiles and versions
  • Eligible worker capacity
  • Network and access policy
  • Upgrade and lifecycle rules
Service consumer

What application teams use

  • Purpose-built cluster choices
  • Project-scoped credentials
  • Worker scaling and status
  • Usage and service support
Operational outcome

What this changes in the working model.

Outcome 01

Repeatable delivery

Clusters follow one approved service definition.

Outcome 02

GPU-ready service

Accelerator capacity joins the cluster catalogue explicitly.

Outcome 03

Clear ownership

Every cluster belongs to a tenant, project and commercial plan.

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Partner with us

Package Kubernetes around the infrastructure you operate.

We will map cluster profiles, worker capacity and lifecycle responsibilities into a managed service.

Book a briefingCustomer cloud overview