On-Premises Kubernetes: Architecture and Deployment Services

Yes, absolutely. Kubernetes is infrastructure-agnostic and runs on bare metal servers, on-premise virtual machines, VMware vSphere, hyper-converged infrastructure and private cloud platforms. Many organisations run production Kubernetes entirely on-premise, particularly in regulated industries where data sovereignty or compliance requirements restrict public cloud use.

With cloud Kubernetes (EKS, AKS, GKE), the cloud provider manages the Kubernetes control plane on your behalf. With on-premise Kubernetes, you are responsible for the full stack — including control plane management, etcd clustering, storage integration, load balancing and cluster upgrades. This requires more operational discipline and specialist expertise, which is why enterprise distributions like Red Hat OpenShift are often the better choice for on-premise deployments.

Private cloud Kubernetes refers to Kubernetes deployed on private infrastructure — whether a physically on-premise data centre or a hosted private cloud environment (such as Rackspace Private Cloud or VMware-based private cloud). It delivers cloud-native architecture and container orchestration capabilities without using public cloud infrastructure, giving organisations more control over data residency, security and cost.

It’s more demanding than deploying on a managed cloud service, because you’re responsible for components the cloud provider would otherwise manage. High availability design, storage architecture, networking and cluster lifecycle management all require careful attention. Using an enterprise Kubernetes distribution like Red Hat OpenShift significantly reduces this complexity by automating cluster operations and lifecycle management.

A straightforward on-premise Kubernetes deployment with a clear scope can be completed in four to eight weeks. More complex enterprise deployments involving legacy workload migration, bespoke security requirements or hybrid architecture design typically take two to four months. The architecture design phase at the beginning is critical — time invested there prevents far more time being lost to rework later.

Requirements depend on workload characteristics, but a minimal production-grade on-premise Kubernetes cluster typically requires three control plane nodes (for etcd redundancy) and at least three worker nodes. The underlying hardware — CPU cores, RAM and storage — should be sized based on workload requirements with appropriate headroom. We conduct infrastructure assessments as part of our engagement process to ensure the hardware foundation is right before deployment begins.

For most enterprise on-premise deployments, Red Hat OpenShift is the better choice. It automates cluster lifecycle management, provides integrated security controls, and comes with enterprise support. Upstream Kubernetes gives you more flexibility and lower licensing cost, but requires more operational effort to reach the same level of enterprise readiness. The right answer depends on your team’s capabilities, your governance requirements and your long-term platform strategy.

Yes, and many organisations do. A well-designed hybrid Kubernetes architecture uses consistent tooling across on-premise and cloud environments — the same GitOps workflows, monitoring frameworks and deployment patterns everywhere. Red Hat OpenShift is particularly well-suited to hybrid deployments because it runs identically across on-premise and cloud, eliminating the operational fragmentation that comes from managing different platforms in different environments.

Ongoing management of on-premise Kubernetes requires regular cluster upgrades, security patching, monitoring and incident response, capacity management and periodic architecture reviews. Some organisations manage this with internal teams; others use a managed service provider. DeeperThanBlue provides 24/7 managed support for on-premise Kubernetes environments, including all routine operational tasks and incident management.

The economics depend heavily on existing infrastructure investment and utilisation. Organisations with significant on-premise hardware capacity often find on-premise Kubernetes significantly cheaper than cloud for high-utilisation workloads — but this advantage diminishes for workloads with variable or unpredictable demand, where cloud autoscaling provides cost efficiency that fixed on-premise infrastructure cannot match. We can help you model the total cost of ownership for each approach for your specific situation.