What Is Bare Metal Kubernetes? Benefits, Tradeoffs, & Use Cases

Kubernetes has become the default platform for container orchestration. According to the CNCF 2025 Annual Report, 82% of organizations are using Kubernetes in production.

At the same time, performance and cost pressures are pushing more teams to rethink where their workloads should run. Many are looking beyond hyperscaler cloud platforms and exploring bare metal infrastructure, with 87% of decision-makers expecting to pursue some form of repatriation within the next two years.

Together, these trends are driving more organizations to consider bare metal Kubernetes as a way to maximize the performance, control, and cost-efficiency of running their containerized applications. 

In this guide, we’ll break down the fundamentals of bare metal Kubernetes, cover the benefits and tradeoffs of this model compared to cloud-based or managed Kubernetes, and help you determine if it’s the right option for your next deployment.

What is bare metal Kubernetes?

Bare metal Kubernetes refers to running Kubernetes directly on physical servers, instead of on virtual machines (VMs). With bare metal Kubernetes, the node operating system (OS) is installed on the server hardware itself, and Kubernetes runs on top of that OS.

A Kubernetes cluster on bare metal is typically composed of multiple nodes running directly on physical servers. These nodes work together, with some nodes managing the cluster and others running application workloads.

The underlying bare metal infrastructure can live in an on-premises data center, a colocation facility, or with a bare metal server provider.

What are the benefits of Kubernetes on bare metal?

Depending on the workload, running Kubernetes on bare metal can offer more consistent performance, greater infrastructure control, and better cost predictability than self-managed Kubernetes on virtual machines or managed Kubernetes services like Amazon EKS.

This is because when Kubernetes runs on cloud infrastructure, the node OS runs inside a virtual machine. There is a hypervisor layer between the Kubernetes node and the underlying physical hardware. That introduces a few potential constraints:

• The hypervisor adds a layer of abstraction between the Kubernetes nodes and the underlying CPU, RAM, storage, and networking resources.

• The hypervisor itself consumes some hardware resources, commonly referred to as virtualization overhead.

• In shared cloud environments, multiple VMs may run on the same physical machine, which can create resource contention under load.

With Kubernetes on bare metal, there is no hypervisor. Kubernetes runs directly on the physical server OS. All nodes get dedicated, direct access to their server’s compute, memory, storage, and network capacity. 

That translates to some key advantages for teams running Kubernetes in production:

Latency-sensitive workloads

Running Kubernetes on bare metal can mean fewer sources of variability in latency. In cloud environments, the slowest requests are often affected by shared infrastructure, virtualization overhead, network congestion, storage I/O delays, or throttling. 

In a Kubernetes cluster, that variability can show up as inconsistent pod performance, slower service-to-service communication, delayed responses, or unpredictable throughput under load.

With bare metal, there is no neighboring VM competing for the same physical resources, and no virtualization layer sitting between the application and the server. With those factors no longer in the equation, the latency and throughput of your nodes become easier to tune, control, and reason about.

Compute-intensive workloads

For compute-intensive workloads, bare metal can help teams get more value from the hardware they pay for. 

Because the server is dedicated to a single tenant, the workload can use more of the available CPU and memory, as well as any GPU capacity, without sharing the underlying hardware with other tenants. 

For long-running, resource-heavy applications, this can lead to more predictable performance and higher hardware utilization, meaning more of the server’s available capacity is being used by the workload instead of sitting unused or being lost to virtualization overhead.

Bandwidth-heavy workloads

For bandwidth-heavy workloads, the biggest advantage often shows up in cost predictability. Cloud platforms can become expensive when applications move large amounts of data, especially when that traffic leaves the cloud environment and is billed as egress fees.

Running Kubernetes on bare metal can help teams bring those costs under control. With a bare metal provider that includes unmetered bandwidth, they can run high-traffic Kubernetes workloads without data transfer fees turning into a major cost driver.

Bare metal Kubernetes architecture: what a cluster needs

A bare metal Kubernetes cluster is built from physical servers that work together as one environment. Each server acts as a Kubernetes node.

In a typical production setup, the cluster includes two main types of nodes:

• Control plane nodes manage the cluster. They track the desired state of the environment, schedule workloads, coordinate activity across nodes, and expose the Kubernetes API.

• Worker nodes run the actual application workloads. These are the servers where Kubernetes places pods and containers.

A simple bare metal Kubernetes cluster might be set up like this:

It is technically possible to schedule application workloads on control plane nodes, which means a bare metal Kubernetes cluster could be as small as a single physical server.

That may be fine for experimentation, testing, or small non-critical deployments. Generally, however, it’s not recommended for production, as it can result in control plane and worker components competing for the same server resources and create unnecessary availability risk.

In production, teams often use multiple control plane nodes so the cluster can maintain quorum and continue operating if one control plane server fails. Worker node redundancy matters for the same reason. If one worker node goes offline, Kubernetes needs enough remaining capacity to reschedule workloads elsewhere.

Keep in mind, servers are only part of the architecture. A production bare metal Kubernetes environment also needs additional setup around the cluster, including:

• Networking between nodes

• Load balancing for traffic entering the cluster

• Persistent storage for stateful workloads

• Backups

• Remote management access

• Planning for hardware maintenance or failure.

Accounting for these requirements makes bare metal Kubernetes more involved than using a managed Kubernetes service from a provider. But for teams with the right needs and competencies, that added responsibility can be worth it.

Bare metal Kubernetes vs. self-managed Kubernetes on cloud VMs vs. managed Kubernetes

Bare metal Kubernetes is just one way to run a Kubernetes cluster. You can also self-manage Kubernetes on cloud VMs or use a managed Kubernetes service like Amazon EKS, Google Kubernetes Engine, or Azure Kubernetes Service.

Determining which model is best-suited for your use case will depend on the amount of control and operational responsibility you’re comfortable taking on. 

Here’s a quick rundown of each deployment type:

Challenges of running Kubernetes on bare metal

Bare metal Kubernetes can be a strong fit for demanding workloads. That said, it’s usually not the lowest-effort way to run Kubernetes. While this model gives teams more control over the infrastructure layer, as expected, that comes with more responsibility.

Here are a few of the challenges your team should be prepared to handle: 

• Control plane availability: In a managed Kubernetes service, the provider usually runs the control plane. On bare metal, that responsibility is yours. You need to plan for control plane redundancy, etcd backups, upgrades, and recovery if a control plane node fails.
  
  

• Networking and load balancing: Cloud platforms often package private networking, firewall rules, service exposure, and load balancers into the environment. Bare metal clusters still need those pieces, but you are responsible for designing how nodes communicate, how traffic enters the cluster, and how services are exposed.
  
  

• Storage: Stateful workloads need a plan for persistent volumes, replication, backups, and recovery. You’ll need to decide whether storage should live locally on the physical server, come from a networked storage system, or use another architecture.
  
  

• Hardware failure and maintenance: Kubernetes can reschedule workloads when a node fails, but the physical server still needs to be monitored, accessed, repaired, or replaced. You need to maintain enough spare capacity to keep workloads running during failures or planned maintenance.
  
  

• Scaling: In the cloud, adding capacity can often happen through an API call to provision more instances. With bare metal, adding capacity usually means adding physical servers or provisioning more dedicated servers from a provider. That makes capacity planning more important, especially for workloads with sharp growth or uneven traffic patterns.
  
  

• Team expertise: Teams with existing competencies in Kubernetes, Linux, networking, monitoring, and incident response will have an easier time with bare metal Kubernetes than those without. 

Despite these challenges, bare metal Kubernetes remains an attractive option for many teams. The benefits of dedicated infrastructure, predictable performance, and clearer cost control can be well worth this added operational responsibility.

When bare metal Kubernetes is the right choice

As more and more organizations turn to Kubernetes for their container orchestration needs, running Kubernetes on bare metal infrastructure has emerged as an important option to consider.

The best way to decide if it’s the right option for you is to assess both your workload requirements and your team’s operational capacity. For teams with demanding workloads, especially those that are latency-sensitive, compute-intensive, or bandwidth-heavy, running Kubernetes on bare metal can offer a level of performance, predictability, and control that simply can’t be replicated any other way. 

If you’re considering a bare metal Kubernetes deployment, Rackdog can provide a high-performance infrastructure layer for your nodes. With Rackdog, you can deploy dedicated bare metal servers from 12+ global locations, provision in minutes via API or Terraform, and run on flat monthly pricing with no egress fees.

Get in touch with our team to discuss a bare metal solution for your Kubernetes deployment. We can help assess your workload needs, plan your deployment, and design a custom infrastructure solution built around your cluster.