Containers in Your Hypervisor vs. VMs in Kubernetes: What’s the Difference?

When talking about modern infrastructure, there are multiple ways to combine virtualization and Kubernetes. I’ll focus on three common approaches:

1. Kubernetes running directly on the hypervisor alongside traditional VMs.
2. Kubernetes running inside VMs on a hypervisor.
3. VMs running inside Kubernetes (via KubeVirt).

1. Kubernetes Directly on the Hypervisor

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In this model:

• The hypervisor runs traditional VMs for legacy workloads.
• A Kubernetes cluster runs directly on the hypervisor to manage containers as pods.
• Pods can represent cloud-native applications without requiring an extra VM layer.

Diagram:

flowchart TB
  classDef node fill:#ADD8E6,stroke:#333,stroke-width:2px;
  classDef pod fill:#90EE90,stroke:#333,stroke-width:1px;

  A["Physical Server"] --> B["Hypervisor"]
  B --> C["VM: Full OS"]
  B --> K["K8s Node(s)"]
  K --> P1["Cloud Native App A"]
  K --> P2["Cloud Native App B"]

  class C,K node;
  class P1,P2 pod;

Figure 1: Hypervisor model. A traditional VM runs a full OS (light blue), and a Kubernetes cluster (light cyan node) runs directly on the hypervisor managing multiple cloud-native app pods (light green). Network isolation is possible depending on hypervisor and CNI configuration. This setup allows for common management of both traditional VMs and Kubernetes nodes.

Key points:

• Kubernetes nodes run directly on the hypervisor, alongside other VMs.
• Provides common management with other hypervisor workloads — everything can be managed through the same hypervisor tools.
• Pods run directly on cluster nodes on the hypervisor.
• Isolation depends on hypervisor networking and CNI configuration; snapshots/migration can be more complex.

2. Kubernetes Inside VMs

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Some organizations prefer to run Kubernetes inside VMs on a hypervisor:

• Hypervisor provides VMs with full OS isolation.
• Kubernetes runs inside one or more of these VMs.
• Pods run inside the Kubernetes cluster, which itself is inside VMs.

Diagram:

flowchart TB
  classDef node fill:#ADD8E6,stroke:#333,stroke-width:2px;
  classDef pod fill:#90EE90,stroke:#333,stroke-width:1px;

  A["Physical Server"] --> B["Hypervisor"]
  B --> VM1["VM 1: K8s Node"]
  B --> VM2["VM 2: K8s Node"]
  VM1 --> P1["Cloud Native App A"]
  VM2 --> P2["Cloud Native App B"]

  class VM1,VM2 node;
  class P1,P2 pod;

Figure 2: Kubernetes cluster running inside VMs. Each VM (light blue) contains a Kubernetes node which manages pods (light green). Network isolation is strong due to VM boundaries.

Key points:

• Adds an extra layer of isolation using VMs.
• Useful for multi-tenant environments or when compliance requires OS-level separation.
• Slightly more complex infrastructure compared to running Kubernetes directly on the hypervisor.

3. VMs Inside Kubernetes (KubeVirt)

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Kubernetes becomes the control plane and manages VMs as workloads using KubeVirt:

• Kubernetes manages both pods (containers) and VMs.
• VMs can host traditional workloads or cloud-native applications.
• This unifies management under Kubernetes for hybrid workloads.

Diagram:

flowchart TB
  classDef node fill:#ADD8E6,stroke:#333,stroke-width:2px;
  classDef pod fill:#90EE90,stroke:#333,stroke-width:1px;

  X["Physical Server"] --> Y["Kubernetes Cluster"]
  Y --> P["Pod: Cloud Native App"]
  Y --> Q["Pod: VM (KubeVirt)"]
  Q --> Q1["Legacy App"]

  class Y,Q node;
  class P,Q1 pod;

Figure 3: VMs managed as pods inside a Kubernetes cluster. Pod container is light green, VM node light blue, Cloud Native App highlighted in gold.

Choosing the Right Model

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Workload Considerations

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• Traditional VMs primary workload: Option 1 or 2 might be better.
• Cloud-native container primary workload: Option 3 is likely more suitable.
• Consider management, isolation, and operational complexity.

Networking Considerations

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Takeaway: Network setup should reflect isolation, security, and workload requirements.

Network Comparison

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flowchart TB
  classDef node fill:#ADD8E6,stroke:#333,stroke-width:2px;
  classDef net fill:#90EE90,stroke:#333,stroke-width:1px;

  O1["Kubernetes in Hypervisor"]
  O2["Kubernetes in VMs"]
  O3["VMs in Kubernetes (KubeVirt)"]

  O1_N["Pods → Hypervisor network (CNI)"]
  O2_N["Pods → VM network → Hypervisor"]
  O3_N["Pods & VMs → Kubernetes overlay network"]

  O1 --> O1_N
  O2 --> O2_N
  O3 --> O3_N

  class O1,O2,O3 node;
  class O1_N,O2_N,O3_N net;

Figure 4: Simplified networking comparison. Light blue = nodes/VMs, light green = pod/VM networking layers.

Summary

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There are multiple ways to deploy containers and VMs, each with different trade-offs:

• Kubernetes in Hypervisor: Simplest management alongside traditional VMs; network isolation depends on CNI.
• Kubernetes in VMs: Strong isolation via VM boundaries; slightly more complex setup.
• VMs in Kubernetes (KubeVirt): Unified control plane for containers and VMs; advanced networking setup.

Before selecting a deployment model, carefully consider:

• Primary workload type: Traditional VMs vs. cloud-native containers.
• Isolation and security requirements: VM boundaries, network segmentation, CNI configuration.
• Operational complexity: Management tools, snapshots, migrations, and networking setup.

No single approach fits every scenario — the right choice depends on workload, expertise, and infrastructure goals.