Container Orchestration vs. Virtualization: A Matter of Belief?

Anyone who has worked with IT infrastructure for a while has probably encountered this debate: Do we still need virtual machines when containers and Kubernetes can run our applications?

Some administrators prefer traditional virtualization with VMware, Proxmox, or KVM. Others believe that containers and Kubernetes are the future and that every application should be containerized as soon as possible.

However, is container orchestration vs virtualization really a matter of belief? Or are we comparing two technologies designed to solve different problems?

In my opinion, this distinction is often overlooked. Just because Kubernetes offers powerful automation features does not mean every virtual machine should disappear from your infrastructure.

Therefore, in this article, we will examine the technical differences between container orchestration and traditional virtualization. Furthermore, we will compare performance, security, scalability, operational complexity, and real-world use cases.

Most importantly, we will discuss why combining Kubernetes with virtual machines can sometimes be the most practical solution.

Container Orchestration vs Virtualization: Are We Comparing the Right Technologies?

Before discussing advantages and disadvantages, we need to clarify something important.

Virtualization and container orchestration are not exactly the same type of technology.

Traditional server virtualization allows multiple virtual machines to run independently on the same physical hardware. Each virtual machine normally has its own operating system and kernel.

Containerization, on the other hand, isolates applications and their processes while sharing the host operating system kernel.

Container orchestration adds another layer. It automates the deployment, scheduling, scaling, and management of containerized applications across one or more servers.

Consequently, we are actually comparing three different concepts:

• Virtualization: Creating independent virtual computing environments.
• Containerization: Packaging and isolating applications at the operating-system level.
• Container orchestration: Automating the management of containerized workloads.

This distinction is essential because a hypervisor and a Kubernetes cluster perform different tasks.

Therefore, Kubernetes cannot automatically replace every feature of a traditional virtualization platform.

How Does Traditional Virtualization Work?

Traditional virtualization has been a fundamental part of enterprise IT infrastructure for many years.

Platforms such as VMware ESXi, Microsoft Hyper-V, and KVM allow administrators to run multiple virtual machines on a single physical server.

A hypervisor manages access to the underlying hardware and provides virtual resources to each guest system.

These resources typically include:

• Virtual CPUs
• Virtual memory
• Virtual network interfaces
• Virtual disks
• Virtual hardware devices

Each virtual machine normally runs its own operating system. For example, you could run several Linux servers alongside Windows Server instances on the same physical hardware.

Furthermore, each virtual machine can be configured, updated, restarted, and managed independently.

This makes virtualization particularly useful for applications that require a complete operating system environment.

Why Virtual Machines Are Still Relevant

Virtual machines provide several advantages that remain important in modern infrastructure.

First, they offer flexibility when different operating systems are required.

For example, a Windows Active Directory Domain Controller cannot simply be moved unchanged into a standard Linux container.

Similarly, older enterprise applications may depend on specific operating system versions, system services, or software components.

In these situations, running the application inside a virtual machine may be considerably easier than redesigning it for containers.

Moreover, established virtualization platforms often provide features such as:

• Live migration between physical hosts
• High-availability configurations
• Virtual machine snapshots
• Centralized storage integration
• Virtual networking
• Backup and disaster recovery tools
• Resource reservations and limits

Because these technologies have been used for years, many organizations already have stable operational processes around them.

Therefore, replacing a reliable virtualization platform simply because Kubernetes is becoming more popular may not be a reasonable decision.

How Are Containers Different from Virtual Machines?

Containers use a different technical approach.

While virtual machines normally run separate guest kernels, Linux containers share the kernel of the host operating system.

Instead of virtualizing an entire computer, containers isolate application processes.

Under Linux, this isolation relies on several kernel features.

Two especially important components are Linux namespaces and control groups, commonly known as cgroups.

Linux Namespaces

Namespaces provide isolated views of certain operating system resources.

For example, a process running inside a container may see its own process hierarchy, network interfaces, and filesystem mounts.

As a result, the application operates within an environment that appears separated from other workloads.

However, this does not mean the container has its own operating system kernel.

Control Groups

Control groups are responsible for resource accounting and control.

For example, they can restrict how much memory a container may consume or influence its CPU usage.

This becomes particularly important when several applications share the same physical server.

Without appropriate resource management, one application could consume excessive resources and negatively affect other workloads.

Consequently, cgroups are an essential component of reliable container environments.

Why Containers Often Use Fewer Resources

Because containers do not require a complete guest operating system for every application instance, they typically introduce less overhead than traditional virtual machines.

Additionally, many containers start within seconds or even faster because there is no separate operating system to boot.

However, lower overhead does not automatically mean better application performance.

The actual performance depends on the workload, resource allocation, storage system, and network configuration.

Container Orchestration vs Virtualization: A Direct Comparison

The following table summarizes some of the most important technical differences.

At first glance, containers seem to offer several advantages.

Nevertheless, that does not make virtualization obsolete.

For example, virtual machines offer a different isolation boundary and may be better suited for legacy applications.

Ultimately, the correct choice depends on the workload rather than the popularity of the technology.

Where Does Kubernetes Fit into the Picture?

So far, we have mainly compared containers and virtual machines.

However, container orchestration becomes relevant when applications need to be managed automatically across a larger environment.

This is where Kubernetes comes into play.

Kubernetes is an open-source platform for deploying, scaling, and managing containerized applications.

Instead of manually starting containers, you describe the desired state of your application.

Kubernetes then continuously works toward maintaining that state.

For example, imagine you want to run three instances of a web application.

With Kubernetes, you can define those instances in a Deployment.

A simple configuration might look like this:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: webserver
spec:
  replicas: 3
  selector:
    matchLabels:
      app: webserver
  template:
    metadata:
      labels:
        app: webserver
    spec:
      containers:
        - name: nginx
          image: nginx:stable
          ports:
            - containerPort: 80

After saving the configuration as deployment.yaml, you can apply it using:

kubectl apply -f deployment.yaml

Kubernetes processes the configuration through its API server.

Next, the appropriate controllers create the required resources, while the scheduler assigns the Pods to suitable worker nodes.

As a result, Kubernetes attempts to maintain three running instances of the application.

If one Pod is deleted, a replacement is normally created automatically.

However, it is important to understand that Kubernetes cannot guarantee successful recovery when there are insufficient resources or unavailable dependencies.

High Availability: Is Kubernetes Better Than Virtualization?

High availability is often presented as one of the strongest arguments for Kubernetes.

However, traditional virtualization platforms can also provide high-availability capabilities.

For example, if a physical virtualization host fails, an appropriately configured HA platform may restart affected virtual machines on another host.

Kubernetes approaches availability differently.

Instead of focusing primarily on restarting complete machines, Kubernetes manages application workloads through Pods and controllers.

Therefore, if one application instance fails, a replacement Pod can be created without restarting an entire guest operating system.

Furthermore, multiple replicas can run across different nodes.

This allows applications to remain available when individual Pods or nodes fail, provided the application and infrastructure are designed appropriately.

Nevertheless, Kubernetes does not automatically make every application highly available.

Consider a database running as a single Pod with storage that becomes unavailable.

Although Kubernetes may attempt to restart the Pod, it cannot recover missing data or repair an unavailable storage backend on its own.

Consequently, reliable high availability requires more than selecting Kubernetes or VMware.

High availability is the result of good architecture, redundancy, monitoring, and tested recovery procedures.

Resource Efficiency: Are Containers Always Better?

Resource efficiency is another common argument in discussions about container orchestration vs virtualization.

Running ten virtual machines usually means maintaining ten separate guest operating systems.

Each operating system consumes memory, storage, and administrative resources.

Containers, in contrast, share the host kernel.

Therefore, they can reduce the overhead associated with running multiple application instances.

However, Kubernetes introduces its own infrastructure requirements.

A production Kubernetes cluster needs a control plane, networking, DNS, monitoring, and often additional storage components.

Furthermore, administrators must maintain the Kubernetes nodes, container runtimes, and cluster configuration.

For a small environment with only two applications, this overhead may outweigh the benefits.

On the other hand, organizations operating many independently deployed applications can benefit significantly from standardized container orchestration.

As a result, resource efficiency should always be evaluated across the complete infrastructure rather than individual containers.

Security: Virtual Machines vs Containers

Security is one of the most important considerations when choosing an infrastructure platform.

Virtual machines normally have separate guest kernels, providing a different isolation boundary from standard Linux containers.

Containers share the host kernel, which means kernel vulnerabilities may potentially affect multiple workloads.

However, this does not mean containers are inherently insecure.

Linux provides several mechanisms to restrict container capabilities and access.

These include:

• Linux namespaces
• Control groups
• Seccomp profiles
• AppArmor and SELinux
• Linux capabilities
• User namespaces
• Read-only filesystems

Additionally, Kubernetes provides security mechanisms such as Role-Based Access Control, NetworkPolicies, and Pod Security Admission.

Nevertheless, these controls require proper configuration.

For example, privileged containers with excessive permissions may introduce significant security risks.

Likewise, a virtual machine running an outdated operating system with exposed management interfaces can also become a serious security problem.

Therefore, neither technology should be considered secure simply because of its architecture.

Security depends on configuration, patch management, access control, and operational discipline.

Proxmox, VMware, and Kubernetes: Why Not Use Both?

One of the biggest misconceptions in this debate is that organizations must choose either Kubernetes or traditional virtualization.

In reality, both technologies can work extremely well together.

For example, imagine an existing Proxmox or VMware infrastructure.

Instead of replacing the virtualization platform, you could create several virtual machines and use them as Kubernetes nodes.

A possible architecture might include:

• Multiple physical virtualization hosts
• Virtual machines running Kubernetes control plane components
• Additional virtual machines acting as worker nodes
• Containerized applications running inside Kubernetes Pods
• Shared storage and networking infrastructure

In this design, virtualization provides the infrastructure layer.

Kubernetes manages the containerized workloads running on top of it.

Consequently, each platform can focus on what it does best.

However, this approach also introduces additional operational layers.

Administrators must maintain both the virtualization environment and the Kubernetes cluster.

Even so, this can be a reasonable trade-off when an organization already has a mature virtualization infrastructure.

What About Bare-Metal Kubernetes?

Running Kubernetes inside virtual machines is common, but it is not the only option.

Kubernetes can also run directly on physical servers.

This architecture is often referred to as bare-metal Kubernetes.

By removing the virtualization layer, organizations may reduce some infrastructure overhead and gain more direct control over hardware resources.

For example, workloads with specific performance or hardware requirements may benefit from direct access to physical infrastructure.

However, bare-metal environments introduce their own management challenges.

Provisioning, hardware maintenance, node replacement, networking, and storage integration need to be handled appropriately.

Therefore, bare-metal Kubernetes is not automatically simpler than running Kubernetes on virtual machines.

The right choice depends on operational expertise, existing infrastructure, and workload requirements.

KubeVirt: Bringing Virtual Machines into Kubernetes

Another interesting development is KubeVirt.

KubeVirt extends Kubernetes with the ability to manage virtual machines through Kubernetes resources.

Instead of converting traditional virtual machines into ordinary containers, KubeVirt integrates virtualization technologies such as KVM into the Kubernetes environment.

Consequently, organizations can manage virtual machines and containerized workloads through a more unified platform.

For example, an organization migrating from traditional infrastructure may want to modernize applications gradually.

Some services could move into containers, while other applications remain in virtual machines.

KubeVirt provides an approach for managing these different workload types within Kubernetes.

However, this does not eliminate the complexity of virtualization.

Storage, networking, backups, migration, and high availability still require careful planning.

Therefore, KubeVirt should be evaluated as an architectural option rather than an automatic replacement for every established hypervisor platform.

A Practical Example: Choosing the Right Platform

Let’s consider a small company that needs to operate several applications.

The environment includes:

• A Windows Active Directory Domain Controller
• A legacy ERP application
• Several modern web applications
• A REST API
• A monitoring platform
• A relational database

Would I move everything into Kubernetes?

Probably not.

First, I would keep the Windows Domain Controller in an appropriately configured virtual machine.

Similarly, the legacy ERP application might remain on a virtual machine because of its operating system dependencies.

However, the web applications and REST API could be good candidates for containerization.

If these applications require frequent deployments, multiple instances, or automated scaling, Kubernetes could offer significant advantages.

The monitoring platform could also run in containers, although its storage and availability requirements would need attention.

The database deserves a more detailed evaluation.

Running databases on Kubernetes is possible, especially when suitable operators and storage systems are available.

Nevertheless, an external database service or a database running on virtual machines may be easier to operate in some environments.

As a result, the final architecture could contain both Kubernetes and traditional virtual machines.

And there is absolutely nothing wrong with that.

Operational Complexity and Total Cost of Ownership

Technical discussions often focus on performance, scaling, and features.

However, operational costs are equally important.

Traditional virtualization platforms may involve hardware, licensing, storage, backup, and administration costs.

Kubernetes is open source, but operating a Kubernetes cluster is not free.

It requires infrastructure, monitoring, logging, security controls, backups, upgrades, and skilled administrators.

Furthermore, troubleshooting Kubernetes can be challenging when teams lack experience with networking, storage, and distributed systems.

For a company already operating a stable virtualization environment, a complete migration to Kubernetes may initially increase complexity and cost.

On the other hand, Kubernetes can reduce repetitive deployment work in environments with many applications and frequent releases.

Therefore, the decision should consider the entire lifecycle of the infrastructure.

This includes maintenance, staff training, operational risk, and future scalability.

Simply comparing software license prices does not provide a complete picture.

When Would I Choose Virtualization?

Traditional virtualization remains a strong choice in several situations.

For example, I would prefer virtual machines when:

• Different guest operating systems are required.
• Legacy applications depend on specific system configurations.
• A stable virtualization environment already exists.
• Strong separation between complete operating systems is important.
• Only a few applications need to be operated.
• Existing backup and recovery procedures are built around virtual machines.

In these scenarios, containerization may introduce complexity without providing enough additional value.

When Would I Choose Kubernetes?

Kubernetes becomes especially attractive when applications are designed for container-based deployment.

For example, Kubernetes may be the better choice when:

• Many containerized applications need to be managed.
• Frequent automated deployments are required.
• Applications benefit from horizontal scaling.
• Several development teams share an infrastructure platform.
• GitOps and CI/CD are important operational requirements.
• Workloads need to be distributed across multiple nodes.
• Declarative configuration and standardized deployment processes are desired.

However, organizations should still evaluate whether Kubernetes provides enough benefit to justify its operational complexity.

Frequently Asked Questions

Is Kubernetes a replacement for VMware or Proxmox?

Not directly. Kubernetes primarily orchestrates containerized applications, while VMware and Proxmox provide virtualization infrastructure. Although technologies such as KubeVirt extend Kubernetes to manage virtual machines, they do not automatically replace every capability of an established virtualization platform.

Are containers faster than virtual machines?

Containers usually start faster and introduce less operating system overhead. However, actual application performance depends on the workload, storage, networking, and resource configuration.

Can Kubernetes run on virtual machines?

Yes. Kubernetes clusters frequently operate on virtual machines. In this architecture, the virtualization platform provides computing infrastructure, while Kubernetes manages containerized applications.

Is Kubernetes suitable for small businesses?

Yes, but it depends on operational requirements. For a few simple applications, Kubernetes may introduce unnecessary complexity. However, automated deployment and scaling requirements can justify Kubernetes even in smaller organizations.

Can databases run on Kubernetes?

Yes. Databases can run on Kubernetes using appropriate storage configurations and, in some cases, database operators. Nevertheless, backup, recovery, replication, and data consistency must be planned carefully.

Is container orchestration more secure than virtualization?

Neither approach is automatically more secure. Virtual machines and containers use different isolation models. Consequently, security depends on configuration, patch management, permissions, and infrastructure design.

Conclusion: Container Orchestration vs Virtualization Is Not a Matter of Belief

So, which technology is better: container orchestration or virtualization?

The answer depends on what you need to achieve.

Virtual machines remain valuable because they provide independent operating system environments and integrate well with traditional enterprise applications.

Containers, on the other hand, offer a lightweight and standardized way to package and deploy applications.

Kubernetes adds automation, scheduling, scaling, and workload management to containerized environments.

Therefore, these technologies should not be treated as mutually exclusive.

In fact, combining Kubernetes with an existing Proxmox or VMware environment can provide an excellent balance between flexibility and automation.

Likewise, bare-metal Kubernetes may be the right solution when direct hardware access and standardized container deployment are priorities.

My recommendation is simple: Analyze your applications before choosing the platform.

Which workloads really benefit from containers? Which applications still require virtual machines? What operational skills are available, and how much complexity can the organization realistically maintain?

Once those questions are answered, the debate becomes less emotional and much more practical.

The best infrastructure is not necessarily the newest technology. It is the architecture that meets your requirements, remains manageable, and delivers reliable results.

Ultimately, container orchestration vs virtualization should never be a matter of belief. It should be an informed technical decision.

Further Reading

For additional technical information, I recommend the official Kubernetes documentation.

If you are interested in combining Kubernetes with virtual machines, visit the official KubeVirt project.