The debate between virtualization and containers has been at the centre of IT architecture decisions for years. Some teams migrate everything to containers, convinced that VMs are a relic of the past; others distrust containers and keep their entire infrastructure virtualized. The reality is that both technologies solve different problems and that the optimal decision depends on the use case, security requirements and the operational maturity of the organisation.
In this article we explain how each isolation model works, compare their characteristics in a detailed table, analyse when VMs are the right choice, when containers win and when a hybrid approach is best, and describe how EasyDataHost supports both technologies on its cloud platform.
What Is Virtualization
Virtualization allows multiple complete operating systems to run on a single physical server. A hypervisor sits between the hardware and the virtual machines (VMs), assigning each VM its own isolated CPU, memory, disk and network resources. Each VM includes its own kernel, drivers and user space, behaving as an independent server.
There are two main types of hypervisor:
- layers Type 1 (bare-metal): runs directly on the hardware without a host operating system. Examples: Proxmox VE (KVM), VMware ESXi, Microsoft Hyper-V. Delivers the best performance and the strongest isolation.
- layers Type 2 (hosted): runs as an application inside a host operating system. Examples: VirtualBox, VMware Workstation. Easier to install but with higher overhead. Suitable for local development, not for production.
The isolation provided by virtualization is at the hardware level: each VM has its own memory page tables, its own network stack and its own kernel. A crash or vulnerability inside one VM does not affect the others or the hypervisor. This model is the foundation of the VPS and Cloud IaaS infrastructure offered by hosting providers.
What Are Containers
Containers are execution units that package an application together with all its dependencies (libraries, configuration, binaries) into a portable image. Unlike VMs, containers share the host operating system's kernel and use Linux kernel mechanisms (namespaces, cgroups, seccomp) to isolate processes, networks and file systems.
Docker popularised containers from 2013 onward, but the ecosystem has evolved towards open standards. The Open Container Initiative (OCI) defines the image and runtime specifications that guarantee interoperability between tools. Today you can build images with Docker, Buildah or Kaniko and run them with containerd, CRI-O or any OCI-compatible runtime.
Because they do not require their own kernel or a full operating system, containers start in milliseconds, consume a fraction of the memory of a VM and allow tens or hundreds of instances to run on a single server. This efficiency makes them the natural choice for microservices architectures, CI/CD pipelines and high-density deployments.
Comparison Table: VMs vs Containers
The following table summarises the key differences between virtual machines and containers across the aspects that matter most in production:
| Criterion | Virtual Machines | Containers |
|---|---|---|
| Isolation | Hardware (hypervisor + own kernel) | Shared kernel (namespaces + cgroups) |
| Overhead | High (full OS, 512 MB-2 GB RAM minimum) | Minimal (process + libraries only, ~10 MB) |
| Boot time | Seconds to minutes | Milliseconds to seconds |
| Density | Tens of VMs per server | Hundreds or thousands per server |
| Security | Strong (hypervisor barrier) | Good (depends on configuration and runtime) |
| Orchestration | Proxmox, vCenter, OpenStack | Kubernetes, Docker Swarm, Nomad |
Container Runtimes
The runtime is the component that actually executes containers on the operating system. The ecosystem has matured towards a clear separation between high-level and low-level runtimes:
- terminal containerd: a high-level runtime donated by Docker to the CNCF. It manages the complete container lifecycle (images, execution, storage, networking). It has been the default runtime in Kubernetes since version 1.24.
- terminal CRI-O: a high-level runtime designed exclusively for Kubernetes. Lighter than containerd as it does not include functionality outside the Kubernetes scope. Widely used in OpenShift.
- terminal runc: a low-level runtime (OCI runtime) that creates the kernel namespaces and cgroups. Both containerd and CRI-O delegate actual execution to runc by default.
- terminal gVisor / Kata Containers: sandboxed runtimes that isolate containers with an intermediate kernel (gVisor) or a microVM (Kata), bringing container security closer to that of a VM.
Orchestration: Kubernetes as the Standard
Running containers on a single server is straightforward. The challenge appears when you need to manage hundreds of containers distributed across multiple nodes: automatic scaling, load balancing, self-healing, rolling updates and secrets management. This is what Kubernetes (K8s) is for -- the container orchestrator that has become the de facto industry standard.
Kubernetes abstracts the underlying infrastructure and exposes a declarative API: you describe the desired state (number of replicas, resources, network policies) and K8s takes care of materialising and maintaining it. If a node fails, Kubernetes reschedules the affected pods on other healthy nodes. If traffic increases, the Horizontal Pod Autoscaler scales replicas automatically.
Deploying Kubernetes on bare metal or in the cloud is an important architectural decision. On dedicated servers you get maximum performance and control, while on cloud VMs you gain elasticity and simplified management.
When VMs Are the Best Choice
Virtual machines remain the right choice in numerous scenarios that containers do not cover adequately:
- shield Multi-tenancy with strong isolation: when multiple customers share infrastructure and a robust security boundary between them is required. The hypervisor provides an isolation barrier that Linux namespaces cannot match.
- desktop_windows Heterogeneous operating systems: when you need to run Windows, FreeBSD or specific Linux kernels that are not compatible with standard Linux containers.
- database Stateful databases: stateful workloads requiring direct disk access, predictable I/O performance and advanced memory management. PostgreSQL, Oracle and SAP HANA benefit from the isolation and guaranteed resources of a VM.
- gavel Regulatory compliance: regulations such as PCI-DSS or ISO 27001 that require hypervisor-level isolation for sensitive data or payment environments.
When Containers Are the Best Choice
Containers dominate in scenarios where speed, density and portability are the priority:
- account_tree Microservices: applications decomposed into small, independent services that are deployed, scaled and updated individually. Each microservice in its own container with its own lifecycle.
- rocket_launch CI/CD and DevOps: continuous integration and deployment pipelines where each step runs in an ephemeral container. Build, test, scan and deploy in containers guarantee reproducible and disposable environments.
- bolt Rapid horizontal scaling: stateless web applications that need to scale from 10 to 1,000 instances in seconds during traffic spikes. Kubernetes with HPA handles this natively.
- swap_horiz Portability across environments: the same OCI image runs identically on the developer's laptop, in staging and in production, eliminating the classic "it works on my machine" problem.
Hybrid Approach: VMs + Containers
In practice, most production infrastructures use a hybrid approach that combines VMs and containers at different layers. The most common pattern is to run Kubernetes on virtual machines: each K8s node is a VM that provides hypervisor-level isolation, while multiple pods with containers run inside each VM.
This model combines the best of both worlds: the robust isolation of VMs to separate environments (production vs staging, customer A vs customer B) with the efficiency and speed of containers for deploying applications. Databases can run on dedicated VMs with high-performance disks, while the application's microservices run in containers orchestrated by Kubernetes.
Recommended pattern:
Use VMs as the environment isolation unit (hypervisor) and containers as the application deployment unit (Kubernetes). The VM provides the security boundary; the container provides portability and deployment speed.
Security Considerations
Security is the factor that most differentiates VMs and containers. A VM has a clear isolation boundary: the hypervisor. A vulnerability inside the VM must escape the guest kernel and the hypervisor to affect the host or other VMs. Hypervisor escape vulnerabilities exist but are extremely rare.
Containers share the host kernel. A privilege escalation vulnerability in the kernel can compromise all containers on the server. To mitigate this risk, best practices include: running containers as a non-root user, enabling AppArmor/SELinux profiles, using restrictive seccomp profiles, limiting kernel capabilities, scanning images for CVEs and keeping the host kernel up to date.
For workloads that require VM-level isolation with the agility of containers, technologies such as Kata Containers and gVisor offer a middle ground: each container runs inside a microVM or a sandboxed kernel, combining the container API with hypervisor-level isolation.
EasyDataHost: Proxmox VMs + Container Support
EasyDataHost's cloud platform is built on Proxmox VE with the KVM hypervisor, enabling VMs with hardware-level isolation and native performance. Every VPS and every Cloud IaaS instance runs as a full KVM virtual machine with its own kernel, dedicated resources and Ceph NVMe storage with triple replication.
Inside each VM, customers can freely deploy containers: Docker, Podman, Kubernetes, K3s or any OCI runtime. Proxmox also supports native LXC containers for workloads that need the efficiency of a container with more direct hardware access. The result is an infrastructure that combines the robust isolation of virtualization with the flexibility of containers.
- check_circle KVM VMs with hardware isolation: type 1 hypervisor on dedicated enterprise servers.
- check_circle Native LXC containers: available as a lightweight alternative to full VMs in Proxmox.
- check_circle Kubernetes on VMs: deploy K8s on cloud instances with Ceph persistent storage.
- check_circle Managed services: configuration, monitoring and maintenance of virtualized and containerized environments.
Conclusion
Virtualization and containers are not rival technologies but complementary ones. The key lies in understanding the strengths of each model and applying the most suitable one to each layer of the infrastructure. Virtualization provides robust isolation and multi-OS support; containers deliver speed, density and portability. The hybrid approach combines both virtues.
- arrow_right VMs offer hardware-level isolation: own kernel, hypervisor as a barrier, ideal for multi-tenancy.
- arrow_right Containers share the kernel and boot in milliseconds: optimal for microservices and CI/CD.
- arrow_right Kubernetes is the standard orchestrator for containers at scale, with self-healing and automatic scaling.
- arrow_right The hybrid approach (K8s on VMs) combines hypervisor isolation with the agility of containers.
- arrow_right EasyDataHost supports both technologies: KVM VMs on Proxmox with native LXC container and K8s support.
If you need to design an infrastructure that combines virtualization and containers, contact our team to define the architecture that best fits your workloads.