Virtual machines vs containers

What it means

The kernel is the core of an operating system that manages processes and system resources. User space is where applications and libraries run. Separating user-space environments is therefore different from giving each environment its own kernel. This comparison focuses on that distinction, rather than comparing hosting plans or recommending a replacement for an existing deployment.

Try it

Simulation: start with Workload environment = Linux container and Requires separate guest kernel? = no. Change only Requires separate guest kernel? to yes, then inspect the result and its explanation. Select Compare with baseline to display the baseline and current outcomes. This runs locally; it does not inspect or change a deployment.

The initial result is “Shares host kernel.” Its explanation is: “An ordinary Linux container uses the host kernel with user-space isolation mechanisms.” Changing the requirement to yes does not create a new kernel; it exposes that this container model cannot meet the new requirement.

For the first contrast, keep Workload environment = Linux container. Only Requires separate guest kernel? changes, from no to yes.

Reset restores Workload environment = Linux container and Requires separate guest kernel? = no, removes input errors and clears the comparison. It does not change which FAQ answers or the About this model panel you have opened. There is no running clock or stored event history to reset.

How it works

Linux namespaces give processes separate views of selected system resources. Container resource controls can constrain resource use. These mechanisms change the environment presented to a process without creating an independent kernel for it: the ordinary Linux container still relies on the host kernel.

A VM instead provides a virtualized guest environment through a virtualization platform. When that platform supports the guest, the environment can include its own operating system and kernel. That is why a requirement for a separate guest kernel changes the architectural fit: the container model has no separate kernel to provide, while the VM model permits one.

Neither boundary determines the whole deployment. Containers can also run inside a VM, so the labels are not mutually exclusive choices. The question to resolve first is which kernel the workload would use, not which label appears on the service.

Worked example

This is a synthetic baseline, not a captured production observation.

The result is “Shares host kernel.” The explanation is: “An ordinary Linux container uses the host kernel with user-space isolation mechanisms.”

Here, no means that the workload does not require a separate guest kernel. It does not mean that the Simulation has checked every other workload requirement. The result establishes the modeled kernel relationship, not complete compatibility.

What changes when the condition changes

Change Requires separate guest kernel? from no to yes, leaving Workload environment = Linux container. The result becomes “Requirement not met by this container model.” The explanation is: “The described Linux container shares the host kernel, so a separate guest kernel is unavailable.”

The requirement changed; the container architecture did not. This is an architectural mismatch, not evidence that a running container has failed.

For a second contrast, keep Requires separate guest kernel? = yes and change Workload environment to VM. The result becomes “Guest kernel can be separate,” because “A VM can include a guest OS/kernel when supported by the hypervisor.” That makes a VM a possible fit for this requirement, not proof that a particular platform supports the kernel you want.

In practice

For a proposed workload, separate its user-space needs—applications, libraries and files—from any requirement for a particular kernel or kernel feature. Different application dependencies do not, by themselves, establish that the workload needs its own kernel.

Keep the initial assessment read-only: use platform documentation and deployment inventory you are authorized to view. For the specific workload and proposed environment, identify which kernel it would use and what the platform supports. The useful observation is an explicit kernel relationship and support statement, not merely a product label such as “container hosting.”

STOP before choosing a migration or changing isolation, privileges or device access if that relationship is undocumented or unclear. Treat the platform’s suitability as unknown and obtain the missing configuration or support information. This comparison does not authorize or prescribe a deployment change.

Limits and unknowns

The scene evaluates only the two selected teaching inputs. It does not observe a machine, inspect an image, contact a provider or verify an actual kernel. A baseline result does not prove application compatibility, and the VM result does not confirm that a particular guest kernel is supported. No result measures performance, cost, operational simplicity or security.

The model covers ordinary shared-kernel Linux containers, not every product marketed as a container. Specialized execution environments need their own documentation.

If input validation reports an invalid value, no calculated outcome applies until you correct it or use Reset; an earlier valid result must not be treated as current. The supported selections produce architectural results, not a diagnosis of an undocumented deployment. Missing real-world evidence remains unknown even when the local Simulation displays a result.

Without JavaScript, the initial example and explanation remain readable, but the interactive controls do not operate.

What to carry forward

Treat a separate-kernel requirement as an architectural filter: the ordinary shared-kernel Linux container model cannot satisfy it, while a VM may, subject to platform support. If you need only different user-space dependencies, that alone does not establish a need for a separate kernel. Confirm the actual requirement before comparing the remaining operational and security tradeoffs.