Sovereign AI is not something you add at the end of a system. It changes what your infrastructure has to support once customers, auditors, or procurement teams start asking questions you can’t ignore.
Containers alone often fall short at that point. They are excellent for speed and repeatability, but sovereignty conversations tend to surface requirements around OS control, operational evidence, and predictable administration. That’s where virtual machines stop being optional and become the practical baseline.
On Compute, you can run both containers and virtual machines (VMs). Containers keep iteration fast. VMs give you a full server-shaped environment when sovereignty stops being abstract.
Sovereignty starts with the provider, but shows up in operations
Sovereignty is mainly about jurisdiction and control. It depends on who operates the platform, where contracts sit, and which legal regimes apply. Choosing a container or a VM does not change those fundamentals.
What the runtime choice does affect is how you operate under scrutiny. Sovereignty rarely appears as a legal debate. It shows up as due diligence, incident response expectations, and audit questions that require clear, repeatable answers.
What reviewers usually look for
Security and compliance reviews tend to follow a familiar pattern. The focus is less on the technology label and more on whether control can be exercised and demonstrated.
Reviewers typically want to know whether you can administer the environment at the OS level, run required security and monitoring tooling, produce a clear record of configuration and access, explain isolation boundaries without special cases, and investigate incidents without rebuilding the system first.
These questions can be answered with containers, but doing so often requires extra design work and explanation. VMs usually make the path shorter.
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Containers optimize for speed
Containers are designed to start quickly, run a defined workload, and be replaced rather than repaired. They share the host kernel and work best when the environment is image-defined and disposable.
This model fits job-shaped work well. Training runs, evaluation jobs, batch inference, and burst workloads all benefit from fast startup and reproducibility, with the container image acting as the reference point.
Containers become less comfortable when teams expect to manage the environment like a machine. At that point, the runtime and the operational model are no longer aligned.
VMs fit how sovereignty requirements are written
A VM provides a full guest operating system that you manage like a traditional server. That matters because most sovereignty-driven requirements are framed in server terms: OS configuration, system services, host-level tooling, administrative access, and audit evidence.
VMs tend to be the right choice when production systems rely on long-running services, when deployments assume a conventional server lifecycle, when OS-level security or monitoring agents are required, when system-level dependencies need tuning, or when an existing VM-based setup is being migrated without a full redesign.
VMs are not inherently more compliant. They are simply easier to operate and easier to explain when sovereignty becomes contractual or audited. Fewer exceptions usually mean fewer points of friction.
Where containers still make sense
Taking sovereignty seriously does not mean avoiding containers. It means using them where they reduce effort instead of adding it.
Containers remain a strong fit when workloads are short-lived, when fast iteration for experimentation and training matters, when reproducibility through versioned images is the priority, and when work scales horizontally in a job-based way.
In practice, a simple rule holds up well: use containers for fast loops and batch work, and VMs for production services that need to stand up to scrutiny.
Using both without adding complexity
Most teams settle into a predictable split.
Containers handle experimentation, evaluation, and burst workloads. VMs handle production services and anything that requires OS-level control.
Two habits keep this manageable. First, treat VM changes deliberately. Persistent systems can drift, and drift becomes a risk when sovereignty reviews are part of the process. Second, stop forcing workloads into the wrong model. If a container setup requires constant workarounds, that’s a signal. Move the workload to a VM and move on.
VM OS options on Compute
When launching a VM on Compute, you choose a standard Linux distribution image. Available options include Ubuntu 22.04 LTS, Fedora 41, and Debian 12. Familiar base systems help keep behavior consistent across development, staging, and regulated production environments.Keep your AI stack sovereign
Sovereignty is enforced through scrutiny. If an infrastructure setup cannot answer basic operational and control questions cleanly, the label does not hold.
That is why VMs matter. They reduce exceptions, reduce redesign work, and make audits less fragile. Containers still have a clear role, especially for fast iteration and job-shaped workloads. Compute supports both so teams can choose the right model per workload and keep moving when sovereignty stops being optional.\
