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Datum Cloud Compute runs your app close to your users. You describe what to run and where, and Datum starts isolated Instances in the locations you choose, connects them to a private network, and can serve them publicly through Datum’s Application Load Balancer (ALB).
Compute is in preview, and the v1alpha API can change. Your project needs approved access to Compute before you can deploy, and Datum reviews access requests manually. For details, see Limits and quotas.
Every Instance runs in its own virtual machine with its own kernel. No kernel is shared between tenants. Compute is a good fit if you want to:
  • Run an HTTP service or API in more than one location without operating servers.
  • Deploy a container image you already build, with virtual machine isolation.
  • Start small, purpose-built services in a fraction of a second as unikernels.

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How it works

You create a workload. A workload holds a template for the Instances you want (image, command, environment variables, and ports) and one or more placements that say where to run them and how many to run in each location. For each location in a placement, Datum starts the requested number of Instances there. Every Instance attaches to a network in your project and receives a private IPv6 address. To reach a workload from the internet, attach Datum’s Application Load Balancer (ALB) to it. The following diagram shows a workload with one placement in two locations:
Each Instance reports its own status, and the workload summarizes the status of its Instances. When something goes wrong, the Instance has the most specific reason.

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Key concepts

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Runtime classes

Compute offers two runtime classes. Both give each Instance its own kernel.
  • General purpose (general-purpose): Runs standard Linux container images without changes. Instances take several seconds to start.
  • Unikernel (unikernel): Runs a specially packaged image as a unikernel that starts in a fraction of a second, with very little overhead per Instance. You package the image with datumctl compute build.
If you don’t name a runtime class, Datum uses unikernel. For a detailed comparison, see Choose a runtime class.

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Ways to work with Compute

  • datumctl compute: A datumctl plugin that deploys, publishes, scales, and deletes workloads with a single command each. The guides in this section use it. For the command reference, see Compute commands.
  • Manifests: Workloads are Kubernetes-style resources. You can write them in YAML and manage them with datumctl apply, datumctl get, and datumctl describe, or with GitOps tooling. For more information, see Kubernetes.

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What’s next

Quickstart

Deploy a container and reach it through Datum’s ALB.

Choose a runtime class

Compare the general-purpose and unikernel tiers.

Run a container image

Run a standard Linux container on general-purpose Instances.

Build and deploy a unikernel

Package your app as a unikernel with datumctl compute build.

Configure a workload

Set environment variables and mount ConfigMaps and Secrets.

Placement and scaling

Choose locations, set Instance counts, and roll out changes.

Publish a workload

Serve a workload with Datum’s ALB, on a generated or custom hostname.

Manage and troubleshoot

Check status, update, restart, and delete workloads.

Limits and quotas

Request access, check quota, and review limitations.

Galactic VPC

Create private networks and attach workloads to them.
Last modified on September 23, 2026