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.- 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.
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:Key concepts
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 withdatumctl compute build.
unikernel. For a detailed comparison, see Choose a runtime class.
Ways to work with Compute
datumctl compute: Adatumctlplugin 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, anddatumctl describe, or with GitOps tooling. For more information, see Kubernetes.
What’s next
Deploy an app
Deploy draw.io with one command and open 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.
Operations
Check status, update, and delete workloads.
Troubleshooting
Fix common errors and Instance failures.
Observability
View CPU and memory metrics, Instance output, and ALB access logs.
Instance shell
Open an interactive shell from the Cloud Portal or run a command with
datumctl.Limits and quotas
Request access, check quota, and review fixed limits.
Limitations and roadmap
Review what the preview doesn’t support yet.
gVPC
Create private networks and attach workloads to them.
Private DNS
Reach Instances by private name instead of IP address.