> ## Documentation Index > Fetch the complete documentation index at: /docs/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > Agent home for Datum, with what it is, pricing, and how to act: https://agents.datum.net > If you can only fetch URLs: read https://www.datum.net/docs/llms.txt in full and open the most specific page for the task. Commands, limits, and field paths are on task, operations, and limits pages, not on section overviews. Pages described as "Documentation is coming soon" are placeholders. > If you have a shell or can save files: download https://www.datum.net/docs/llms-full.txt (every page, about 740 KB) once and search it with grep, instead of fetching pages one at a time. > datumctl describes itself: `datumctl api-resources` lists resource types and `datumctl explain ` shows a schema. To act on live resources, use Datum MCP or datumctl. To search the docs, use the Docs MCP server at https://www.datum.net/docs/mcp. # Deploy an app > Deploy draw.io to Datum Compute and open it in your browser through an Application Load Balancer that Datum attaches for you. > [!NOTE] > > Compute is in preview. The `v1alpha` APIs can change, and Datum reviews Compute access requests manually. ## Before you begin * Create a Datum Cloud account, an organization, and a project. For more information, see [Account setup](/docs/getting-started/account-setup.md). * Install `datumctl`. For more information, see [Install](/docs/datumctl/install.md). * Run `datumctl login`. For more information, see [Logging in](/docs/datumctl/auth/logging-in.md). * Run `datumctl plugin install compute`. For more information, see [Using plugins](/docs/datumctl/plugins/using-plugins.md). * Select the project to deploy in with `datumctl ctx use your-org-id/your-project-id`. To confirm your account and project, run `datumctl whoami`. For more information, see [Contexts and scoping](/docs/datumctl/contexts-and-scoping.md). * Make sure that Compute access is active for the project. Run `datumctl compute access` and check that the `Status` line shows `Active`. If it doesn't, see [Request Compute access](/docs/compute/limits-and-quotas.md#request-access). ## Deploy draw\.io This page deploys [draw.io](https://www.drawio.com/), an open source diagramming app, using the official `docker.io/jgraph/drawio` image with the `general-purpose` runtime class, which runs standard container images without changes. The app fits in one Instance (1 vCPU and 2 GiB of memory), stores nothing on the Instance, and needs no passwords or config files. **1. Deploy draw\.io** To deploy draw\.io to Dallas (`us-central-1`) and publish it on a public URL, run the following command: ```bash theme={null} datumctl compute deploy drawio \ --image=docker.io/jgraph/drawio:31.4.6 \ --runtime-class=general-purpose \ --location=us-central-1 \ --http-port=8080 ``` The flags do the following: * `--image`: the container image to run, pinned to a draw\.io release. Compute requires the registry host in the image reference, such as `docker.io`. * `--runtime-class=general-purpose`: runs the image as a standard container in a lightweight virtual machine. Without this flag, Datum uses the `unikernel` class, which needs a [specially packaged image](/docs/compute/runtimes/unikernels.md). To compare the two, see [Choose a runtime class](/docs/compute/runtimes/overview). * `--location=us-central-1`: runs one Instance in Dallas. * `--http-port=8080`: attaches an ALB to the workload and publishes port `8080`, where draw\.io serves HTTP. The command asks you two questions: 1. The first time you deploy in a project, it asks whether to create a network named `default`. Enter `y`. 2. It prints a plan and asks `Apply? (Y/n)`. Enter `y`. The command then creates the workload, waits for the Instance to start, and publishes the URL. The end of the output is similar to the following: ```text theme={null} Rollout complete in 22s. Publishing... Backends 1 healthy across us-central-1 Edge programmed Certificate issued https://peril-oven-p53hn.datumproxy.net ``` The last line is the hostname of the ALB attached to the workload. Your hostname is different. The command also saves the workload definition to `workload.yaml` in the current directory. **2. Check that draw\.io is available** To list the workloads in your project, run the following command: ```bash theme={null} datumctl compute workloads ``` Continue when `HEALTH` is `Available` and `READY` is `1/1`. The `URL` column shows the ALB hostname from the deploy output. **3. Open draw\.io and draw a diagram** In your web browser, go to the URL from the deploy output. Datum's ALB serves draw\.io over HTTPS, and the app opens a blank diagram. If the browser can't find the site, wait a minute and try again. Click the rectangle in the **General** shape panel, double-click it, and type `Hello from Datum`. To keep it, click **File** > **Export as** > **PNG...**. The editor runs in your browser, so your diagrams stay with you even when Datum restarts or replaces the Instance. **4. Optional: See the Instance** To list the workload's Instances, run the following command: ```bash theme={null} datumctl compute instances --workload=drawio ``` The `INTERNAL IP` column shows the Instance's private IPv6 address on the `default` [gVPC](/docs/galactic-vpc/overview.md) network. The Instance has no public address, so traffic from the internet reaches draw\.io only through the ALB. ## Clean up 1. To delete the draw\.io workload, its Instance, and its ALB, run the following command and enter `y` to confirm: ```bash theme={null} datumctl compute destroy drawio ``` 2. Delete `workload.yaml` from the current directory. 3. Optional: If this tutorial created the `default` network and no other workload uses it, delete the network: ```bash theme={null} datumctl delete network default ``` ## What's next * To deploy your own image, check that your app listens on IPv6 and serves plain HTTP. During the preview, Instances have no persistent disks and no readiness checks. For details, see [Compute limitations](/docs/compute/limitations-and-roadmap.md#limitations). * To pass configuration and secrets to a workload, see [Compute configuration](/docs/compute/configuration.md). * To package your own app as a fast-starting unikernel, see [Unikernels](/docs/compute/runtimes/unikernels.md). * To run in more locations or with more Instances, see [Placement and scaling](/docs/compute/placement-and-scaling.md). * To learn how Datum's control plane turns your resources into running Instances, DNS, and load balancers, see [Platform API](/docs/platform/kubernetes.md). This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.