> For the complete documentation index, see [llms.txt](https://docs.gofigr.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.gofigr.io/managed-compute/quickstart.md).

# Launch Your First Instance

This walks you from an empty workspace to your first published figure on a managed compute instance. Plan for about 5–10 minutes—most of it is the machine provisioning while you grab a coffee.

## 1. Launch an instance

In the GoFigr web app, open the **Compute** view and click **Launch compute instance**. The launch dialog has three short sections:

* **Instance** — give it a **Name** you'll recognize (e.g. *Lung-cancer analysis*).
* **Machine** — pick a **Tier** (machine type) and a data **Volume** size. **Standard** (2 vCPU, 4 GB) is selected by default and is plenty for most notebooks; you can [change it later](/managed-compute/tiers.md). The default volume is 10 GiB.
* **Auto-shutdown** — leave **Auto-stop on idle** on so the machine parks itself when you step away. See [idle auto-stop](/managed-compute/lifecycle.md#idle-auto-stop).

The dialog shows an **Estimated cost** table (hourly, 24/7, and a typical 8 h/day) so there are no surprises. Click **Launch**.

{% hint style="info" %}
**Provisioning takes about 5–10 minutes.** You don't have to wait on the page—we'll email you when the instance is ready. You can watch it move through **Launching → Initializing → Starting services → Running**.
{% endhint %}

## 2. Connect

When the status reaches **Running**, the **Jupyter**, **code-server**, and **R Server** buttons light up. Click one to open that editor in a new browser tab:

* **Jupyter** — JupyterLab, for interactive Python notebooks.
* **code-server** — code-server in the browser, with the GoFigr extension installed.
* **R Server** — for R notebooks, R Markdown, and Quarto.

All three edit the same files, so it doesn't matter which you start with. See [Working in your instance](/managed-compute/working-in-the-workspace.md) for the details of each.

## 3. Run the example and publish a figure

You don't need to configure anything—this machine is **already connected to your GoFigr account**. Your home directory comes seeded with a welcome doc (`START-HERE.md`) and a ready-to-run example.

{% tabs %}
{% tab title="Python" %}
In JupyterLab, open **`examples/tcga_lung_classifier.ipynb`** and run it top to bottom. As it runs, each figure is published to your GoFigr account together with the code, data, and environment that produced it.
{% endtab %}

{% tab title="R" %}
In R Server, open **`examples/tcga_lung_analysis.qmd`**—the same analysis as a Quarto report—and render it. `library(gofigR)` is already installed and configured, so figures publish as the report runs.
{% endtab %}
{% endtabs %}

Open [app.gofigr.io](https://app.gofigr.io) and watch the figures appear in your workspace, each linked to the exact code that created it.

{% hint style="info" %}
New to publishing with GoFigr? The [Quick Start](/getting-started/quickstart.md) explains how capture works. The only difference on a managed instance: there's no `gfconfig` step—it's done for you.
{% endhint %}

## 4. Stop when you're done

Compute bills per minute **only while an instance is Running**. When you finish, use the instance's **Stop** action (or just let idle auto-stop handle it). Your files are preserved—start the instance again any time and pick up where you left off.

## Next steps

* [Working in your instance](/managed-compute/working-in-the-workspace.md) — Jupyter, code-server, and R Server
* [Lifecycle & persistence](/managed-compute/lifecycle.md) — what persists, and idle auto-stop
* [Choosing a machine type](/managed-compute/tiers.md) — sizing your instance
* [Compute & storage charges](/billing-and-plans/compute-usage.md) — how billing works