From 390123bf25bedd84288a841df8902c9f8b632c73 Mon Sep 17 00:00:00 2001 From: "promptless[bot]" Date: Thu, 18 Jun 2026 00:55:53 +0000 Subject: [PATCH 1/9] Add Deploy a Pod page with On-Demand and Deploy When Available flows Documents the two Pod deployment paths (DOCS-450): Deploy On-Demand and Deploy When Available (Beta) for out-of-capacity GPUs. Adds the page to navigation and links it from the get-started Step 2 deploy step. --- docs.json | 1 + get-started.mdx | 4 ++ pods/deploy-a-pod.mdx | 116 ++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 121 insertions(+) create mode 100644 pods/deploy-a-pod.mdx diff --git a/docs.json b/docs.json index 9566b500..0197564f 100644 --- a/docs.json +++ b/docs.json @@ -172,6 +172,7 @@ "pods/overview", "pods/pricing", "pods/choose-a-pod", + "pods/deploy-a-pod", "pods/manage-pods", { "group": "Connect to Pods", diff --git a/get-started.mdx b/get-started.mdx index aa7e3789..7b1ef36d 100644 --- a/get-started.mdx +++ b/get-started.mdx @@ -34,6 +34,10 @@ Now that you've created your account, you're ready to deploy your first Pod: If you haven't set up payments yet, you'll be prompted to add a payment method and purchase credits for your account. + +If the GPU you want is out of capacity, use **Deploy When Available** to queue your Pod. Runpod deploys it automatically as soon as that GPU frees up. See [Deploy a Pod](/pods/deploy-a-pod) for both deployment paths. + + diff --git a/pods/deploy-a-pod.mdx b/pods/deploy-a-pod.mdx new file mode 100644 index 00000000..43876a2c --- /dev/null +++ b/pods/deploy-a-pod.mdx @@ -0,0 +1,116 @@ +--- +title: "Deploy a GPU Pod" +sidebarTitle: "Deploy a Pod" +description: "Deploy a GPU Pod immediately or queue a deployment for a GPU that's currently out of capacity." +--- + +The **Deploy a Pod** page lets you launch a GPU Pod in two ways: deploy immediately on an available GPU, or subscribe to deploy automatically when an out-of-capacity GPU becomes free. + + + +Use this path when you want to launch a Pod immediately on an available GPU. + +## Step 1: Configure your workload + +In the **Workload** panel on the left: + +**Template** — Select the container image your Pod will run. Use the search box to find a template, or click **Explore all** to browse. The selected template and its image are shown below the search bar. Click **Set overrides** to customize environment variables, exposed ports, or container start commands without editing the template itself. + +**Pod name** — A name is auto-generated. You can replace it with any name you prefer. + +**Options**: +- **Start Jupyter notebook** — Launches a Jupyter server when the Pod starts, accessible from the console. Enabled by default. +- **SSH terminal access** — Enables SSH into the Pod. If enabled, paste your SSH public key in the field that appears. [Learn how to create an SSH key](/pods/configuration/use-ssh). + +**Region** — By default set to **Any region**. Click to restrict deployment to a specific geographic region. + +## Step 2: Select an available GPU + +In the **Compute** panel, make sure the **Available** or **Recommended** tab is selected. + +- **Available** — shows only GPUs with capacity right now. +- **Recommended** — shows GPUs suggested for your workload. +- **All** — shows all GPUs including those that are out of capacity (use this tab with the **Deploy When Available** option below). + +Use the search box, **Network volume** filter, **Filter** button, or **VRAM** dropdown to narrow the list. Click **Compare GPUs** to view specs side-by-side. + +Each GPU card shows the price per hour, VRAM, maximum available count, and a colored availability indicator. Click a GPU card to select it — the right panel updates with your pricing summary. + + +GPUs showing **Out of capacity** cannot be selected for On-Demand deployment. Switch to the **Deploy when available** tab to queue for one of those GPUs. + + +## Step 3: Review the pricing summary + +The **Summary** panel on the right shows: +- The selected template and GPU. +- Total cost per hour (billed per millisecond). +- Breakdown: GPU cost, container disk cost, volume disk cost, and stopped cost. + +Verify the configuration looks correct before deploying. + +## Step 4: Deploy + +Click **Deploy On-Demand** to launch your Pod. + +Your Pod will appear in **Pods** in the left sidebar. It may take a moment to reach the **Running** state while the container image is pulled. + + + +Use this path when the GPU you want is currently out of capacity. Runpod automatically deploys your Pod as soon as that GPU becomes available within your chosen time window. + + +**Deploy when available** is a Beta feature. Enable it from [Account → Early access](https://console.runpod.io/user/early-access) if you don't see it. + + +## Step 1: Configure your workload + +In the **Workload** panel on the left, set up your deployment before selecting a GPU: + +**Template** — Select the container image your Pod will run. Use the search box to find a template, or click **Explore all** to browse. Click **Set overrides** to customize environment variables or ports without editing the template. + +**Pod name** — A name is auto-generated. You can replace it with any name you prefer. + +**Options**: +- **Start Jupyter notebook** — Launches a Jupyter server when the Pod starts. Enabled by default. +- **SSH terminal access** — Enables SSH into the Pod. Paste your SSH public key in the field that appears. + +**Region** — By default set to **Any region**. Click to restrict to a specific region. + +## Step 2: Select an out-of-capacity GPU + +In the **Compute** panel, click the **All** tab to show all GPUs, including those currently out of capacity. + +GPUs showing **Out of capacity** are eligible for **Deploy when available**. Click one to select it — the right panel updates to show **Instance not available** and a **Deploy when available** button. + +## Step 3: Click "Deploy when available" + +In the right panel, click the **Deploy when available** button. A modal opens. + +## Step 4: Set your subscription options + +In the **Deploy when available** modal: + +**Notifications** — Choose how you want to be notified when your Pod deploys: +- **Email** — sends a notification to your account email address. +- **In-console notification** — shows an alert inside the Runpod console. + +Both are enabled by default. + +**Subscription window** — Set the time range during which Runpod monitors for availability and auto-deploys your Pod: +- The default window is 24 hours from now. +- Click the date range to adjust the start and end time. +- Check **Use advanced scheduler** to set a recurring or more complex schedule. + +## Step 5: Subscribe + +Click **Subscribe** to confirm. Runpod monitors for availability and deploys your Pod automatically when the selected GPU becomes free within your subscription window. + +You'll receive a notification (via email or in-console, depending on your settings) when the Pod has been deployed. + + +If the GPU does not become available within your subscription window, your subscription expires and no Pod is deployed — you are not charged. You can create a new subscription at any time. + + + + From 0242327ca03dc14ab6632ced78e4aed6b671d4aa Mon Sep 17 00:00:00 2001 From: "promptless[bot]" Date: Thu, 18 Jun 2026 01:24:05 +0000 Subject: [PATCH 2/9] docs: fold Deploy When Available flow into get-started Step 2 Address PR #664 review feedback: instead of a standalone pods/deploy-a-pod page, document the Deploy When Available (Beta) out-of-capacity flow inline in the get-started quickstart's Step 2. Remove the standalone page and revert its docs.json nav entry. --- docs.json | 1 - get-started.mdx | 18 +++++-- pods/deploy-a-pod.mdx | 116 ------------------------------------------ 3 files changed, 15 insertions(+), 120 deletions(-) delete mode 100644 pods/deploy-a-pod.mdx diff --git a/docs.json b/docs.json index 0197564f..9566b500 100644 --- a/docs.json +++ b/docs.json @@ -172,7 +172,6 @@ "pods/overview", "pods/pricing", "pods/choose-a-pod", - "pods/deploy-a-pod", "pods/manage-pods", { "group": "Connect to Pods", diff --git a/get-started.mdx b/get-started.mdx index 7b1ef36d..e6985918 100644 --- a/get-started.mdx +++ b/get-started.mdx @@ -34,9 +34,21 @@ Now that you've created your account, you're ready to deploy your first Pod: If you haven't set up payments yet, you'll be prompted to add a payment method and purchase credits for your account. - -If the GPU you want is out of capacity, use **Deploy When Available** to queue your Pod. Runpod deploys it automatically as soon as that GPU frees up. See [Deploy a Pod](/pods/deploy-a-pod) for both deployment paths. - +### Deploy when available (Beta) + +If the GPU you want is out of capacity, you can queue your Pod and let Runpod deploy it automatically as soon as that GPU frees up. + + +**Deploy When Available** is a Beta feature. If you don't see it, enable it from [Account → Early access](https://console.runpod.io/user/early-access). + + +1. In the **Compute** panel, click the **All** tab to show every GPU, including those that are out of capacity. +2. Select an out-of-capacity GPU. The right panel updates to show **Instance not available** and a **Deploy when available** button. +3. Click **Deploy when available** to open the subscription modal. +4. Choose your notification preferences (email and in-console notifications are both enabled by default), then set the subscription window, which is the time range during which Runpod monitors for availability. The default window is 24 hours; check **Use advanced scheduler** for a recurring or more complex schedule. +5. Click **Subscribe**. Runpod deploys your Pod automatically when the GPU becomes available within your window, and notifies you when it's running. + +If the GPU doesn't become available before your subscription window ends, the subscription expires without deploying a Pod and you aren't charged. You can create a new subscription at any time. diff --git a/pods/deploy-a-pod.mdx b/pods/deploy-a-pod.mdx deleted file mode 100644 index 43876a2c..00000000 --- a/pods/deploy-a-pod.mdx +++ /dev/null @@ -1,116 +0,0 @@ ---- -title: "Deploy a GPU Pod" -sidebarTitle: "Deploy a Pod" -description: "Deploy a GPU Pod immediately or queue a deployment for a GPU that's currently out of capacity." ---- - -The **Deploy a Pod** page lets you launch a GPU Pod in two ways: deploy immediately on an available GPU, or subscribe to deploy automatically when an out-of-capacity GPU becomes free. - - - -Use this path when you want to launch a Pod immediately on an available GPU. - -## Step 1: Configure your workload - -In the **Workload** panel on the left: - -**Template** — Select the container image your Pod will run. Use the search box to find a template, or click **Explore all** to browse. The selected template and its image are shown below the search bar. Click **Set overrides** to customize environment variables, exposed ports, or container start commands without editing the template itself. - -**Pod name** — A name is auto-generated. You can replace it with any name you prefer. - -**Options**: -- **Start Jupyter notebook** — Launches a Jupyter server when the Pod starts, accessible from the console. Enabled by default. -- **SSH terminal access** — Enables SSH into the Pod. If enabled, paste your SSH public key in the field that appears. [Learn how to create an SSH key](/pods/configuration/use-ssh). - -**Region** — By default set to **Any region**. Click to restrict deployment to a specific geographic region. - -## Step 2: Select an available GPU - -In the **Compute** panel, make sure the **Available** or **Recommended** tab is selected. - -- **Available** — shows only GPUs with capacity right now. -- **Recommended** — shows GPUs suggested for your workload. -- **All** — shows all GPUs including those that are out of capacity (use this tab with the **Deploy When Available** option below). - -Use the search box, **Network volume** filter, **Filter** button, or **VRAM** dropdown to narrow the list. Click **Compare GPUs** to view specs side-by-side. - -Each GPU card shows the price per hour, VRAM, maximum available count, and a colored availability indicator. Click a GPU card to select it — the right panel updates with your pricing summary. - - -GPUs showing **Out of capacity** cannot be selected for On-Demand deployment. Switch to the **Deploy when available** tab to queue for one of those GPUs. - - -## Step 3: Review the pricing summary - -The **Summary** panel on the right shows: -- The selected template and GPU. -- Total cost per hour (billed per millisecond). -- Breakdown: GPU cost, container disk cost, volume disk cost, and stopped cost. - -Verify the configuration looks correct before deploying. - -## Step 4: Deploy - -Click **Deploy On-Demand** to launch your Pod. - -Your Pod will appear in **Pods** in the left sidebar. It may take a moment to reach the **Running** state while the container image is pulled. - - - -Use this path when the GPU you want is currently out of capacity. Runpod automatically deploys your Pod as soon as that GPU becomes available within your chosen time window. - - -**Deploy when available** is a Beta feature. Enable it from [Account → Early access](https://console.runpod.io/user/early-access) if you don't see it. - - -## Step 1: Configure your workload - -In the **Workload** panel on the left, set up your deployment before selecting a GPU: - -**Template** — Select the container image your Pod will run. Use the search box to find a template, or click **Explore all** to browse. Click **Set overrides** to customize environment variables or ports without editing the template. - -**Pod name** — A name is auto-generated. You can replace it with any name you prefer. - -**Options**: -- **Start Jupyter notebook** — Launches a Jupyter server when the Pod starts. Enabled by default. -- **SSH terminal access** — Enables SSH into the Pod. Paste your SSH public key in the field that appears. - -**Region** — By default set to **Any region**. Click to restrict to a specific region. - -## Step 2: Select an out-of-capacity GPU - -In the **Compute** panel, click the **All** tab to show all GPUs, including those currently out of capacity. - -GPUs showing **Out of capacity** are eligible for **Deploy when available**. Click one to select it — the right panel updates to show **Instance not available** and a **Deploy when available** button. - -## Step 3: Click "Deploy when available" - -In the right panel, click the **Deploy when available** button. A modal opens. - -## Step 4: Set your subscription options - -In the **Deploy when available** modal: - -**Notifications** — Choose how you want to be notified when your Pod deploys: -- **Email** — sends a notification to your account email address. -- **In-console notification** — shows an alert inside the Runpod console. - -Both are enabled by default. - -**Subscription window** — Set the time range during which Runpod monitors for availability and auto-deploys your Pod: -- The default window is 24 hours from now. -- Click the date range to adjust the start and end time. -- Check **Use advanced scheduler** to set a recurring or more complex schedule. - -## Step 5: Subscribe - -Click **Subscribe** to confirm. Runpod monitors for availability and deploys your Pod automatically when the selected GPU becomes free within your subscription window. - -You'll receive a notification (via email or in-console, depending on your settings) when the Pod has been deployed. - - -If the GPU does not become available within your subscription window, your subscription expires and no Pod is deployed — you are not charged. You can create a new subscription at any time. - - - - From 2d04e848b4fc500439448d3e8cc1332bf9f86762 Mon Sep 17 00:00:00 2001 From: "promptless[bot]" Date: Thu, 18 Jun 2026 01:48:03 +0000 Subject: [PATCH 3/9] docs: split Step 2 Web tab into Deploy On-Demand and Deploy When Available tabs MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Per reviewer feedback on PR #664, replace the 'Web' tab in the get-started Step 2 section with two tabs — 'Deploy On-Demand' and 'Deploy When Available' — using the reviewer's corrected instructions. Content uses the Steps component to keep the page heading hierarchy clean. Terminal tab preserved. --- get-started.mdx | 117 ++++++++++++++++++++++++++++++++++++++++-------- 1 file changed, 99 insertions(+), 18 deletions(-) diff --git a/get-started.mdx b/get-started.mdx index e6985918..af8cea44 100644 --- a/get-started.mdx +++ b/get-started.mdx @@ -21,34 +21,115 @@ Start by creating a Runpod account: Now that you've created your account, you're ready to deploy your first Pod: - + -1. Open the [Pods page](https://www.console.runpod.io/pods) in the web interface. -2. Click the **Deploy** button. -3. Select **A40** from the list of graphics cards (or any other GPU that's available). -4. In the field under **Pod Name**, enter the name **quickstart-pod**. -5. Keep all other fields (Pod Template, GPU Count, and Instance Pricing) on their default settings. -6. Click **Deploy On-Demand** to deploy and start your Pod. You'll be redirected back to the Pods page after a few seconds. +Use this path to launch a Pod immediately on an available GPU. Configure your workload, choose a GPU that has capacity right now, review the pricing, and deploy. - -If you haven't set up payments yet, you'll be prompted to add a payment method and purchase credits for your account. - + + + In the **Workload** panel on the left: + + - **Template** — Select the container image your Pod will run. Use the search box to find a template, or click **Explore all** to browse. The selected template and its image appear below the search bar. Click **Set overrides** to customize environment variables, exposed ports, or container start commands without editing the template itself. + - **Pod name** — A name is auto-generated. You can replace it with any name you prefer. + - **Options**: + - **Start Jupyter notebook** — Launches a Jupyter server when the Pod starts, accessible from the console. Enabled by default. + - **SSH terminal access** — Enables SSH into the Pod. If enabled, paste your SSH public key in the field that appears. [Learn how to create an SSH key](/pods/configuration/use-ssh). + - **Region** — Set to **Any region** by default. Click to restrict deployment to a specific geographic region. + + + + In the **Compute** panel, make sure the **Available** or **Recommended** tab is selected. + + - **Available** — shows only GPUs with capacity right now. + - **Recommended** — shows GPUs suggested for your workload. + - **All** — shows all GPUs, including those that are out of capacity (use this tab for Deploy when available). + + Use the search box, **Network volume** filter, **Filter** button, or **VRAM** dropdown to narrow the list. Click **Compare GPUs** to view specs side-by-side. + + Each GPU card shows the price per hour, VRAM, maximum available count, and a colored availability indicator. Click a GPU card to select it — the right panel updates with your pricing summary. + + + GPUs showing **Out of capacity** cannot be selected for On-Demand deployment. Switch to the **Deploy When Available** tab to queue for one of those GPUs. + + + + + The **Summary** panel on the right shows: + + - The selected template and GPU. + - Total cost per hour (billed per millisecond). + - A breakdown of GPU cost, container disk cost, volume disk cost, and stopped cost. + + Verify the configuration looks correct before deploying. + + + + Click **Deploy On-Demand** to launch your Pod. -### Deploy when available (Beta) + Your Pod appears under **Pods** in the left sidebar. It may take a moment to reach the **Running** state while the container image is pulled. -If the GPU you want is out of capacity, you can queue your Pod and let Runpod deploy it automatically as soon as that GPU frees up. + + If you haven't set up payments yet, you'll be prompted to add a payment method and purchase credits for your account. + + + + + + + + +Use this path when the GPU you want is out of capacity. Runpod queues your Pod and deploys it automatically as soon as that GPU frees up within the time window you choose. **Deploy When Available** is a Beta feature. If you don't see it, enable it from [Account → Early access](https://console.runpod.io/user/early-access). -1. In the **Compute** panel, click the **All** tab to show every GPU, including those that are out of capacity. -2. Select an out-of-capacity GPU. The right panel updates to show **Instance not available** and a **Deploy when available** button. -3. Click **Deploy when available** to open the subscription modal. -4. Choose your notification preferences (email and in-console notifications are both enabled by default), then set the subscription window, which is the time range during which Runpod monitors for availability. The default window is 24 hours; check **Use advanced scheduler** for a recurring or more complex schedule. -5. Click **Subscribe**. Runpod deploys your Pod automatically when the GPU becomes available within your window, and notifies you when it's running. + + + In the **Workload** panel on the left, set up your deployment before selecting a GPU: + + - **Template** — Select the container image your Pod will run. Use the search box to find a template, or click **Explore all** to browse. Click **Set overrides** to customize environment variables or ports without editing the template. + - **Pod name** — A name is auto-generated. You can replace it with any name you prefer. + - **Options**: + - **Start Jupyter notebook** — Launches a Jupyter server when the Pod starts. Enabled by default. + - **SSH terminal access** — Enables SSH into the Pod. Paste your SSH public key in the field that appears. + - **Region** — Set to **Any region** by default. Click to restrict to a specific region. + + + + In the **Compute** panel, click the **All** tab to show all GPUs, including those currently out of capacity. + + GPUs showing **Out of capacity** are eligible for **Deploy When Available**. Click one to select it — the right panel updates to show **Instance not available** and a **Deploy when available** button. + + + + In the right panel, click the **Deploy when available** button to open the subscription modal. + + + + In the **Deploy when available** modal: + + - **Notifications** — Choose how you want to be notified when your Pod deploys: + - **Email** — sends a notification to your account email address. + - **In-console notification** — shows an alert inside the Runpod console. + + Both are enabled by default. + - **Subscription window** — Set the time range during which Runpod monitors for availability and auto-deploys your Pod: + - The default window is 24 hours from now. + - Click the date range to adjust the start and end time. + - Check **Use advanced scheduler** to set a recurring or more complex schedule. + + + + Click **Subscribe** to confirm. Runpod monitors for availability and deploys your Pod automatically when the selected GPU becomes free within your subscription window. + + You'll receive a notification (via email or in-console, depending on your settings) when the Pod has been deployed. -If the GPU doesn't become available before your subscription window ends, the subscription expires without deploying a Pod and you aren't charged. You can create a new subscription at any time. + + If the GPU doesn't become available within your subscription window, your subscription expires and no Pod is deployed — you aren't charged. You can create a new subscription at any time. + + + From 3a399fc47a8eaed3b6416358e1a156c014bbfe29 Mon Sep 17 00:00:00 2001 From: "promptless[bot]" Date: Thu, 18 Jun 2026 16:06:17 +0000 Subject: [PATCH 4/9] docs: apply reviewer feedback to Step 2 deploy flow - Rename 'Deploy On-Demand' tab to 'Deploy a Pod'; sentence-case 'Deploy when available' - Add early access / standard flow toggle inside the Deploy a Pod tab - Note Jupyter/SSH options appear only for official templates - Split region into its own step; document all four GPU tabs (Available, Recommended, All, Recent) - Use 'Sort by' dropdown; remove incorrect out-of-capacity alert - Add a storage step covering storage types and network volume selection behavior - Use 'persistent storage cost' and 'Deploy Pod' button label - Fix deploy-when-available flow: email selection (incl. team email), advanced scheduler meaning, insufficient-funds re-subscribe warning - Remove em-dashes and fix title-cased prose --- get-started.mdx | 131 ++++++++++++++++++++++++++++++++++-------------- 1 file changed, 94 insertions(+), 37 deletions(-) diff --git a/get-started.mdx b/get-started.mdx index af8cea44..87bbc58e 100644 --- a/get-started.mdx +++ b/get-started.mdx @@ -21,36 +21,51 @@ Start by creating a Runpod account: Now that you've created your account, you're ready to deploy your first Pod: - + -Use this path to launch a Pod immediately on an available GPU. Configure your workload, choose a GPU that has capacity right now, review the pricing, and deploy. +Use this path to launch a Pod on an available GPU. Configure your workload, choose a region and GPU, review the pricing, and deploy. + +Runpod is rolling out an updated deployment flow through [early access](https://console.runpod.io/user/early-access). Use the tabs below to follow the version that matches what you see in the console. + + + + + +These instructions describe the early access version of the deployment flow. If you don't see this flow, follow the **Standard flow** tab, or enable the new flow from [Account → Early access](https://console.runpod.io/user/early-access). + In the **Workload** panel on the left: - - **Template** — Select the container image your Pod will run. Use the search box to find a template, or click **Explore all** to browse. The selected template and its image appear below the search bar. Click **Set overrides** to customize environment variables, exposed ports, or container start commands without editing the template itself. - - **Pod name** — A name is auto-generated. You can replace it with any name you prefer. - - **Options**: - - **Start Jupyter notebook** — Launches a Jupyter server when the Pod starts, accessible from the console. Enabled by default. - - **SSH terminal access** — Enables SSH into the Pod. If enabled, paste your SSH public key in the field that appears. [Learn how to create an SSH key](/pods/configuration/use-ssh). - - **Region** — Set to **Any region** by default. Click to restrict deployment to a specific geographic region. + - **Template**: select the container image your Pod will run. Use the search box to find a template, or click **Explore all** to browse. The selected template and its image appear below the search bar. Click **Set overrides** to customize environment variables, exposed ports, or container start commands without editing the template itself. + - **Pod name**: a name is auto-generated. You can replace it with any name you prefer. + - **Options**: when you select an [official Runpod template](/pods/templates/overview), two extra options appear. These options are not shown for community templates. + - **Start Jupyter notebook**: launches a Jupyter server when the Pod starts, accessible from the console. Enabled by default. + - **SSH terminal access**: enables SSH into the Pod. If enabled, paste your SSH public key in the field that appears. [Learn how to create an SSH key](/pods/configuration/use-ssh). + + + + Set the **Region** for your Pod. It's set to **Any region** by default. Click to restrict deployment to a specific geographic region. - - In the **Compute** panel, make sure the **Available** or **Recommended** tab is selected. + + In the **Compute** panel, choose a GPU from one of four tabs: - - **Available** — shows only GPUs with capacity right now. - - **Recommended** — shows GPUs suggested for your workload. - - **All** — shows all GPUs, including those that are out of capacity (use this tab for Deploy when available). + - **Available**: shows only GPUs with capacity right now. + - **Recommended**: shows GPUs recommended by Runpod and by the template maintainer. + - **All**: shows all GPUs, including those that are out of capacity and those marked incompatible by the template. + - **Recent**: shows all GPUs you've deployed in the last 7 days. - Use the search box, **Network volume** filter, **Filter** button, or **VRAM** dropdown to narrow the list. Click **Compare GPUs** to view specs side-by-side. + Use the search box, **Network volume** filter, **Filter** button, or **Sort by** dropdown to narrow the list. Click **Compare GPUs** to view specs side by side. - Each GPU card shows the price per hour, VRAM, maximum available count, and a colored availability indicator. Click a GPU card to select it — the right panel updates with your pricing summary. + Each GPU card shows the price per hour, VRAM, maximum available count, and a colored availability indicator. Click a GPU card to select it, and the right panel updates with your pricing summary. + - - GPUs showing **Out of capacity** cannot be selected for On-Demand deployment. Switch to the **Deploy When Available** tab to queue for one of those GPUs. - + + Pods offer three storage types, each with different persistence behavior. The container disk holds the operating system and temporary files, and it's cleared whenever the Pod stops. The volume disk provides persistent storage mounted at `/workspace` that survives stops and restarts, but it's deleted when you terminate the Pod. A network volume is permanent storage that exists independently of any Pod, so you can attach it to multiple Pods and keep your data even after a Pod is deleted. For a full comparison, see [Storage options](/pods/storage/types). + + You can select a network volume in two places, and each behaves differently. In the **Storage** step, the network volume selector lists only the volumes that are compatible with the GPU you've already selected. In the **Compute** panel, the network volume selector works as a filter instead: you can choose any network volume, and the GPU list updates to match it. GPUs that aren't compatible with the selected volume move to the incompatible section of the **All** tab. @@ -58,15 +73,15 @@ Use this path to launch a Pod immediately on an available GPU. Configure your wo - The selected template and GPU. - Total cost per hour (billed per millisecond). - - A breakdown of GPU cost, container disk cost, volume disk cost, and stopped cost. + - A breakdown of GPU cost, container disk cost, persistent storage cost, and stopped cost. Verify the configuration looks correct before deploying. - Click **Deploy On-Demand** to launch your Pod. + Click **Deploy Pod** to launch your Pod. - Your Pod appears under **Pods** in the left sidebar. It may take a moment to reach the **Running** state while the container image is pulled. + Your Pod appears under **Pods** in the left sidebar. It may take a moment to reach the running state while the container image is pulled. If you haven't set up payments yet, you'll be prompted to add a payment method and purchase credits for your account. @@ -76,30 +91,68 @@ Use this path to launch a Pod immediately on an available GPU. Configure your wo - + + + + + Open the [Pods page](https://www.console.runpod.io/pods) in the web interface, then click the **Deploy** button. + + + + Select **A40** from the list of graphics cards, or any other GPU that's available. + + + + In the field under **Pod Name**, enter the name **quickstart-pod**. Keep all other fields (Pod Template, GPU Count, and Instance Pricing) on their default settings. + + + + Click **Deploy On-Demand** to deploy and start your Pod. You'll be redirected back to the Pods page after a few seconds. + + + If you haven't set up payments yet, you'll be prompted to add a payment method and purchase credits for your account. + + + + + + + + + + Use this path when the GPU you want is out of capacity. Runpod queues your Pod and deploys it automatically as soon as that GPU frees up within the time window you choose. -**Deploy When Available** is a Beta feature. If you don't see it, enable it from [Account → Early access](https://console.runpod.io/user/early-access). +Deploy when available is a beta feature. If you don't see it, enable it from [Account → Early access](https://console.runpod.io/user/early-access). In the **Workload** panel on the left, set up your deployment before selecting a GPU: - - **Template** — Select the container image your Pod will run. Use the search box to find a template, or click **Explore all** to browse. Click **Set overrides** to customize environment variables or ports without editing the template. - - **Pod name** — A name is auto-generated. You can replace it with any name you prefer. - - **Options**: - - **Start Jupyter notebook** — Launches a Jupyter server when the Pod starts. Enabled by default. - - **SSH terminal access** — Enables SSH into the Pod. Paste your SSH public key in the field that appears. - - **Region** — Set to **Any region** by default. Click to restrict to a specific region. + - **Template**: select the container image your Pod will run. Use the search box to find a template, or click **Explore all** to browse. Click **Set overrides** to customize environment variables or ports without editing the template. + - **Pod name**: a name is auto-generated. You can replace it with any name you prefer. + - **Options**: when you select an [official Runpod template](/pods/templates/overview), two extra options appear. These options are not shown for community templates. + - **Start Jupyter notebook**: launches a Jupyter server when the Pod starts. Enabled by default. + - **SSH terminal access**: enables SSH into the Pod. Paste your SSH public key in the field that appears. + + + + Set the **Region** for your Pod. It's set to **Any region** by default. Click to restrict deployment to a specific geographic region. - + In the **Compute** panel, click the **All** tab to show all GPUs, including those currently out of capacity. - GPUs showing **Out of capacity** are eligible for **Deploy When Available**. Click one to select it — the right panel updates to show **Instance not available** and a **Deploy when available** button. + GPUs showing **Out of capacity** are eligible for deploy when available. Click one to select it, and the right panel updates to show **Instance not available** and a **Deploy when available** button. + + + + As with a standard deployment, you can attach persistent storage to your Pod. The container disk holds temporary files and is cleared when the Pod stops, the volume disk provides persistent storage at `/workspace` that's deleted when the Pod is terminated, and a network volume is permanent storage that exists independently of any Pod. For a full comparison, see [Storage options](/pods/storage/types). + + The network volume selector in the **Storage** step lists only the volumes that are compatible with the GPU you've selected. The selector in the **Compute** panel works as a filter instead: you can choose any network volume, and GPU availability updates to match it. GPUs that aren't compatible with the selected volume move to the incompatible section of the **All** tab. @@ -109,15 +162,15 @@ Use this path when the GPU you want is out of capacity. Runpod queues your Pod a In the **Deploy when available** modal: - - **Notifications** — Choose how you want to be notified when your Pod deploys: - - **Email** — sends a notification to your account email address. - - **In-console notification** — shows an alert inside the Runpod console. + - **Notifications**: choose how you want to be notified when your Pod deploys: + - **Email**: sends a notification to one of your account's email addresses. Select which address to use. If you're a member of a team, you can also select the team's email address. + - **In-console notification**: shows an alert inside the Runpod console. Both are enabled by default. - - **Subscription window** — Set the time range during which Runpod monitors for availability and auto-deploys your Pod: + - **Subscription window**: set the time range during which Runpod monitors for availability and auto-deploys your Pod: - The default window is 24 hours from now. - Click the date range to adjust the start and end time. - - Check **Use advanced scheduler** to set a recurring or more complex schedule. + - Check **Use advanced scheduler** to fine-tune the hours when Runpod can deploy your request, rather than monitoring continuously across the entire window. @@ -125,8 +178,12 @@ Use this path when the GPU you want is out of capacity. Runpod queues your Pod a You'll receive a notification (via email or in-console, depending on your settings) when the Pod has been deployed. + + If you don't have enough funds available when the GPU becomes available, your deploy when available subscription fails and no Pod is deployed. To retry, you'll need to subscribe again. + + - If the GPU doesn't become available within your subscription window, your subscription expires and no Pod is deployed — you aren't charged. You can create a new subscription at any time. + If the GPU doesn't become available within your subscription window, your subscription expires and no Pod is deployed. You can create a new subscription at any time. From 984ec1f3e580fa82cf4fce60c68256ab8562abe7 Mon Sep 17 00:00:00 2001 From: "promptless[bot]" Date: Thu, 18 Jun 2026 16:30:30 +0000 Subject: [PATCH 5/9] Correct Compare GPUs description in get-started deploy flow Compare GPUs asks the Runpod assistant for a comparison rather than showing specs side by side, per reviewer feedback. --- get-started.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/get-started.mdx b/get-started.mdx index 87bbc58e..7bc6daac 100644 --- a/get-started.mdx +++ b/get-started.mdx @@ -57,7 +57,7 @@ These instructions describe the early access version of the deployment flow. If - **All**: shows all GPUs, including those that are out of capacity and those marked incompatible by the template. - **Recent**: shows all GPUs you've deployed in the last 7 days. - Use the search box, **Network volume** filter, **Filter** button, or **Sort by** dropdown to narrow the list. Click **Compare GPUs** to view specs side by side. + Use the search box, **Network volume** filter, **Filter** button, or **Sort by** dropdown to narrow the list. Click **Compare GPUs** to ask the Runpod assistant for a comparison of the selected GPUs. Each GPU card shows the price per hour, VRAM, maximum available count, and a colored availability indicator. Click a GPU card to select it, and the right panel updates with your pricing summary. From ee0e67e35d47d81882cdaad350932f808529e11c Mon Sep 17 00:00:00 2001 From: "promptless[bot]" Date: Thu, 18 Jun 2026 16:52:31 +0000 Subject: [PATCH 6/9] docs: apply storage and legacy flow feedback to deploy-a-pod flow --- get-started.mdx | 22 +++++++++++----------- 1 file changed, 11 insertions(+), 11 deletions(-) diff --git a/get-started.mdx b/get-started.mdx index 7bc6daac..b28ab112 100644 --- a/get-started.mdx +++ b/get-started.mdx @@ -31,7 +31,7 @@ Runpod is rolling out an updated deployment flow through [early access](https:// -These instructions describe the early access version of the deployment flow. If you don't see this flow, follow the **Standard flow** tab, or enable the new flow from [Account → Early access](https://console.runpod.io/user/early-access). +These instructions describe the early access version of the deployment flow. If you don't see this flow, follow the **Legacy flow** tab, or enable the new flow from [Account → Early access](https://console.runpod.io/user/early-access). @@ -63,9 +63,13 @@ These instructions describe the early access version of the deployment flow. If - Pods offer three storage types, each with different persistence behavior. The container disk holds the operating system and temporary files, and it's cleared whenever the Pod stops. The volume disk provides persistent storage mounted at `/workspace` that survives stops and restarts, but it's deleted when you terminate the Pod. A network volume is permanent storage that exists independently of any Pod, so you can attach it to multiple Pods and keep your data even after a Pod is deleted. For a full comparison, see [Storage options](/pods/storage/types). + Pods offer two kinds of storage. The container disk is the container's primary storage, and it's wiped whenever the Pod is stopped. Persistent storage keeps your data across stops and restarts, and comes in two forms: a volume disk or a network volume. You can attach one or the other, but not both, so you'll need to choose. - You can select a network volume in two places, and each behaves differently. In the **Storage** step, the network volume selector lists only the volumes that are compatible with the GPU you've already selected. In the **Compute** panel, the network volume selector works as a filter instead: you can choose any network volume, and the GPU list updates to match it. GPUs that aren't compatible with the selected volume move to the incompatible section of the **All** tab. + A volume disk can be mounted at any location. It's mounted at `/workspace` by default, but you can change this with a template override, or the template itself can set a different default. A network volume is permanent storage that exists independently of any Pod. + + If you didn't select a network volume in the **Compute** step and your selected GPU is compatible with one, Runpod automatically creates a network volume for you. If you did select a network volume in the **Compute** step, the persistent storage option in this step is locked to that network volume. + + For a full comparison, see [Storage options](/pods/storage/types). @@ -91,19 +95,15 @@ These instructions describe the early access version of the deployment flow. If - + - - Open the [Pods page](https://www.console.runpod.io/pods) in the web interface, then click the **Deploy** button. - - - Select **A40** from the list of graphics cards, or any other GPU that's available. + Select a GPU from the list of graphics cards. - - In the field under **Pod Name**, enter the name **quickstart-pod**. Keep all other fields (Pod Template, GPU Count, and Instance Pricing) on their default settings. + + Select the template you want to use. To customize environment variables, exposed ports, or container start commands, click **Edit** to set template overrides. From d5e77096b7e236881dbb86c8a03071544bd10f00 Mon Sep 17 00:00:00 2001 From: "promptless[bot]" Date: Thu, 18 Jun 2026 17:19:18 +0000 Subject: [PATCH 7/9] docs: restructure storage step and add network volume filter note --- get-started.mdx | 21 ++++++++++++++++++--- 1 file changed, 18 insertions(+), 3 deletions(-) diff --git a/get-started.mdx b/get-started.mdx index b28ab112..e430e246 100644 --- a/get-started.mdx +++ b/get-started.mdx @@ -59,15 +59,30 @@ These instructions describe the early access version of the deployment flow. If Use the search box, **Network volume** filter, **Filter** button, or **Sort by** dropdown to narrow the list. Click **Compare GPUs** to ask the Runpod assistant for a comparison of the selected GPUs. + The **Network volume** filter narrows the GPU list to a network volume you choose. Select any network volume, and GPU availability updates to match it. GPUs that aren't compatible with the selected volume move to the incompatible section of the **All** tab. + Each GPU card shows the price per hour, VRAM, maximum available count, and a colored availability indicator. Click a GPU card to select it, and the right panel updates with your pricing summary. - Pods offer two kinds of storage. The container disk is the container's primary storage, and it's wiped whenever the Pod is stopped. Persistent storage keeps your data across stops and restarts, and comes in two forms: a volume disk or a network volume. You can attach one or the other, but not both, so you'll need to choose. + Pods offer two kinds of storage. + + **Container disk** + + This is the container's primary storage, and it's wiped whenever the Pod is stopped. + + **Persistent storage** + + Persistent storage keeps your data across stops and restarts, and you can mount it at any location. It's mounted at `/workspace` by default, but you can change this with a template override, or the template itself can set a different default. It comes in two types, and you can attach one or the other but not both: + + - **Volume disk**: a disk attached directly to your Pod that keeps its data across stops and restarts but is deleted when the Pod is terminated. + - **Network volume**: permanent storage that exists independently of any Pod, so you can attach the same volume to different Pods over time. + + If you didn't select a network volume in the **Compute** step and your selected GPU is compatible with one, Runpod automatically creates a network volume for you. When this will happen, the selection dropdown reads **Automatically create**. To opt out, either switch persistent storage to **Volume disk**, or manually select a different network volume from the dropdown. - A volume disk can be mounted at any location. It's mounted at `/workspace` by default, but you can change this with a template override, or the template itself can set a different default. A network volume is permanent storage that exists independently of any Pod. + If you did select a network volume in the **Compute** step, the persistent storage selection in this step is locked to that network volume. - If you didn't select a network volume in the **Compute** step and your selected GPU is compatible with one, Runpod automatically creates a network volume for you. If you did select a network volume in the **Compute** step, the persistent storage option in this step is locked to that network volume. + GPUs that aren't compatible with any network volume have volume disk selected automatically, and you can't select a network volume for them. For a full comparison, see [Storage options](/pods/storage/types). From 39541bc0312024e999b864a82e5150f4297febc4 Mon Sep 17 00:00:00 2001 From: "promptless[bot]" Date: Thu, 18 Jun 2026 17:34:48 +0000 Subject: [PATCH 8/9] docs: restructure deploy flow tabs and fold Deploy when available into Deploy step - Rename 'Deploy a Pod' tab to 'Deploy via the console' and 'Terminal' to 'Deploy via the CLI' - Remove standalone 'Deploy when available' tab; add Deploy available Pod / Deploy when available tabs at the Deploy step of the Early access flow - Note out-of-capacity GPU selection in Select a GPU step, linking to the Deploy step --- get-started.mdx | 126 ++++++++++++++++++++---------------------------- 1 file changed, 52 insertions(+), 74 deletions(-) diff --git a/get-started.mdx b/get-started.mdx index e430e246..3ace8a91 100644 --- a/get-started.mdx +++ b/get-started.mdx @@ -21,9 +21,9 @@ Start by creating a Runpod account: Now that you've created your account, you're ready to deploy your first Pod: - + -Use this path to launch a Pod on an available GPU. Configure your workload, choose a region and GPU, review the pricing, and deploy. +Use this path to launch a Pod from the console. Configure your workload, choose a region and GPU, review the pricing, and deploy. Runpod is rolling out an updated deployment flow through [early access](https://console.runpod.io/user/early-access). Use the tabs below to follow the version that matches what you see in the console. @@ -62,6 +62,8 @@ These instructions describe the early access version of the deployment flow. If The **Network volume** filter narrows the GPU list to a network volume you choose. Select any network volume, and GPU availability updates to match it. GPUs that aren't compatible with the selected volume move to the incompatible section of the **All** tab. Each GPU card shows the price per hour, VRAM, maximum available count, and a colored availability indicator. Click a GPU card to select it, and the right panel updates with your pricing summary. + + If the GPU you want shows **Out of capacity**, you can still select it and deploy it once capacity frees up. Selecting an out-of-capacity GPU changes the final [Deploy](#deploy) step: instead of deploying right away, you can subscribe to deploy when the GPU becomes available. @@ -97,7 +99,10 @@ These instructions describe the early access version of the deployment flow. If Verify the configuration looks correct before deploying. - + + + + Click **Deploy Pod** to launch your Pod. Your Pod appears under **Pods** in the left sidebar. It may take a moment to reach the running state while the container image is pulled. @@ -105,6 +110,49 @@ These instructions describe the early access version of the deployment flow. If If you haven't set up payments yet, you'll be prompted to add a payment method and purchase credits for your account. + + + + + + If you selected an out-of-capacity GPU, the **Summary** panel shows **Instance not available** and a **Deploy when available** button in place of **Deploy Pod**. Runpod queues your Pod and deploys it automatically as soon as that GPU frees up within the time window you choose. + + + + In the right panel, click the **Deploy when available** button to open the subscription modal. + + + + In the **Deploy when available** modal: + + - **Notifications**: choose how you want to be notified when your Pod deploys: + - **Email**: sends a notification to one of your account's email addresses. Select which address to use. If you're a member of a team, you can also select the team's email address. + - **In-console notification**: shows an alert inside the Runpod console. + + Both are enabled by default. + - **Subscription window**: set the time range during which Runpod monitors for availability and auto-deploys your Pod: + - The default window is 24 hours from now. + - Click the date range to adjust the start and end time. + - Check **Use advanced scheduler** to fine-tune the hours when Runpod can deploy your request, rather than monitoring continuously across the entire window. + + + + Click **Subscribe** to confirm. Runpod monitors for availability and deploys your Pod automatically when the selected GPU becomes free within your subscription window. + + You'll receive a notification (via email or in-console, depending on your settings) when the Pod has been deployed. + + + If you don't have enough funds available when the GPU becomes available, your deploy when available subscription fails and no Pod is deployed. To retry, you'll need to subscribe again. + + + + If the GPU doesn't become available within your subscription window, your subscription expires and no Pod is deployed. You can create a new subscription at any time. + + + + + + @@ -135,77 +183,7 @@ These instructions describe the early access version of the deployment flow. If - - -Use this path when the GPU you want is out of capacity. Runpod queues your Pod and deploys it automatically as soon as that GPU frees up within the time window you choose. - - -Deploy when available is a beta feature. If you don't see it, enable it from [Account → Early access](https://console.runpod.io/user/early-access). - - - - - In the **Workload** panel on the left, set up your deployment before selecting a GPU: - - - **Template**: select the container image your Pod will run. Use the search box to find a template, or click **Explore all** to browse. Click **Set overrides** to customize environment variables or ports without editing the template. - - **Pod name**: a name is auto-generated. You can replace it with any name you prefer. - - **Options**: when you select an [official Runpod template](/pods/templates/overview), two extra options appear. These options are not shown for community templates. - - **Start Jupyter notebook**: launches a Jupyter server when the Pod starts. Enabled by default. - - **SSH terminal access**: enables SSH into the Pod. Paste your SSH public key in the field that appears. - - - - Set the **Region** for your Pod. It's set to **Any region** by default. Click to restrict deployment to a specific geographic region. - - - - In the **Compute** panel, click the **All** tab to show all GPUs, including those currently out of capacity. - - GPUs showing **Out of capacity** are eligible for deploy when available. Click one to select it, and the right panel updates to show **Instance not available** and a **Deploy when available** button. - - - - As with a standard deployment, you can attach persistent storage to your Pod. The container disk holds temporary files and is cleared when the Pod stops, the volume disk provides persistent storage at `/workspace` that's deleted when the Pod is terminated, and a network volume is permanent storage that exists independently of any Pod. For a full comparison, see [Storage options](/pods/storage/types). - - The network volume selector in the **Storage** step lists only the volumes that are compatible with the GPU you've selected. The selector in the **Compute** panel works as a filter instead: you can choose any network volume, and GPU availability updates to match it. GPUs that aren't compatible with the selected volume move to the incompatible section of the **All** tab. - - - - In the right panel, click the **Deploy when available** button to open the subscription modal. - - - - In the **Deploy when available** modal: - - - **Notifications**: choose how you want to be notified when your Pod deploys: - - **Email**: sends a notification to one of your account's email addresses. Select which address to use. If you're a member of a team, you can also select the team's email address. - - **In-console notification**: shows an alert inside the Runpod console. - - Both are enabled by default. - - **Subscription window**: set the time range during which Runpod monitors for availability and auto-deploys your Pod: - - The default window is 24 hours from now. - - Click the date range to adjust the start and end time. - - Check **Use advanced scheduler** to fine-tune the hours when Runpod can deploy your request, rather than monitoring continuously across the entire window. - - - - Click **Subscribe** to confirm. Runpod monitors for availability and deploys your Pod automatically when the selected GPU becomes free within your subscription window. - - You'll receive a notification (via email or in-console, depending on your settings) when the Pod has been deployed. - - - If you don't have enough funds available when the GPU becomes available, your deploy when available subscription fails and no Pod is deployed. To retry, you'll need to subscribe again. - - - - If the GPU doesn't become available within your subscription window, your subscription expires and no Pod is deployed. You can create a new subscription at any time. - - - - - - - + First, install the [Runpod CLI](/runpodctl/overview) on your local machine and configure it with your API key: From b0492f192d692594efc64fbbca8021761f4e3bf2 Mon Sep 17 00:00:00 2001 From: "promptless[bot]" Date: Thu, 18 Jun 2026 17:53:21 +0000 Subject: [PATCH 9/9] docs: slim down GPU card and auto-create volume content, update network volume filter description --- get-started.mdx | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/get-started.mdx b/get-started.mdx index 3ace8a91..f5e4f7eb 100644 --- a/get-started.mdx +++ b/get-started.mdx @@ -59,9 +59,7 @@ These instructions describe the early access version of the deployment flow. If Use the search box, **Network volume** filter, **Filter** button, or **Sort by** dropdown to narrow the list. Click **Compare GPUs** to ask the Runpod assistant for a comparison of the selected GPUs. - The **Network volume** filter narrows the GPU list to a network volume you choose. Select any network volume, and GPU availability updates to match it. GPUs that aren't compatible with the selected volume move to the incompatible section of the **All** tab. - - Each GPU card shows the price per hour, VRAM, maximum available count, and a colored availability indicator. Click a GPU card to select it, and the right panel updates with your pricing summary. + The **Network volume** filter narrows the GPU list to compatible GPUs by filtering for GPUs that are in the same data center as the selected network volume. Select any network volume, and GPU availability updates to match it. GPUs that aren't compatible with the selected volume move to the incompatible section of the **All** tab. If the GPU you want shows **Out of capacity**, you can still select it and deploy it once capacity frees up. Selecting an out-of-capacity GPU changes the final [Deploy](#deploy) step: instead of deploying right away, you can subscribe to deploy when the GPU becomes available. @@ -80,8 +78,6 @@ These instructions describe the early access version of the deployment flow. If - **Volume disk**: a disk attached directly to your Pod that keeps its data across stops and restarts but is deleted when the Pod is terminated. - **Network volume**: permanent storage that exists independently of any Pod, so you can attach the same volume to different Pods over time. - If you didn't select a network volume in the **Compute** step and your selected GPU is compatible with one, Runpod automatically creates a network volume for you. When this will happen, the selection dropdown reads **Automatically create**. To opt out, either switch persistent storage to **Volume disk**, or manually select a different network volume from the dropdown. - If you did select a network volume in the **Compute** step, the persistent storage selection in this step is locked to that network volume. GPUs that aren't compatible with any network volume have volume disk selected automatically, and you can't select a network volume for them.