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Deployments

The Deployments page (Computers) is the central hub for managing your AI environments. It provides powerful filtering, statistics, and management tools for handling fleets of AI computers.

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Dashboard Stats

At the top of the page, you’ll see a quick summary of your resources:
  • Total Computers: The total count of all deployments (active and inactive).
  • Active: Number of currently running or provisioning systems.
  • Stopped: Computers that are paused and not consuming runtime credits.
  • Failed: Deployments that encountered errors during startup.

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Browsing Deployments

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Views

Toggle between two display modes based on your preference:
  • Grid View: A visual card layout showing desktop thumbnails, status dots, and key metrics. Ideal for visual monitoring.
  • List View: A compact table view perfect for managing large numbers of deployments efficiently.
Easily find specific computers using the toolbar:
  • Search: Filter by deployment name or ID.
  • Status Filter: Show only Running, Stopped, Failed, or Provisioning units.
  • Origin: Filter by how the deployment was created (e.g., via API or Dashboard).
  • Show Archived: Toggle to view historical deployments that have been terminated.

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Actions

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Management

Each deployment card or list item offers a menu of actions:
  • Stop: Pause a running computer to save credits (disk storage costs may still apply).
  • Restart: Reboot the system if it becomes unresponsive.
  • Delete: Permanently terminate the deployment and remove all associated data.

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Direct Access

  • Watch: Click the thumbnail or “Watch” button on running instances to open the live desktop stream.
  • Jump In: Open the full Computer Interface to take control or view logs.

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Deployment Lifecycle

  1. Provisioning: The system allocates resources and boots the OS.
  2. Running: The computer is ready for use.
  3. Stopped: The instance is preserved but not running (no CPU/RAM charges).
  4. Terminated: The instance is deleted. Metadata remains in “Archived” view for audit purposes.