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doctl compute image

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Usage

doctl compute image [flags]

Description

The sub-commands of doctl compute image manage images. A DigitalOcean image can be used to create a Droplet.

Currently, there are five types of images: snapshots, backups, custom images, distributions, and One-Click Apps.

  • Snapshots provide a full copy of an existing Droplet instance taken on demand.
  • Backups are similar to snapshots but are created automatically at regular intervals when enabled for a Droplet.
  • Custom images are Linux-based virtual machine images that you may upload for use on DigitalOcean. These can be in one of the following formats: raw, qcow2, vhdx, vdi, or vmdk.
  • Distributions are the public Linux distributions that are available to be used as a base to create Droplets.
  • Applications, or One-Click Apps, are distributions pre-configured with additional software.

Flags

OptionDescription
--help, -hHelp for this command
CommandDescription
doctl computeDisplay commands that manage infrastructure
doctl compute image createCreate custom image
doctl compute image deletePermanently delete an image from your account
doctl compute image getRetrieve information about an image
doctl compute image listList images on your account
doctl compute image list-applicationList available One-Click Apps
doctl compute image list-distributionList available distribution images
doctl compute image list-userList user-created images
doctl compute image updateUpdate an image's metadata

Global Flags

OptionDescription
--access-token, -tAPI V2 access token
--api-url, -uOverride default API endpoint
--config, -cSpecify a custom config file
Default:
  • macOS: ${HOME}/Library/Application Support/doctl/config.yaml
  • Linux: ${XDG_CONFIG_HOME}/doctl/config.yaml
  • Windows: %APPDATA%\doctl\config.yaml
--contextSpecify a custom authentication context name
--output, -oDesired output format [text|json]
Default: text
--traceShow a log of network activity while performing a command
Default: false
--verbose, -vEnable verbose output
Default: false