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Version: v3

odo list component

odo list component command is useful for getting information about components running on a specific namespace of a cluster or on Podman.

If the command is executed from a directory containing a Devfile, it also displays the component defined in the Devfile as part of the list, prefixed with a star(*).

For each component, the command displays:

  • its name,
  • its project type,
  • on which mode it is running (None, Dev, Deploy, or both), note that None is only applicable to the component defined in the local Devfile,
  • by which application the component has been deployed,
  • the platform on which the component is running (cluster or podman).

Running the command

odo list component
Example
$ odo list component
✓ Listing components from namespace 'my-percona-server-mongodb-operator' [292ms]
NAME PROJECT TYPE RUNNING IN MANAGED PLATFORM
* my-nodejs nodejs Deploy odo (v3.7) cluster
my-go-app go Dev odo (v3.7) podman
mongodb-instance Unknown None percona-server-mongodb-operator cluster

Targeting a specific platform

By default, odo list component will search components in both the current namespace of the cluster and podman. You can restrict the search to one of the platforms only, using the --platform flag, giving a value cluster or podman.

use of cache

odo list component makes use of cache for performance reasons. This is the same cache that is referred by kubectl command when you do kubectl api-resources --cached=true. As a result, if you were to install an Operator/CRD on the Kubernetes cluster, and create a resource from it using odo, you might not see it in the odo list component output. This would be the case for 10 minutes timeframe for which the cache is considered valid. Beyond this 10 minutes, the cache is updated anyway.

If you would like to invalidate the cache before the 10 minutes timeframe, you could manually delete it by doing:

rm -rf ~/.kube/cache/discovery/api.crc.testing_6443/

Above example shows how to invalidate the cache for a CRC cluster. Note that you will have to modify the api.crc. testing_6443 part based on the cluster you are working against.