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Add SSH Access info (#352)

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pollfly 2022-10-24 10:17:33 +03:00 committed by GitHub
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docs/clearml_agent.md
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@ -137,7 +137,8 @@ Install ClearML Agent as a system Python package and not in a Python virtual env
* Mac - `$HOME/clearml.conf`
* Windows - `\User\<username>\clearml.conf`
1. Optionally, configure ClearML options for **ClearML Agent** (default docker, package manager, etc.). See the [ClearML Configuration Reference](configs/clearml_conf.md).
1. Optionally, configure ClearML options for **ClearML Agent** (default docker, package manager, etc.). See the [ClearML Configuration Reference](configs/clearml_conf.md)
and the [ClearML Agent Environment Variables reference](clearml_agent/clearml_agent_env_var.md).
:::note
The ClearML Enterprise server provides a [configuration vault](webapp/webapp_profile.md#configuration-vault), the contents
@ -242,6 +243,16 @@ clearml-agent daemon --detached --queue group_a group_b --order-fairness --gpus
It will make sure the agent will pull from the `group_a` queue, then from `group_b`, then back to `group_a`, etc. This ensures
that `group_a` or `group_b` will not be able to starve one another of resources.
#### SSH Access
To make SSH keys available to an agent running in Docker mode, use the `SSH_AUTH_SOCK` environment variable.
The command below will execute an agent in Docker mode and assign it to service a queue. The agent will have access to
the SSH keys provided in the environment variable.
```
SSH_AUTH_SOCK=<file_socket> clearml-agent daemon --gpus <your config> --queue <your queue name> --docker
```
### Explicit Task Execution
ClearML Agent can also execute specific tasks directly, without listening to a queue.