Note
Access to this page requires authorization. You can try signing in or changing directories.
Access to this page requires authorization. You can try changing directories.
Important
The AI Runtime CLI is in Beta.
The air CLI provides five subcommands for managing training workloads: air run, air get run, air list runs, air logs, and air cancel. The same reference is always available from the CLI itself:
air --help # All commands
air <command> --help # Flags for a specific command
air -h config # YAML config reference
air -h config.compute # Per-field help for a YAML section
The CLI help reflects the exact version you have installed, so it is the source of truth if it differs from the table below.
Commands
| Command | Purpose |
|---|---|
air run |
Submit a workload defined by a YAML file. Supports --file, --watch, --dry-run, --override, --idempotency-key, --email, and -p to select an authentication profile. |
air get run |
Show metadata, status, and configuration for a specific run. |
air list runs |
List recent runs. Use --limit to bound the result count and --active to show only running workloads. |
air logs |
Stream or download logs for a run. Use --node to target a specific node and --download-to to write logs to a directory. |
air cancel |
Cancel a running workload. |
air register image |
Register and cache a custom Docker image for use in workloads. See Use custom Docker images. |
Global flags
| Flag | Purpose |
|---|---|
--version |
Print the installed CLI version. |
-p, --profile |
Use the named Databricks CLI authentication profile instead of the default. |
-h, --help |
Show help. When followed by a config path (-h config.compute), show YAML field help. |