CLI Reference¶
All commands are available under kedro azureml. Run kedro azureml --help to list them.
kedro azureml init¶
Initializes the plugin in the current Kedro project. Creates:
conf/base/azureml.yml: configuration file with placeholder values.amlignore: file exclusion list for code upload
No flags.
kedro azureml compile¶
Compiles job(s) into Azure ML pipeline YAML definitions without submitting them. Select jobs with one or more -j names, or compile every resolved job with --all. Add --check to validate that jobs compile without writing any files. See Compile and inspect for a walkthrough.
| Flag | Description |
|---|---|
-j JOB_NAME |
Job name from jobs in azureml.yml. Required unless --all is given (provide one of -j or --all). Repeatable for multiple jobs. |
--all |
Compile every resolved job, both literal and factory-derived. Mutually exclusive with -j. |
--check |
Compile in memory without writing any output, and exit non-zero if any job fails to compile. Needs no Azure credentials and submits nothing, so it is suitable as a CI gate. Combine with --all to validate the whole config. |
-o OUTPUT |
Output YAML file path (default: pipeline.yaml). Ignored with --check. |
--aml-env ENV |
Override the Azure ML environment for this invocation |
--params JSON |
Runtime parameters as a JSON string (e.g. '{"key": "value"}') |
--env-var KEY=VALUE |
Inject an environment variable into pipeline steps. Repeatable. |
--load-versions KEY:VERSION |
Pin a dataset to a specific Kedro-versioned version. Repeatable. |
kedro azureml run¶
Submits named job(s) to Azure ML managed compute immediately, ignoring any configured schedule.
| Flag | Description |
|---|---|
-j JOB_NAME |
Job name from jobs in azureml.yml. Required. Repeatable for multiple jobs. |
--dry-run |
Preview the pipeline definition without submitting to Azure ML |
--wait-for-completion |
Block the terminal until the run finishes |
-w WORKSPACE |
Override the workspace for all jobs in this batch |
--aml-env ENV |
Override the Azure ML environment for this invocation |
--params JSON |
Runtime parameters as a JSON string |
--env-var KEY=VALUE |
Inject an environment variable into pipeline steps. Repeatable. |
--load-versions KEY:VERSION |
Pin a dataset to a specific Kedro-versioned version. Repeatable. |
--on-job-scheduled MODULE:FUNC |
Callback invoked after each job is submitted (e.g. mymodule:notify) |
Batch submission is fail-fast¶
When you pass several -j names (or run all configured jobs), they are submitted in the order given, one after another. Jobs in a batch usually feed each other (for example snapshot then training then inference), so if one job fails to submit, run stops immediately and skips every remaining job rather than launching work that would consume missing outputs.
The skipped jobs are listed, and the final summary counts succeeded, failed, and skipped jobs:
Aborting batch: 'training' failed; skipping 1 remaining job(s): inference
Run summary: 1 succeeded, 1 failed, 1 skipped (out of 3 selected)
The command exits non-zero if any job failed or was skipped. To submit jobs independently so that one failure does not hold back the others, invoke run once per job instead of passing multiple -j names.
kedro azureml schedule¶
Creates or updates persistent Azure ML schedules for named job(s). Every selected job must have a schedule configured in azureml.yml.
| Flag | Description |
|---|---|
-j JOB_NAME |
Job name from jobs in azureml.yml. Required. Repeatable for multiple jobs. |
--dry-run |
Preview the schedule definition without creating it in Azure ML |
-w WORKSPACE |
Override the workspace for all jobs in this batch |
--aml-env ENV |
Override the Azure ML environment for this invocation |
--params JSON |
Runtime parameters as a JSON string |
--env-var KEY=VALUE |
Inject an environment variable into pipeline steps. Repeatable. |
--load-versions KEY:VERSION |
Pin a dataset to a specific Kedro-versioned version. Repeatable. |
kedro azureml resolve-patterns¶
Lists the concrete jobs derived from the job factories and the pipeline namespaces (the job analogue of kedro catalog resolve-patterns). For each job it prints the name, pipeline, node namespaces, and schedule; literal (non-factory) jobs are included. No Azure ML connection is made. Add -e ENV to inspect a specific environment.
The names printed here are exactly what you pass to -j on run, schedule, and compile.
kedro azureml list-patterns¶
Lists the job-factory patterns, the jobs keys containing {placeholder} markers (the analogue of kedro catalog list-patterns). Literal job keys are not listed; use resolve-patterns to see the concrete jobs the factories produce.
kedro azureml execute¶
Used internally by Azure ML pipeline steps to run individual Kedro nodes on compute. Not intended for direct use. You may see this command in Azure ML step logs when inspecting pipeline run output in Azure ML Studio.
Common flags¶
The following flags are accepted by compile, run, and schedule:
| Flag | Description |
|---|---|
--params JSON |
Runtime parameters as a JSON string |
--env-var KEY=VALUE |
Inject environment variables into pipeline steps (repeatable) |
--load-versions KEY:VERSION |
Dataset version overrides (repeatable) |
--aml-env ENV |
Override the Azure ML environment |