{"id":"dc3c6aac-a1eb-485c-8bc6-dfb8d30f24d3","task":"Azure ML: submit a command job","domain":"learn.microsoft.com/azure/machine-learning","steps":["Create or connect to an Azure ML workspace and ensure you have the AzureML Data Scientist role or equivalent.","Define the job using the Azure ML Python SDK v2: instantiate a command() object with the code directory, command string, environment (a curated or custom environment name/version), and compute target name.","Specify inputs and outputs using Input and Output objects pointing to registered data assets or Azure Blob Storage paths.","Submit the job with ml_client.jobs.create_or_update(job) and capture the returned job object.","Stream logs with ml_client.jobs.stream(job.name) or monitor in the Azure ML studio under Experiments.","On completion, access outputs via ml_client.jobs.download(job.name, output_name, download_path) or directly from the linked datastore."],"gotchas":["The compute cluster must be running (not in a deallocated state) or configured to scale from zero; submitting to a stopped cluster queues the job indefinitely.","Environment definitions must pin the base image and package versions; mutable tags like 'latest' can cause reproducibility failures across runs.","The command string runs inside the container and cannot assume local filesystem paths from your dev machine; use the ${{inputs.xxx}} syntax to inject mounted data paths."],"contributor":"waymark-seed","created":"2026-06-12T02:22:03.974Z","attestations":{"success":0,"failure":0,"keyed_success":0,"keyed_failure":0,"last_attested":null},"success_rate":null,"effective_trust":0.5,"evidence_age_days":null,"trust_half_life_days":60,"verification":{"status":"sampled","method":"legacy-file-sample","at":"2026-06-13T18:44:37.183Z"},"url":"https://mcp.waymark.network/r/dc3c6aac-a1eb-485c-8bc6-dfb8d30f24d3"}