---

name: launch-and-packaging description: "Build FedML client/server packages, validate job YAML, and launch jobs on FedML/TensorOpera with explicit credential and side-effect control." disable-model-invocation: true metadata: disco-role: operating parent_skill: "fedml" license: Apache 2.0

FedML Launch and Packaging

Use this sub-skill for fedml build, fedml train build, fedml federate build, fedml launch, and the Python launch/build APIs.

Do not use this for

• Basic login/run/cluster/storage CLI tasks: use ../setup-and-cli/SKILL.md.
• Training-loop implementation details: use ../distributed-training/SKILL.md.
• Model card lifecycle and predictor code: use ../model-serving/SKILL.md.
• Multi-job workflow DAGs: use ../workflow-orchestration/SKILL.md.

Preflight checklist

1. Read ../../references/cli-reference.md#launch-and-build.

2. Read ../../references/backend-matrix.md#workflow-backend-requirements.

3. Locate the job YAML and workspace/entry point it references.

4. Run the bundled YAML preflight helper when a local YAML file is available:

   python sub-skills/launch-and-packaging/scripts/validate_job_yaml.py path/to/job.yaml
   

5. Decide whether the requested action is package-only or remote launch.

Package-only route

Package-only tasks are safe if they do not upload or launch remote resources.

Use one of:

fedml build --help
fedml train build --help
fedml federate build --help

Python API equivalents:

import fedml.api
fedml.api.fedml_build(platform, type, source_folder, entry_point, config_folder, dest_folder, ignore)
fedml.api.train_build(job_yaml_file, dest_folder)
fedml.api.federate_build(job_yaml_file, dest_folder)

Remote launch route

Remote launch tasks require explicit approval because they can consume platform resources.

Before launching, confirm:

• API key or logged-in context.
• Backend version (release, test, dev, or local).
• Cluster or resource target, if any.
• Whether auto-created clusters/resources are allowed.
• How logs/status should be inspected after launch.

CLI and API entry points:

fedml launch job.yaml
fedml launch job.yaml -k <api-key> -c <cluster-name>

import fedml.api
result = fedml.api.launch_job("job.yaml", api_key="...")
result = fedml.api.launch_job_on_cluster("job.yaml", cluster="my-cluster", api_key="...")

A successful LaunchResult exposes result_code, result_msg, run_id, project_id, and sometimes inner_id for serving endpoints.

Repo-specific cautions

• The verified CLI root does not expose fedml jobs; older docs may mention fedml jobs start.
• Build/package can be local; launch and run inspection are backend-bound.
• Resource matching errors usually reflect YAML resource requests, cluster state, or account/provider availability.
• Original Docker/AWS/PDSH scripts are reference-only unless the user explicitly asks for that infrastructure setup.

Exit criteria

A launch/packaging task is complete when the YAML/workspace is validated, package-vs-launch intent is clear, any remote side effects are approved, and launch/build outputs or blocking errors are recorded with run ids when available.