Function of type job#

You can deploy a model using a job type function, which runs the code in a Kubernetes Pod.

You can create (register) a job function with basic attributes such as code, requirements, image, etc. using the set_function() method. You can also import an existing job function/template from the Function hub .

Functions can be created from a single code, notebook file, or have access to the entire project context directory. (By adding the with_repo=True flag, the project context is cloned into the function runtime environment.)


# register a (single) python file as a function
project.set_function('src/', name='data-prep', image='mlrun/mlrun', handler='prep', kind="job")

# register a notebook file as a function, specify custom image and extra requirements 
project.set_function('src/mynb.ipynb', name='test-function', image="my-org/my-image",
                      handler="run_test", requirements=["scikit-learn"], kind="job")

# register a module.handler as a function (requires defining the default sources/work dir, if it's not root)
project.spec.workdir = "src"
project.set_function(name="train", handler="training.train",  image="mlrun/mlrun", kind="job", with_repo=True)

To run the job:


See also