Each Job keeps a snapshot of all your files, including any results the code creates or modifies. This includes charts, tables, data files, and serialized model data. All assets are versioned and can be compared across different Jobs. See Domino service filesystem to learn more about the filesystem environment your Jobs will run in.
When you start a Job, Domino launches a new environment for your code on the target executor. You can start multiple concurrent Jobs. Each gets its own container environment, so you can try multiple parameters and techniques in parallel. You can schedule recurring Jobs and set up notifications, including customized reports.
The following lists the supported file types and the commands that Domino executes when it runs the file type:
There are many ways to start Jobs in Domino.
From the navigation pane, click Jobs. The Jobs dashboard shows all Jobs from the history of your project, sorted into tabs by Job status.
Click Run to start a new Job.
In the Start Run window, configure the Job. Enter the File Name of the script you want Domino to execute, followed by any arguments for the script.
You can start a Job directly from the project Files page.
Go the file you want to run and click the gear icon at the end of the row in the files list, then click Run.
Use the window to configure the Run. This window has additional options to set up recurring scheduled Jobs and select different hardware tiers.
In this field, enter a name for the Job. This name will be the label for the Job in the Jobs dashboard.
If there are any arguments or parameters you’d like to pass to your script, enter them here.
- Hardware tier
This dropdown list lets you set the hardware tier used by the Job.
- Schedule to repeat
In this section, specify if you want the run to execute only once, or to repeat on a schedule.
- Publish after complete
Check this if you want Domino to republish a Model API once the Job completes successfully.
From your workstation, you can start Jobs through the Domino CLI . Follow these instructions to install the CLI on your system.
After you have logged in and opened a project, you can start Jobs with:
domino run <filename>
domino run calculateStats.r
domino run runModel.m model1 .05
domino run --wait runModel.m model1 .05
domino run --direct "pip freeze | grep pandas"
Use Domino to schedule Jobs in advance, and set them to execute on a regular schedule. These can be useful when you have a data source that is updated regularly.
A Launcher is a web form that rests on top of a script that Domino can execute in a Job. You can use a Launcher to pass arguments to your script from UI fields in a customized web form.
You can use the Domino API to start a Job with a POST request to:
For more information about how to send valid configuration data, read the API docs.
Click Jobs from the Project menu to open the Jobs dashboard. A table lists all Jobs from the history of this Project, sorted into tabs by queued, running, completed, and archived state. You can use the Jobs dashboard to find, manage, and view results from your Jobs in the following ways:
Click a row in the Jobs dashboard table to see a panel with details on the listed Job. You can filter the table by Job title with the Search box.
Domino retains up to 15 days worth of run usage details. This applies to all Runs and includes Jobs, Workspace sessions, and web apps.
You can tag an individual job by clicking
+ under the Job title in the
You can also bulk tag Jobs by checking them in the table and then clicking Bulk Tag.
Once any Jobs in a Project have been tagged, the Project menu will contain an expandable list under the Jobs header with quick links to filtered views of those tagged Jobs.
You can create a Jobs comparison report by checking exactly two Jobs in the table, then clicking Compare.
Click the funnel icon above the table of Jobs to customize which columns
are shown in the Jobs dashboard. If any Jobs in your
project have produced
Run diagnostic statistics,
the keys from
dominostats.json will become available as columns,
allowing you to quickly compare these outputs.