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. Read about the 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.
There are many ways to start Jobs in Domino.
Click Jobs from the Project menu to open the Jobs dashboard. This dashboard shows all Jobs from the history of your project, sorted into tabs by Job status.
Click Run at the top to start a new Job.
After clicking Run, you will see a Start Run window with options to configure the Job. You need to enter the filename of the script you want Domino to execute, followed by any arguments the script takes.
You can start a Job directly from the project Files page. Find the file you want to run and click the gear icon to the right of its entry in the files list, then click Run.
You will then see a dialog you can use to configure the Run. This window has additional options to set up recurring scheduled Jobs and select different hardware tiers.
TitleIn this field, enter a name for the Job. This name will be thelabel for the Job in the Jobs dashboard.
ParametersIf there are any arguments or parameters you’d like to pass to yourscript, enter them here.
Hardware tierThis dropdown list lets you set the hardware tier used by the Job.
Schedule to repeatIn this section, specify if you want the run to execute only once,or to repeat on a schedule.
Publish after completeCheck this if you want Domino to republish aModel API oncethe Job completes successfully.
From your workstation, you can start Jobs through the Domino CLI . Follow these instructions to install the CLI on your system.
Once 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"
Domino allows you 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.
Click Jobs from the Project menu to open the Jobs dashboard. Here you can see a table of 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 details panel.
You can also bulk tag Jobs by checking them in the table and then clicking the Bulk Tag button.
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 archive Jobs by checking them in the table and clicking the Bulk Archive button.
You can find currently running Jobs on the Running tab, and stop them by checking them and clicking the Bulk Stop button.
You can create a Jobs comparison report by checking exactly two Jobs in the table, then clicking the Compare button.
Click the funnel icon above the table of Jobs to customize which columns are displayed in the Jobs dashboard. Note that 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.