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Create a Job

Step-by-step guide to define, launch, and monitor batch jobs on Outpost.

Prerequisites

  • An Outpost account
  • The Outpost CLI installed (brew install outpostkit)
  • A training script or data processing pipeline ready to run

Launch a job from the CLI

The simplest way to run a job:

outpost jobs launch --name train-classifier --gpus A10G --cloud aws --region us-east-1 --command "python train.py --epochs 20 --batch-size 64"

Available flags:

Flag Description
--name / -n Job name (required)
--cloud Cloud provider (e.g. aws, azure)
--region Cloud region (e.g. us-east-1)
--gpus GPU type and count, e.g. A10G or A100:4
--cpus Number of vCPUs
--memory Memory in GB
--disk-size Disk size in GB
--command Command to execute (required)
--image Container image
--spot Use spot instances
--config / -c Config file
-s, --namespace Namespace (global flag)

Outpost provisions the instance, runs your command, streams logs, and terminates the instance when the command exits.

Monitor a running job

# Check job status outpost jobs status train-classifier # Stream logs in real time outpost jobs logs train-classifier

Job statuses:

Status Description
PENDING Instance is being provisioned
SETTING_UP Setup phase is running
RUNNING Main command is executing
SUCCEEDED Completed with exit code 0
FAILED Exited with non-zero code
CANCELLED Manually cancelled

Launch from the dashboard

  1. Navigate to + New > Job from the dashboard.
  2. Select GPU type, cloud provider, and region.
  3. Enter your run command and any environment variables.
  4. Click Create Job.

Logs stream in real time on the job detail page.

Cancel or delete a job

# Cancel a running job (instance terminates immediately) outpost jobs cancel train-classifier # View all jobs outpost jobs list
Tip
Save checkpoints periodically during training. If using spot instances and the instance is preempted, your job can resume from the latest checkpoint.

Next steps

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