
When this happens...
New Client Is Created
Client Is Updated
Client Is Deleted
New Invoice Is Created
Invoice Updated
New Job Is Created
Job Is Closed
Job Is Updated
New Quote Is Created
Quote Approved
Quote Sent
New Request Created

Automatically do this!
Create a Container Registry
Create a Template
Find a Container Registry Auth
Delete a Container Registry Auth
Delete a Template
Create Registry Authentication
When this happensTriggers
A trigger is an event that starts a workflow.
Runs when new client is created
Runs when client is updated
Runs when Client Is Deleted
Runs when New Invoice Is Created
Runs when invoice is updated
Runs when new job is created
Action is the task that follows automatically within your Jobber integrations.
Create a new container registry auth
Create a new template.
Get a single container registry auth
Delete a single container registry auth
Delete a single template by its id.
Create Registry Authenticationin Runpod

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To start, connect both your Jobber and RunPod accounts to viaSocket. Once connected, you can set up a workflow where an event in Jobber triggers actions in RunPod (or vice versa).
Absolutely. You can customize how Jobber data is recorded in RunPod. This includes choosing which data fields go into which fields of RunPod, setting up custom formats, and filtering out unwanted information.
The data sync between Jobber and RunPod typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Jobber and RunPod. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
Jobber is the command centre for home service businesses. Our easy-to-use app powers sales, operations, and customer service—all in one place.
Learn MoreRunPod is a platform that provides cloud-based computing resources for running and managing machine learning models, data processing tasks, and other computational workloads. It offers scalable and efficient solutions for developers and data scientists to deploy and execute their projects seamlessly.
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