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Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
Workflow Data
Triggered when a workflow data is updated.
Do thisActions
Action is the task that follows automatically within your Kadoa integrations.
Create a Container Registry
Create a new container registry auth
Create a Template
Create a new template.
Find a Container Registry Auth
Get a single container registry auth
Delete a Container Registry Auth
Delete a single container registry auth
Delete a Template
Delete a single template by its id.
Create Registry Authentication
Create Registry Authenticationin Runpod
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Frequently Asked Questions
To start, connect both your Kadoa and RunPod accounts to viaSocket. Once connected, you can set up a workflow where an event in Kadoa triggers actions in RunPod (or vice versa).
Absolutely. You can customize how Kadoa 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 Kadoa 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 Kadoa 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.
About Kadoa
Kadoa is a versatile platform designed to streamline and enhance your project management and team collaboration efforts. With a focus on improving productivity and efficiency, Kadoa offers a suite of tools that facilitate seamless communication, task management, and project tracking. Ideal for teams of all sizes, Kadoa helps you stay organized and on top of your projects, ensuring that deadlines are met and goals are achieved.
Learn MoreAbout RunPod
RunPod 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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