Connect Clockify and RunPod to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Clockify
Choose an Action
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
Enable Integrations or automations with these events of Clockify and RunPod
Enable Integrations or automations with these events of Clockify and RunPod
Actions
Find Project
Find a Project in a workspace.
Update a Client
Update your Client here
Delete a Client
Delete a Client
Create Client
Create a new client
Find Client
Find a Client in Workspace.
Find Task
Find Task by Name on a specified project and workspace.
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- Send for Approval acceptCreate Entry of expensesAdd Step
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Frequently Asked Questions
To start, connect both your Clockify and RunPod accounts to viaSocket. Once connected, you can set up a workflow where an event in Clockify triggers actions in RunPod (or vice versa).
Absolutely. You can customize how Clockify 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 Clockify 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 Clockify 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 Clockify
Clockify, a time tracking and timesheet application, enables project-based work hour tracking for unlimited users at no cost.
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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