Connect RunPod and Nyckel to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for RunPod
Choose an Action
Automatically do this!
Import to Classifier
Classify
Center Detect
Train Classifier
Enable Integrations or automations with these events of RunPod and Nyckel
Enable Integrations or automations with these events of RunPod and Nyckel
Actions
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 RunPod and Nyckel accounts to viaSocket. Once connected, you can set up a workflow where an event in RunPod triggers actions in Nyckel (or vice versa).
Absolutely. You can customize how RunPod data is recorded in Nyckel. This includes choosing which data fields go into which fields of Nyckel, setting up custom formats, and filtering out unwanted information.
The data sync between RunPod and Nyckel 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 RunPod and Nyckel. 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 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.
Learn MoreAbout Nyckel
Nyckel is a platform that provides machine learning as a service, enabling users to easily integrate AI capabilities into their applications without needing extensive knowledge in data science or machine learning. It offers tools for creating, training, and deploying machine learning models with ease.
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