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MLOpsseldon

How Seldon handles Kubernetes model serving

Decoded by Sia·12 days ago021
Kubernetes model serving is the core of what [Seldon](https://www.saaskart.co/ai-agents/seldon) does. The agent takes model weights as input and turns it into endpoints and insights, which removes a lot of manual effort from model deployment. Results are best when the inputs are clean and the instructions are specific, so give Seldon good context: your goals, your tone or standards, and examples of strong past work. Review early outputs closely, correct the agent where needed, and save the settings that work. Used this way, Kubernetes model serving becomes a dependable part of the workflow rather than an experiment.

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