To derive business insights from your data science work, you need to deploy the trained model to an environment where it can be invoked. This process often involves complex DevOps skills and coordination between teams like Data Science, Engineering, and IT. With Domino, the model deployment process is seamless. This simplification allows your teams to derive insights and make critical business decisions.
Domino simplifies the process of deploying models regardless of the scenario in which it is deployed:
- Host Models as REST APIs
You can host models trained on Domino, or imported from outside, as REST interfaces for interactive and low-latency use cases.
- Use Batch Scoring
Domino’s jobs infrastructure helps you deploy models for performing predictions in bulk using distributed compute environments.
- Export to SageMaker
To take advantage of large-scale compute in the cloud or at edge networks, Domino helps package your models and set them up for deployment in AWS Sagemaker (scaling in the cloud).
- Integrate with CI/CD Workflows
Learn how to support sudden bursts in traffic while adhering to strict requirements: SLA, uptime, security, legal, or loyalty.