datarobot-model-deployment

# DataRobot Model Deployment Skill This skill provides comprehensive guidance for deploying models, managing deployment configurations, and operating production deployments. ## Quick Start **Most common use case**: Deploy a trained model to production 1. **Get best model**: Find the best model from a project (highest metric score) 2. **Create deployment**: `create_deployment(model_id, deployment_name)` to deploy model 3. **Get endpoint**: `get_deployment_endpoint(deployment_id)` to retrieve prediction URL **Example**: "Deploy the best model from project abc123 as 'Sales Prediction v1'" ## When to use this skill Use this skill when you need to: - Deploy trained models to production - Configure deployment settings and environments - Manage multiple deployments - Replace a deployment’s champion model with a new model version - Configure prediction servers and environments - Monitor deployment health and status - Manage deployment access and permissions ## Key capabilities ### 1. Deployment Creation - Deploy models from projects or registered models - Choose prediction environment (DataRobot Serverless, external) - Configure deployment settings (challenger models, A/B testing) - Set up deployment metadata and descriptions ### 2. Deployment Configuration - Configure prediction servers and environments - Set up batch prediction settings - Configure real-time prediction endpoints - Manage deployment credentials and access ### 3. Deployment Management - Replace deployme...