Build a Machine Learning Model Deployment Pipeline — System Design Interview Practice
Design an end-to-end ML pipeline that automates model training, validation, deployment, and monitoring with A/B testing capabilities. Work through the requirements, architecture trade-offs, and an interactive design review.
Requirements and concepts to consider
- Train models on large datasetsRequirement
- Version control for modelsRequirement
- Deploy models as APIsRequirement
- A/B test model versionsRequirement
- Monitor model performanceRequirement
- Retrain models automaticallyRequirement
- Scale inference endpointsRequirement
- Track experiments and metricsRequirement
- awsConcept to explore
- sagemakerConcept to explore
- machine learningConcept to explore
- lambdaConcept to explore
- mlopsConcept to explore
- ci cdConcept to explore