AWS Certified Machine Learning – SpecialtyMachine Learning Implementation and OperationsMedium
A data engineering team is building a new feature store to manage features for various machine learning models across their organization. They need a solution that can serve features with very low latency for real-time inference, as well as provide historical feature data for model training and batch inference. Which SageMaker component or mode of operation of the Feature Store meets both of these requirements?
- ASageMaker Feature Store - Online Store only
- BSageMaker Feature Store - Offline Store only
- CSageMaker Feature Store - Online and Offline Stores
- DSageMaker Feature Store - Data Catalog integration
Show answer & explanationAnswer & explanation
Correct answer: C. SageMaker Feature Store - Online and Offline Stores
Amazon SageMaker Feature Store is designed with both an Online Store and an Offline Store. The Online Store provides low-latency access to the latest feature values for real-time inference, while the Offline Store stores historical feature data for model training, batch inference, and analytical purposes. Using both modes simultaneously ensures all requirements are met.
Why the other options are wrong
- A. The Online Store alone provides low-latency access for real-time inference but lacks the historical data needed for training and batch inference.
- B. The Offline Store alone provides historical data for training and batch inference but cannot serve features with the low latency required for real-time inference.
- D. Data Catalog integration helps with feature discovery and metadata but does not provide the storage and serving capabilities for both real-time and historical feature access.
SageMaker Feature Store (Online/Offline)
A fully managed service that provides a centralized repository for machine learning features, consisting of an Online Store for low-latency real-time inference and an Offline Store for historical data for training and batch inference.
- Online Store for real-time, low-latency feature retrieval.
- Offline Store for historical data, training, and batch inference.
- Ensures consistency between training and inference features.
- Simplifies feature management and reuse.
Memory trick: Feature Store: Two sides of a coin, one fast, one deep.