Advanced Feature Store Implementation for ML Systems
Chapter 1: Feature Store Architectural
Core Components Revisited: Advanced Perspectives
Online Store Architectures for Low Latency
Offline Store Design for Scalability
Metadata Management Strategies
Decoupled vs. Integrated Architectures
Cross-Region and Multi-Cloud Considerations
Practice: Designing a Scalable Architecture
Chapter 2: Advanced Feature Engineering and Computation
Feature Transformation Pipelines
Handling Streaming Features
Managing Embeddings and Unstructured Data
Time-Window Aggregations at Scale
On-Demand Feature Computation
Batch vs. Real-time Computation Trade-offs
Hands-on Practical: Implementing Complex Transformations
Chapter 3: Ensuring Data Consistency and Quality
Diagnosing and Mitigating Online/Offline Skew
Point-in-Time Correctness for Training Data
Advanced Data Validation Techniques
Monitoring Feature Data Distribution
Backfilling Strategies and Challenges
Consistency Guarantees in Distributed Systems
Practice: Implementing Skew Detection
Chapter 4: Performance, Scalability, and Optimization
Benchmarking Feature Store Performance
Optimizing Online Serving Latency
Scaling Offline Computation
Storage Optimization and Cost Management
High Availability and Disaster Recovery Patterns
Capacity Planning and Load Testing
Hands-on Practical: Tuning Online Store Performance
Chapter 5: Governance, Security, and MLOps Integration
Implementing Feature Governance Frameworks
Feature Versioning Strategies
End-to-End Feature Lineage Tracking
Access Control and Security Models
Integrating Feature Stores with CI/CD Pipelines
Feature Discovery and Cataloging
Auditing and Compliance Considerations
Practice: Setting Up Feature Lineage
Chapter 6: Evaluating and Operating Feature Store Solutions
Comparing Open-Source Feature Stores (e.g., Feast)
Analyzing Managed Feature Store Services (Cloud)
Build vs. Buy Decision Framework
Operational Monitoring and Alerting
Debugging Common Feature Store Issues
Team Structure and Roles for Feature Store Management
Hands-on Practical: Evaluating a Managed Service
Access Control and Security Models
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- Security Engineering: A Guide to Building Dependable Distributed Systems, Ross J. Anderson, 2020 (John Wiley & Sons) - This comprehensive textbook covers fundamental security concepts including authentication, authorization, access control models (RBAC, ABAC), cryptography, and secure system design, relevant for understanding feature store security.
- Attribute-Based Access Control (ABAC) Definition and Considerations, Vincent C. Hu, David F. Ferraiolo, D. Richard Kuhn, and Adrian B. Feldman, 2014 NIST Special Publication 800-162 (National Institute of Standards and Technology) DOI: 10.6028/NIST.SP.800-162 - This NIST publication provides a detailed definition and considerations for Attribute-Based Access Control (ABAC), a model for fine-grained authorization in complex systems like feature stores.
- Identity and Access Management (IAM) documentation, Google Cloud, 2023 (Google) - Official documentation for Google Cloud IAM, providing practical examples and best practices for implementing cloud-native access control, relevant for integrating feature stores with cloud infrastructure.