Chapter 11: Performance Monitoring
In this chapter, you will learn about the important and relevant area of Machine Learning (ML) operations and how to ensure a smooth ride in the production systems developed so far in this book using best practices in the area and known operational patterns. We will understand the concept of operations in ML, and look at metrics for monitoring data quality in ML systems.
Specifically, we will look at the following sections in this chapter:
- Overview of performance monitoring for ML models
- Monitoring data drift and model performance
- Monitoring target drift
- Infrastructure monitoring and alerting
We will address some practical reference tools for performance and reliability monitoring of ML systems.
