Monitoring tools and technologies

Monitoring LLMs necessitates tracking a mix of traditional system performance metrics and model-specific metrics such as accuracy and data drift. To meet these diverse needs, an array of monitoring solutions is available. These range from scalable, cloud-based platforms designed to handle extensive datasets and high-volume requests to bespoke solutions tailored to meet the specific needs of organizations. We will discuss them in detail in this section.

Cloud-based platforms

Amazon SageMaker Model Monitor is a feature of Amazon Web Services’ (AWS’s) managed machine learning (ML) service that simplifies the deployment and real-time monitoring of ML models. It automatically sets up monitoring schedules, provides visualization dashboards, and sends alerts if it detects deviations in model performance or data quality. Suitable for both tabular and text-based models, this tool scales dynamically with the workload, seamlessly integrating...