Monitoring Plan

A robust monitoring plan is essential for ensuring the continuous health, performance, and reliability of our electricity demand forecasting model. The monitoring plan encompasses various aspects of the MLOps pipeline, including model performance, system metrics, and data quality. The integration of Prometheus, Grafana, and the ELK stack will play a pivotal role in capturing and visualizing these metrics.

Monitoring Components:

Model Performance Metrics:

• Metrics Tracked: accuracy, precision, recall, and F-1score.
• Monitoring Frequency: Real-time monitoring updated once every 100 emotion classifications.
• Alerts: Trigger alerts if tracked metrics deviates significantly from the baseline or exceeds a predefined threshold.

Resource Utilization:

• Metrics Tracked: CPU and memory usage of the deployed model containers.
• Monitoring Frequency: Real-time monitoring with Prometheus.
• Alerts: Notify if resource utilization approaches predefined limits to prevent performance degradation.

Data Quality Checks:

• Metrics Tracked: Missing values, outliers, and distribution shifts in incoming data.
• Monitoring Frequency: Daily batch checks and real-time streaming checks.
• Alerts: Flag anomalies in the data distribution or significant data quality issues.

MLFlow Tracking:

• Metrics Tracked: Experiment metrics, model versions, and deployment artifacts.
• Monitoring Frequency: Continuous tracking with every model update.
• Alerts: Notify if there are discrepancies in logged metrics or issues with model versions.

Log Management:

• Logs Tracked: Deployment logs, application logs, and error logs.
• Monitoring Frequency: Real-time log streaming with the ELK stack.
• Alerts: Alert on critical errors or unusual patterns in logs that may indicate issues.

Visualization and Reporting:

Grafana Dashboards:

• Customized Grafana dashboards will provide a visual representation of model performance, resource utilization, and other critical metrics. These dashboards will enable the operations team to quickly identify trends and potential issues.

Kibana Visualizations:

• Kibana will be used to create visualizations for log data, allowing for efficient analysis of log patterns and facilitating troubleshooting.