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"item_title" : "InfluxDB for Model Monitoring",
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"item_description" : "InfluxDB for Model Monitoring teaches how to observe and measure the behavior of language-driven applications using time-series data. The book focuses on building dashboards and alerting systems that reveal what is truly happening inside production workloads.Readers discover how to collect inference latency, token throughput, error rates, GPU utilization, and custom business metrics into InfluxDB. Step-by-step tutorials show how to design schemas, write efficient queries, and create real-time visualizations with Grafana and native tools.Inside the book you will learn: Designing time-series structures for model workloadsWriting data from Python and application serversCreating dashboards for latency and usage trendsDetecting anomalies and driftSetting up alerts and notificationsRetention policies and storage optimizationIntegrating logs with metrics for deeper insightThe focus is practical observability knowing when systems are slowing down, why costs are rising, and how users are interacting with deployed models. Examples are tool-agnostic and can be applied to cloud or on-premise environments.This book is ideal for engineers who need reliable monitoring rather than guesswork.",
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InfluxDB for Model Monitoring : Metrics, Observability, and Performance Tracking for Modern Applications
by Alex Ming
Overview
InfluxDB for Model Monitoring teaches how to observe and measure the behavior of language-driven applications using time-series data. The book focuses on building dashboards and alerting systems that reveal what is truly happening inside production workloads.
Readers discover how to collect inference latency, token throughput, error rates, GPU utilization, and custom business metrics into InfluxDB. Step-by-step tutorials show how to design schemas, write efficient queries, and create real-time visualizations with Grafana and native tools.
Inside the book you will learn:
- Designing time-series structures for model workloads
- Writing data from Python and application servers
- Creating dashboards for latency and usage trends
- Detecting anomalies and drift
- Setting up alerts and notifications
- Retention policies and storage optimization
- Integrating logs with metrics for deeper insight
This book is ideal for engineers who need reliable monitoring rather than guesswork.
This item is Non-Returnable
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Details
- ISBN-13: 9798247662914
- ISBN-10: 9798247662914
- Publisher: Independently Published
- Publish Date: February 2026
- Dimensions: 10 x 7 x 0.4 inches
- Shipping Weight: 0.74 pounds
- Page Count: 188
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