InfluxDB for Model Monitoring: Metrics, Observability, and Performance Tracking for Modern Applications - Couverture souple

Ming, Alex

Couverture souple

ISBN 13 : 9798247662914

Editeur : Independently published, 2026

Synopsis

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:

1. Designing time-series structures for model workloads
2. Writing data from Python and application servers
3. Creating dashboards for latency and usage trends
4. Detecting anomalies and drift
5. Setting up alerts and notifications
6. Retention policies and storage optimization
7. Integrating logs with metrics for deeper insight

The 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.

Détails de l'édition

• Éditeur: Independently published
• Date d'édition: 2026
• Langue: anglais
• ISBN 13: 9798247662914
• Reliure: Broché
• Nombre de pages: 186
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible