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Generative AI Observability
Paperback
€65.98
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- Book Synopsis
- The book takes you on a step-by-step engineering journey, starting with core observability architectural principles and data-driven monitoring strategies. You will master OpenTelemetry, handling context propagation and advanced tracing techniques across complex microservices and Kubernetes monitoring environments. From there, you will learn to optimize an open-source intelligent monitoring toolchain featuring Prometheus, OpenSearch, Grafana, and Jaeger. We will also learn how generative AI is being applied in real environments to interpret incidents, reduce noise, and support operational judgment, including where it helps and where caution is still needed.
- About The Author
- Siva Guruvareddiar has spent over 20 years building production-grade distributed systems, with the last four focused on one problem: making AI infrastructure observable, measurable, and production-ready. He contributed an AI inference observability blueprint to the OpenTelemetry project, three production dashboards to the NVIDIA DCGM Exporter, and an autoscaling integration to CNCF KEDA that ships in active enterprise deployments. His open-source reference implementation for end-to-end observability of multi-agent AI systems on Kubernetes has been downloaded over three million times. A senior specialist solutions architect at AWS and an author, he brings both the engineering depth of someone who has instrumented GPU inference pipelines in production and the practitioner's instinct for what actually holds up when agentic systems meet real enterprise constraints.
- Product Details
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- ISBN
- 9789378548871
- Format
- Paperback
- Publisher
- BPB Publications, (31 July 2026)
- Number of Pages
- 280
- Language
- English
- Dimensions
- 235 x 191 mm
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