BUILDING ML INFERENCE PIPELINES WITH NUMAFLOW: REAL-TIME AI ON KUBERNETES: Deploy Anomaly Detection, Streaming Analytics and AIOps with Serverless Event Processing
This book guides you through constructing ML inference pipelines with Numaflow on Kubernetes for real-time AI. It details deploying anomaly detection, streaming analytics, and AIOps using serverless event processing, offering practical insights for scalable AI implementations in cloud-native setups.
About This Book
Building ML Inference Pipelines with Numaflow provides a comprehensive approach to implementing real-time AI solutions on Kubernetes. It focuses on leveraging Numaflow for serverless event processing to handle machine learning workloads effectively.
The book explores the deployment of key applications such as anomaly detection and streaming analytics. Readers will learn to integrate these technologies into AIOps frameworks, enabling scalable and responsive AI systems.
With practical guidance from Jules Calderon, this resource is designed for developers and engineers working with modern cloud-native environments. It emphasizes the benefits of real-time processing in enhancing operational intelligence.
Numaflow's architecture is highlighted as a powerful tool for managing data streams in Kubernetes, supporting efficient inference pipelines for AI-driven tasks.
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