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Kubernetes Event-driven Autoscaling with KEDA: The Complete Guide for Developers and Engineers

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"Kubernetes Event-driven Autoscaling with KEDA"

Unlock the full potential of cloud-native architectures with "Kubernetes Event-driven Autoscaling with KEDA," the definitive guide for engineers, architects, and DevOps professionals navigating the complexities of dynamic, event-driven workload scaling. This comprehensive book begins by dissecting Kubernetes autoscaling fundamentals, exploring the mechanisms and limitations of Kubernetes’ native scaling solutions. Readers are introduced to foundational concepts such as the control plane and metric-driven scaling, before delving into the unique challenges associated with unpredictable, spiky workloads typical in modern distributed systems.

The heart of the book offers an in-depth exploration into the internals of KEDA—Kubernetes-based Event Driven Autoscaling—illuminating its architecture, integration patterns, and extensibility. Readers will discover advanced techniques for integrating diverse event sources, securing event-driven pipelines, and deploying KEDA seamlessly across hybrid, edge, and multi-cloud environments. Real-world examples demonstrate how to leverage KEDA’s ScaledObjects, ScaledJobs, and custom scaler plugins to enable resilient, responsive scaling for stateless and stateful workloads alike, all while ensuring operational efficiency and cost optimization at scale.

Touching on every facet of the event-driven Kubernetes journey, the book addresses instrumentation, observability, and troubleshooting strategies tailored to highly dynamic environments. With sections on performance engineering, predictive autoscaling, building custom scalers, and contributing to the open-source KEDA project, this guide empowers practitioners to design robust, future-proof autoscaling workflows. Rounded out by best practices, anti-patterns, and migration strategies, "Kubernetes Event-driven Autoscaling with KEDA" stands as an essential resource for delivering scalable, reliable, and cost-effective cloud-native applications.

© 2025 HiTeX Press (E-bog): 6610000965335

Udgivelsesdato

E-bog: 13. juli 2025

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