Szczegóły ebooka

Kubernetes Autoscaling. Build efficient, cost-optimized clusters with KEDA and Karpenter

Kubernetes Autoscaling. Build efficient, cost-optimized clusters with KEDA and Karpenter

Christian Melendez, Jonathan Innis, Brandon Wagner, Jan Wozniak

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EBOOK
Kubernetes is the backbone of modern containerized infrastructure, but scaling it efficiently remains a challenge. Kubernetes Autoscaling equips cloud professionals with this comprehensive guide to dynamically scaling applications and infrastructure using the powerful combination of Kubernetes Event-Driven Autoscaler (KEDA) and Karpenter, AWS’s next-generation cluster autoscaler.
You’ll begin with autoscaling fundamentals, move through HPA and VPA, and then get hands-on KEDA for event-driven workloads and Karpenter for data plane scaling. With the help of real-world use cases, best practices, and detailed patterns, you’ll deploy resilient, scalable, and cost-effective Kubernetes clusters across production environments.
By the end of this book, you’ll be able to implement practical autoscaling strategies to improve performance, reduce cloud costs, and eliminate over-provisioning.
  • 1. Introduction to Kubernetes Autoscaling
  • 2. Workload Autoscaling Overview
  • 3. Workload Autoscaling with HPA and VPA
  • 4. Kubernetes Event-Driven Autoscaling (KEDA)
  • 5. KEDA in Action on AWS EKS
  • 6. Metrics, Monitoring, and Observability
  • 7. Data Plane Autoscaling Overview
  • 8. Getting Started with Karpenter
  • 9. Karpenter on AWS
  • 10. Karpenter Management Operations
  • 11. Practical Use Cases
  • 12. Patterns and Best Practices
  • Tytuł:Kubernetes Autoscaling. Build efficient, cost-optimized clusters with KEDA and Karpenter
  • Autor:Christian Melendez, Jonathan Innis, Brandon Wagner, Jan Wozniak
  • Tytuł oryginału:Kubernetes Autoscaling. Build efficient, cost-optimized clusters with KEDA and Karpenter
  • ISBN:9781836643821, 9781836643821
  • Data wydania:2025-12-05
  • Format:Ebook
  • Identyfikator pozycji: e_4jaj
  • Wydawca: Packt Publishing
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