Kubernetes Autoscaling

Learn to scale workloads efficiently, reduce cloud costs, and optimize performance with real-world strategies for event-driven and infrastructure-level scalingKey FeaturesAutoscale Kubernetes workloads and infrastructure using KEDA and KarpenterImprove performance, reduce cloud costs, and eliminate resource waste with smarter scalingWork with hands-on labs, real-world use cases, and step-by-step guidance from the creator of Karpenter BlueprintsFree with your book: PDF Copy, AI Assistant, and Next-Gen ReaderBook DescriptionKubernetes 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.What you will learnGain a solid foundation in Kubernetes autoscaling and its componentsScale deployments, jobs, and StatefulSets using KEDA's CRDsConfigure event-based scaling strategies using metrics and schedulesDeploy and manage Karpenter for on-demand infrastructure provisioningExplore advanced node disruption and lifecycle techniquesCombine KEDA and Karpenter to implement full-stack autoscalingOptimize costs using Spot Instances, scale-to-zero, and workload placementApply real-world patterns and monitor autoscaling performance in productionWho this book is forThis book is ideal for DevOps engineers, SREs, cloud architects, and Kubernetes professionals who want to optimize resource usage and improve scalability. A basic understanding of Kubernetes concepts and cloud environments, i.e., AWS, GCP, and Azure, is assumed.]]>