This Azure AKS video demonstrates cost optimization via autoscaling. George shows how to scale node pools to zero, deallocating (not deleting) nodes for rapid scaling when demand increases, minimizing costs during low-demand periods. He highlights configuration options within the Azure portal and the benefits of ARM64 architecture and spot instances. George introduces AKS autoscaling, explaining how DevOps engineers can optimize costs by scaling node pools to zero when applications aren't in high demand. He highlights the ability to scale down to zero nodes, significantly reducing costs during periods of low activity. George clarifies the concept of node pools in AKS, differentiating between the control plane (system node pool) and the data plane (user node pools). He explains how separating node pools can improve application performance by preventing "noise neighbors" and enabling better resource allocation for different application components. George discusses cost-saving strategies, including using ARM64 architecture for cheaper VMs and deploying spot instances. He emphasizes the importance of configuring the cluster autoscaler to scale down quickly (e.g., within 3 minutes) to minimize costs during periods of low demand. He demonstrates how to configure the node pool to scale to zero, eliminating costs when no applications are running.George demonstrates configuring AKS to scale down to zero nodes. He explains the difference between deallocating and deleting nodes, highlighting the benefits of deallocation for faster scaling up when demand increases. He explains that deallocating nodes saves money by only paying for storage, not compute resources. George shares a real-world example of a customer who benefited from AKS autoscaling. He contrasts the speed and cost-effectiveness of AKS's deallocation approach with traditional autoscaling methods that can be slower due to cloud-init scripts and other delays. This segment emphasizes the practical advantages of the AKS approach. This segment details the advantages of deallocating nodes instead of deleting them in AKS node pools. It highlights the significant time savings (30-40 seconds vs. minutes) in node provisioning, enabling rapid scaling of web applications to meet demand spikes. The discussion also covers setting minimum instance counts to ensure quick response times while avoiding unnecessary costs during low-demand periods. The practical demonstration using the AKS console showcases the configuration options and their impact on resource utilization and cost optimization, emphasizing the use of lightweight Linux distributions for improved boot times and performance. George shows how to configure node pools for specific application requirements (e.g., ARM64) and demonstrates deploying an application with multiple instances. He highlights the use of tolerations to ensure applications are scheduled only on appropriate nodes and the seamless integration with Azure Container Registry using managed identities.