Azure Kubernetes Service (AKS) allows users to run Kubernetes without managing the control plane, but understanding its pricing structure is crucial due to its complexity. Costs in AKS mainly arise from the compute resources, storage, and networking, which are billed based on Azure's pricing, not AKS itself. Compute costs, particularly from VM node pools, are typically the largest, and thus, optimizing these through strategies like right-sizing, using Spot or Reserved pricing, and effective scaling is key to cost management. AKS also offers a serverless option via Virtual Nodes, ideal for bursty workloads, which are billed based on CPU and memory usage. Azure provides flexible pricing models such as Spot VMs for lower costs on interruptible workloads and Reserved Instances for steady usage, allowing for significant savings. Accurate cost estimation requires understanding how Kubernetes consumes resources, taking into account node usage, requested versus actual resource usage, and the cost contributions from storage, networking, and load balancers. Cost optimization tools can help monitor and adjust resource usage to prevent inefficiencies.