Scaling AI backend applications efficiently in Kubernetes is crucial for handling fluctuating high traffic. This article dives deep into Horizontal Pod Autoscaling (HPA), explaining how to leverage standard and custom metrics to dynamically adjust your AI inference services. Learn best practices, configuration details, and advanced strategies to ensure your AI models perform optimally under any load, maintaining responsiveness and managing infrastructure costs effectively.