Moving complex enterprise platforms to production requires robust, resilient cloud-native infrastructure. However, traditional resource-based autoscaling (such as standard CPU or Memory metrics) fails to react quickly enough to unpredictable traffic spikes and high-concurrency data streams passing through distributed backend layers.

In this deeply technical session, we will break down how to architect a highly responsive backend system using Azure Kubernetes Service (AKS). We will explore real-world production blueprints for implementing Kubernetes Event-driven Autoscaling (KEDA) to scale microservices dynamically based on actual application demand, system queue depths, and message brokers.