Autoscaling is a critical component of cloud-native architectures, but true elasticity requires more than just setting CPU thresholds. This article examines the underlying control logic that powers Kubernetes and Serverless scaling. It covers how resource monitoring feeds into scaling decisions, how Serverless platforms handle concurrency-based scaling, and the importance of anti-flapping mechanisms to prevent unstable behavior. The discussion highlights the mathematical and business-aware aspects of autoscaling, moving beyond simple threshold-based rules. For engineers building or managing cloud infrastructure, understanding these mechanisms is essential for achieving cost-effective and reliable scaling. The article provides a comprehensive overview that bridges theory and practical implementation.
Explore the core mechanisms behind Kubernetes and Serverless autoscaling, including metrics, concurrency control, and anti-flapping strategies.