Performance and Scaling

Effective scaling strategies are crucial for maintaining optimal performance and cost efficiency in production Kubernetes environments. This section covers the various scaling mechanisms available in AKS to ensure your applications can handle varying workloads while optimizing resource utilization.

You’ll learn about:

• Horizontal Pod Autoscaling: Automatically scaling the number of pod replicas based on CPU, memory, or custom metrics
• Vertical Pod Autoscaling: Dynamically adjusting CPU and memory requests and limits for running pods
• Cluster Autoscaler: Automatically scaling the number of nodes in your cluster based on resource demands
• Node Autoprovisioner: Advanced node provisioning strategies for optimal resource allocation
• KEDA (Kubernetes Event-Driven Autoscaling): Event-driven autoscaling for serverless workloads and external triggers

By the end of this section, you’ll understand how to implement comprehensive scaling strategies that ensure your applications perform optimally while maintaining cost efficiency.