Autoscaling Configuration

Overview

Implement autoscaling strategies to automatically adjust resource capacity based on demand, ensuring cost efficiency while maintaining performance and availability.

When to Use

• Traffic-driven workload scaling
• Time-based scheduled scaling
• Resource utilization optimization
• Cost reduction
• High-traffic event handling
• Batch processing optimization
• Database connection pooling

Implementation Examples

1. Kubernetes Horizontal Pod Autoscaler

# hpa-configuration.yaml
apiVersion: autoscaling/v2