Brian Donelan, VP Cloud Platform Engineering at JPMorgan Chase, shares his ingenious side project that automatically scales Kubernetes workloads based on whether his MacBook is open or closed.
By connecting macOS screen lock events to CloudWatch, KEDA, and Karpenter, he built a system that achieves 80% cost savings by scaling pods and nodes to zero when he's away from his laptop.
You will learn:
How KEDA differs from traditional Kubernetes HPA - including its scale-to-zero capabilities, event-driven scaling, and extensive ecosystem of 60+ built-in scalers
The technical architecture connecting macOS notifications through CloudWatch to trigger Kubernetes autoscaling using Swift, AWS SDKs, and custom metrics
Cost optimization strategies including how to calculate actual savings, account for API costs, and identify leading indicators of compute demand
Creative approaches to autoscaling signals beyond CPU and memory, including examples from financial services and e-commerce that could revolutionize workload management
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