Scale Smarter Not Harder: How Extending Cluster Autoscaler Saves Mi... Rahul Rangith & Ben Hinthorne
Rahul Rangith, Ben Hinthorne
KubeCon + CloudNativeCon Europe 2025 · Session
In this insightful talk from KubeCon EU, Datadog software engineers Ben Hinthorne and Rahul Rangith unveil a sophisticated approach to Kubernetes node autoscaling that has yielded millions in cost savings for their vast infrastructure. The presentation delves into how Datadog, operating Kubernetes across dozens of multi-cloud clusters with tens of thousands of nodes and hundreds of thousands of pods, tackled the complex challenge of optimizing instance type selection. Their solution leverages and extends the native Kubernetes Cluster Autoscaler to dynamically identify and provision the most cost-efficient, performant, and reliable instance types for diverse workloads.
AI review
This talk from Datadog engineers presents a genuinely impressive deep-dive into how they've extended Kubernetes Cluster Autoscaler to achieve millions in cost savings. They've built a sophisticated ecosystem of custom tooling, including an instance type adviser, performance benchmarks, and dedicated controllers, all leveraging the CA's gRPC expander. It's a prime example of real-world, large-scale infrastructure optimization, demonstrating significant technical skill and tangible financial impact.