KubeCon + CloudNativeCon North America 2024

Imagine managing a set of diverse workloads on a Kubernetes node, operating across dozens of CPU cores and several memory zones. But do you truly comprehend the difference between one CPU core versus another? Are you aware of the impact that different memory zone might have on your workload's efficiency? Will optimisations for one type of workloads be helpful for another? Do you think that your ML workload will behave same way as e.g. Redis? This presentation delves deep into CPU internals, memory types (DRAM, HBM, CXL), and diverse cache/core types and layouts. Explore recent hardware advancements and their impact on workloads. We'll examine native compute resource allocation strategies from a hardware point of view, crucial for enhancing workload performance and optimising energy usage and cost efficiency. Join and learn details of the modern hardware architecture that gives you a framework to make more informed choices on hardware resource optimisation for your infrastructure.