Deep Dive

Artificial intelligence workloads are becoming some of the most valuable assets an organization runs. Models capture years of research and tuning. Datasets encode customer behavior, health information, or financial risk profiles. At the same time, more of that compute is running on infrastructure you do not fully control, whether that is a public cloud, a partner data center, or a cluster of GPUs at the edge sitting in a closet in a retail store.

Discover how setting the right CPU and memory requests and limits in Kubernetes keeps your applications running smoothly and your cloud costs in check. From basic QoS classes to advanced FinOps strategies and hidden CPU throttling pitfalls, this guide equips you with practical insights to optimize performance and budget.

As global tariffs and supply chain disruptions derail hardware procurement, containerization, hybrid cloud, and edge computing empower CIOs to build agile, resilient infrastructure—ensuring performance, flexibility, and cost control in uncertain times.