Historically, running AI/ML workloads on Kubernetes has been challenging due to the substantial CPU/GPU resources these workloads typically demand.
However, things are now changing. The Cloud Native Computing Foundation (CNCF), a nonprofit organisation that promotes the development and adoption of Kubernetes, recently released a new update, Kubernetes 1.31 (Elli).
Elli introduces enhancements designed to improve resource management and efficiency, making it easier to handle the intensive requirements of AI and ML applications on Kubernetes.
Enterprises are increasingly turning to cloud native applications, especially Kubernetes, to manage their AI workload. According to a recent Pure Storage survey of companies with 500 employees and more, 54% said they were already running AI/ML workloads on Kubernetes.
Around 72% said they run databases on Kubernetes and 67% ran analytics. Interestingly, the numbers are expected to rise as more and more enterprises turn to Kubernetes. This is because the development of AI and ML models is …