Is your infrastructure ready to handle GenAI workloads?
GenAI workloads, which include tasks like machine learning, deep learning and AI model training, require serious computational resources. As they get bigger and more complex, having scalable infrastructure becomes essential to accommodate increasing demand. Optimising infrastructure ensures these GenAI workloads run efficiently, reducing processing time and enhancing overall performance.
If you are visiting KubeCon EU 2024, make sure you stop by Booth E25 to see how Canonical can future-proof your infrastructure for GenAI and other demanding workloads.
The Canonical approach to a future-ready infrastructure starts with Ubuntu and extends to every part of your tech stack.
What does that look like?
- Build applications with ultra-small, ultra-secure containers
- Deploy your applications on Canonical Kubernetes
- Secure your workloads against all critical vulnerabilities through a single subscription: Ubuntu Pro
- Scale your workloads according to your needs by adopting a hybrid or multi-cloud strategy
Increasing GPU Utilisation on K8s Clusters for AI/ML Workloads
Join Maciej Mazur, Principal ML Engineer at Canonical for his talk at KubeCon EU on March 22 at 11.55 CET. More details here
