Have you ever wondered how large organizations and high tech unicorns are able to build platforms on Kubernetes to run all kinds of workloads - web, stateless, stateful, batch, and even AI?
Kubernetes’ strengths in dynamic resource scheduling, automated orchestration and vibrant ecosystem of frameworks make it ideal for building AI/ML platforms. This becomes highly scalable when it combines the power of GKE hosted in the Cloud with disposable GPUs and TPUs.
In this talk we will explore some recent OSS technologies that enable efficient job management and powerful distributed computing while preventing compute resource wastage and maximising utilisation. These are essential when training and serving large Generative AI models.
Quick Info
Content
Basic Kubernetes and ML knowledge
Speaker
Tommy Tse
Tommy is a Customer Solutions Architect from Google Cloud helping customers to become more agile in delivering transformational business results. He has held various technical roles in solution architecture and software engineering within large enterprises and boutique solution partners over the past 15 years. He has been helping organisations in designing scalable digital solutions and enabling their teams to adopt cloud native architectures and modern software delivery practices.