Unleash the power of distributed AI/ML training on Kubernetes without breaking the bank. Discover open-source gems like Kubernetes cluster autoscalers, DASK, and Volcano that unlock intelligent scheduling, autoscaling, and resource optimization across your cluster. Explore real-world case studies on maximizing GPU utilization, right-sizing resources, and leveraging spot instances to their full potential.

Cut your compute costs by up to 60% while maintaining peak performance. Gain valuable insights into evaluating and adopting cost-effective distributed training frameworks such as Horovod, TensorFlow Distributed, and PyTorch Lightning, tailored for Kubernetes environments. Leave with actionable strategies to optimize your AI/ML pipelines for both scalability and cost-efficiency on any cloud platform.