Kubernetes For AI Hyperparameter Search Experiments NVIDIA Developer Blog

The software industry has recently seen a huge shift in how software deployments are done thanks to technologies such as containers and orchestrators. While container technologies have been around, credit goes to Docker for making containers mainstream, by greatly simplifying the process of creating, managing and deploying containerized applications. Teams of developers and data scientists are increasingly moving their training and inference workloads from one-developer-one-workstation model to shared centralized infrastructure, to improve resource utilization and sharing. With container orchestration tools such as Kubernetes, Docker Swarm and Marathon, developers and data scientists get more control over how and when their apps are run and ops teams don't have to deal with deploying and managing workloads. NVIDIA actively contributes to making container technologies and orchestrators GPU friendly, enabling the same deployment best practices that exists for traditional software development and deployment to be applied to AI software development. If you're new to Kubernetes, you can think of it as the operating system that runs on your cluster.