Computing jobs can be converted to Kubernetes workloads and scheduled in batches to deliver optimal performance.
Co-scheduling, fair-share scheduling, gang scheduling, topologies, reservation/backfill, data-aware scheduling, and more
Managing jobs with multiple templates
Singularity and GPU Accelerators
Logging, metrics, and dashboard
A Kubernetes native system for high-performance workloads
Volcano is system for running high-performance workloads on Kubernetes. It features powerful batch scheduling capability that Kubernetes cannot provide but is commonly required by many classes of high-performance workloads, including:
These types of applications typically run on generalized domain frameworks like TensorFlow, Spark, PyTorch, and MPI. Volcano is integrated with these frameworks to allow you to run your applications without adaptation efforts while enjoying remarkable batch scheduling.
A powerful batch scheduler that allows you to run multi-architecture, computing-intensive jobs as Kubernetes workloads