dstack vs Voda Scheduler
dstack
dstack.aiVoda Scheduler
github.comSide by side
| Figure | dstack | Voda Scheduler |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 0 |
| Spec score · GPU Cluster Management Software | 8.9 (#1) | 6.5 (#18) |
| API | dstack offers an HTTP API for functionality not available in the CLI and for integrations that need to call the server directly. | The project documentation links to API endpoints as part of its getting-started steps. |
| Deployment | The server can run on a laptop or another environment with access to the cloud and on-prem clusters being used. | The project says Voda Scheduler is designed to deploy in any Kubernetes cluster, on-cloud or on-premise, that can schedule GPUs. |
| Purpose | dstack is an open-source orchestration layer for AI workloads on heterogeneous accelerators, including GPU clouds, Kubernetes, VMs, and bare-metal clusters. | Voda Scheduler is a GPU scheduler for elastic deep learning workloads built on Kubernetes, Kubeflow Training Operator, and Horovod. |
Plans
In their own words
dstack
dstack is an open-source orchestration layer for AI workloads across GPU clouds, Kubernetes, virtual machines, and bare-metal clusters. YAML configurations define fleets, development environments, tasks, services, presets, and volumes, while dstack handles provisioning and job scheduling, including auto-scaling, port forwarding, and ingress. Supported accelerators include NVIDIA, AMD, TPU, and Tenstorrent. Documented backends include AWS, Azure, GCP, Kubernetes, GPU cloud providers, remote SSH hosts, and experimental Slurm. Tasks can use frameworks such as accelerate, torchrun, Ray, and Spark. Users manage resources through the CLI or HTTP API, and the server can run on a laptop or another environment that can access the clusters in use. Services can publish inference endpoints through gateways with HTTPS, custom domains, auto-scaling, and rate limits. The self-hosted open-source stack is free. Server data and project secrets are stored in plaintext by default unless administrators configure AES-256-GCM encryption. TPU support is limited to single-host instances with up to eight cores. GPU Marketplace usage is prepaid, with prices that vary by GPU and provider and appear in the console before provisioning.
Voda Scheduler
Voda Scheduler has no write-up on Specifiction yet; its figures are above.