dstack
6.9#2 in gpu cluster management softwareFree planFree planWebAPILinuxmacOS
Visitdstack vs NVIDIA Mission Control
NVIDIA Mission Control
5.4#16 in gpu cluster management softwareWebLinuxSelf-hosted
VisitWhat both publish
| Fact | dstack | NVIDIA Mission Control |
|---|---|---|
| Deployment | The server can run on a laptop or another environment with access to the cloud and on-prem clusters being used. | The 2.3 release adds an option for a virtualized control plane and deployment in air-gapped environments. |
| Purpose | dstack is an open-source orchestration layer for AI workloads on heterogeneous accelerators, including GPU clouds, Kubernetes, VMs, and bare-metal clusters. | NVIDIA Mission Control is an integrated AI factory management platform for enterprise AI infrastructure that combines cluster automation and operational best practices in one control plane. |
| Security | The service configuration supports authorization, which is enabled by default for services. | Mission Control offers secure configurations with validated namespace isolation and provides Kubernetes security policy files through its artifact collection. |
| Support | The documentation directs users to report issues on GitHub and ask questions in the dstack Discord server. | NVIDIA directs Mission Control customers to NVIDIA Enterprise Support Services for expert support and guidance. |
dstack plans
- dstack OSSFree
- dstack Sky GPU MarketplacePriced on request
NVIDIA Mission Control plans
- NVIDIA Mission ControlPriced on request
Pick dstack if…
dstack suits teams orchestrating AI workloads across different accelerator and infrastructure environments. It is also suited to users who want to configure workloads with YAML and manage resources through a CLI or HTTP API.
Pick NVIDIA Mission Control if…
NVIDIA Mission Control is intended for enterprise AI infrastructure teams, AI architects, and HPC operators managing AI factories. It is relevant to organizations using Slurm or Kubernetes for multi-node scheduling.