dstack vs Kueue
dstack
dstack.aiKueue
kueue.sigs.k8s.ioSide by side
| Figure | dstack | Kueue |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 1 |
| Spec score · GPU Cluster Management Software | 8.9 (#1) | 8.0 (#7) |
| Purpose | dstack is an open-source orchestration layer for AI workloads on heterogeneous accelerators, including GPU clouds, Kubernetes, VMs, and bare-metal clusters. | Kueue manages quotas and job resource consumption in Kubernetes, deciding when jobs wait, start, or are preempted. |
| What it does | dstack is an open-source orchestration layer for AI workloads across GPU clouds, Kubernetes, VMs, and bare-metal clusters. | Kueue manages quotas and job resource consumption, deciding when jobs wait, start, or are preempted. |
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.
Kueue
Kueue is a free Kubernetes project that manages quotas and job resource consumption, deciding when workloads wait, start, or are preempted. It installs on a standard Kubernetes cluster without replacing existing components. Its scheduling tools include priority-based queues, fair sharing, quota borrowing between teams, resource flavor fungibility, preemption policies, and all-or-nothing scheduling. Built-in integrations cover Kubernetes Jobs and Pods, Kubeflow training jobs, Ray jobs and clusters, JobSet, AppWrapper, Deployments, StatefulSets, and LeaderWorkerSet. MultiKueue can find capacity and dispatch workloads across clusters, while topology-aware scheduling accounts for data center layout to improve communication throughput between pods. Kueue provides Prometheus metrics and an endpoint for viewing pending workloads. Installation instructions cover kubectl, Helm, and source builds. The guide recommends Kubernetes 1.34 or newer and officially supports and tests only those versions. Kueue also provides administrator and user ClusterRoles, with resource-specific roles that can be composed into custom roles. Its webhook server includes internal certificate management, and the installation guide links to cert-manager instructions.