dstack
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About
dstack is an open-source alternative to Kubernetes and Slurm, designed to simplify GPU allocation and AI workload orchestration for ML teams across top clouds, on-prem clusters, and accelerators. It provides a unified interface on top of GPU clouds, simplifying development, training, and deployment for ML teams. It enables more flexible and cost-effective provisioning and management of clusters. dstack works with any open-source or proprietary frameworks, making it developer-friendly and vendor-agnostic for training and deploying AI models.
Platform
Task
Features
• deploying auto-scaling model endpoints
• scheduling jobs on clusters and single instances
• launching containerized dev environments
• orchestrating workloads on existing clusters
• efficient cloud gpu provisioning and utilization
FAQs
How does dstack compare to Kubernetes?
Kubernetes is a widely used container orchestrator designed for general-purpose deployments. dstack focuses on container orchestration specifically for AI workloads, with the goal of making life easier for ML engineers.
How does dstack differ from Slurm?
Slurm excels at job scheduling across pre-configured clusters. dstack goes beyond scheduling, providing a full suite of features tailored to ML teams. This makes dstack a more comprehensive solution for AI workloads.
When should I use dstack?
dstack is designed for ML teams aiming to speed up development while reducing GPU costs across top cloud providers or on-prem clusters.
Pricing Plans
Free
Free PlanJob Opportunities
There are currently no job postings for this AI tool.
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