dstack Enterprise

dstack is a streamlined alternative to Kubernetes and Slurm, designed to simplify development and deployment of AI. It works with top cloud providers and on-prem servers.

0 AWS reviews

View purchase options

Overview

dstack is a streamlined alternative to Kubernetes and Slurm, specifically designed for AI. It simplifies container orchestration for AI workloads both in the cloud and on-prem, speeding up the development, training, and deployment of AI models.

dstack is easy to use with any cloud providers as well as on-prem servers.

dstack supports NVIDIA GPU, AMD GPU, and Google Cloud TPU out of the box.

Highlights

dstack is a streamlined alternative to Kubernetes and Slurm, designed to simplify the development and deployment of AI.
It simplifies container orchestration for AI workloads across multiple clouds and on-prem, speeding up the development, training, and deployment of AI models.
dstack enables AI teams to work with any tools, frameworks, and hardware across multiple cloud platforms and on-premises.

Details

Sold by

dstack

Unlock automation with AI agent solutions

Fast-track AI initiatives with agents, tools, and solutions from AWS Partners.

Explore AI agent solutions

Features and programs

Financing for AWS Marketplace purchases

AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.

View financing details

Pricing

dstack Enterprise

Info

View purchase options

Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.

Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.

12-month contract (2)

Info

Dimension	Description	Cost/12 months
Base/Support + 60 Users	Includes a license, support, and up to 60 active users	$40,000.00
Advanced/Support + Unlimited users	Includes a license, support, and unlimited number of active users	$80,000.00

Vendor refund policy

All fees are non-cancellable and non-refundable except as required by law.

How can we make this page better?

We'd like to hear your feedback and ideas on how to improve this page.

Legal

Vendor terms and conditions

Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .

Content disclaimer

Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.

Usage information

Info

Delivery details

Container image

Supported services: Learn more

Amazon ECS
Amazon EKS
Amazon ECS Anywhere
Amazon EKS Anywhere

Container image

Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.

Version release notes

0.18.20

The update includes all the features and bug fixes from version 0.18.20.

Python 3.13 support

Following a recent Python 3.13 release on October 7, 2024, dstack now supports python: 3.13 in run configurations. python: 3.8 is still supported but deprecated.

Note: the dstack package itself does not yet work on Python 3.13 due to some limitations in dependencies. We're looking into supporting it as well.

Custom backend tags

You can now define custom tags that dstack will assign to all cloud resources it creates including instances and volumes. The tags are defined in the backend configuration:

type: aws tags: company_department: finance company_project: dstack company_user: victor creds: type: default

Custom tags are supported for AWS, Azure, and GCP.

Improved support of AWS private subnets

Previously, when configuring an AWS backend to use private subnets (public_ips: false), dstack would require a NAT Gateway. Now dstack supports more networking setups that provide outbound internet traffic including NAT Gateway, Transit Gateway, and VPC Peering Connection.

New required permissions

dstack now sets labels on GCP volumes which requires a compute.disks.setLabels permission.

Deprecations

python: 3.8 in run configurations is deprecated.

What's Changed

Add created_at to projects and users by @r4victor in https://github.com/dstackai/dstack/pull/1857
Improvements for model details page in the UI by @olgenn in https://github.com/dstackai/dstack/pull/1860
[Bug]: Users logged out after rotating their tokens without seeing tokens by @olgenn in https://github.com/dstackai/dstack/pull/1861
[dind] Move dind processes to a separate cgroup by @un-def in https://github.com/dstackai/dstack/pull/1859
[Docs] Add Docker protip and Docker Compose example by @un-def in https://github.com/dstackai/dstack/pull/1858
Implement custom backend tags by @r4victor in https://github.com/dstackai/dstack/pull/1872
[shim] Remove anonymous volumes along associated container by @un-def in https://github.com/dstackai/dstack/pull/1873
Allow running services without a gateway by @jvstme in https://github.com/dstackai/dstack/pull/1869
[UX]: Resize chat input field based on content #1562 by @olgenn in https://github.com/dstackai/dstack/pull/1875
Collect AMD GPU metrics by @r4victor in https://github.com/dstackai/dstack/pull/1877
[Blog] Monitoring GPU usage and other container metrics by @peterschmidt85 in https://github.com/dstackai/dstack/pull/1874
[Docs] Rename HUGGING_FACE_HUB_TOKEN to HF_TOKEN by @peterschmidt85 in https://github.com/dstackai/dstack/pull/1871
Support Python 3.13 and deprecate 3.8 in run configurations by @jvstme in https://github.com/dstackai/dstack/pull/1878
Support AWS private subnets with Transit Gateway by @r4victor in https://github.com/dstackai/dstack/pull/1881
Fix collecting metrics from CPU instances by @r4victor in https://github.com/dstackai/dstack/pull/1882

Full Changelog: https://github.com/dstackai/dstack/compare/0.18.19...0.18.20

Additional details

Usage instructions

Here's the most simple way to run the container image:

aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 709825985650.dkr.ecr.us-east-1.amazonaws.com

Pull the container image:

docker pull 709825985650.dkr.ecr.us-east-1.amazonaws.com/dstack/dstack-enterprise-v1:0.18.20-v1

Run the Container Image

docker run -it -p 3000:3000 -v $HOME/.dstack-enterprise/server/:/root/.dstack/server 709825985650.dkr.ecr.us-east-1.amazonaws.com/dstack/dstack-enterprise-v1:0.18.20-v1

Click the URL in the container output (e.g., http://localhost:3000 ).
Copy the admin token from the container output to log in to the UI

For more advanced deployment configurations, check https://dstack.ai/docs/guides/server-deployment/

dstack Enterprise is fully compatible with the open-source CLI of dstack. More details can be found at dstack documentation: https://dstack.ai/docs/ .

Resources

Vendor resources

Website

Support

Vendor support

hello@dstack.ai

AWS infrastructure support

AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

Get support

Product comparison

Info

Updated weekly

dstack Enterprise

By dstack

Modal

By Modal

Rancher on Ubuntu Server 22.04 LTS with support by AskforCloud LLC

By Askforcloud LLC

Accolades

Info

Top

In AIOps, Container Workloads, Generative AI

Top

In Serverless Workloads

Overview

Info

AI generated from product descriptions

Container Orchestration

Simplified container management for AI workloads across cloud and on-premises environments

Hardware Support

Native integration with NVIDIA GPU, AMD GPU, and Google Cloud TPU technologies

Multi-Cloud Compatibility

Supports deployment and management across multiple cloud providers and on-prem servers

AI Workflow Optimization

Streamlines development, training, and deployment processes for AI models

Infrastructure Abstraction

Provides alternative orchestration layer to Kubernetes and Slurm with specialized AI infrastructure management

Serverless Compute

Provides serverless compute infrastructure specifically designed for AI, ML, and data processing workloads

GPU Container Deployment

Enables rapid GPU-enabled container deployment with startup times as low as one second

Infrastructure as Code

Supports deploying Python functions to cloud environments with custom container image and hardware specification definitions

Dynamic Resource Scaling

Automatically scales computational resources up to hundreds of GPUs and down to zero based on workload requirements

Cloud Workload Optimization

Supports complex computational tasks including ML inference, fine-tuning, and batch data processing

Kubernetes Management

Open source tool for deploying and managing Kubernetes clusters across multiple providers and environments

Authentication Control

Centralized role-based access control (RBAC) for managing cluster access from a single location

Cluster Monitoring

Detailed monitoring and alerting capabilities for Kubernetes clusters and their associated resources

Log Management

Capability to ship logs to external providers for comprehensive cluster observability

Application Deployment

Direct integration with Helm via Application Catalog for streamlined application management and deployment

Contract

Info

Standard contract

Customer reviews

Leave a review

Ratings and reviews

Info

0 ratings

5 star

4 star

3 star

2 star

1 star

0 AWS reviews

No customer reviews yet

Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.