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Releases: dstackai/dstack

0.19.32

09 Oct 11:23
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Fleets

Nodes

Maximum number of nodes

The fleet nodes.max property is now respected that allows limiting maximum number of instances allowed in a fleet. For example, to allow at most 10 instances in the fleet, you can do:

type: fleet
name: cloud-fleet
nodes: 0..10

A fleet will be considered for a run only if the run can fit into the fleet without violating nodes.max. If you don't need to enforce an upper limit, you can omit it:

type: fleet
name: cloud-fleet
nodes: 0..

Backends

Nebius

Tags

Nebius backend now supports backend and resource-level tags to tag cloud resources provisioned via dstack:

type: nebius
creds:
  type: service_account
  # ...
tags:
  team: my_team
  user: jake

Credentials file

It's also possible to configure the nebius backend using a credentials file generated by the nebius CLI:

nebius iam auth-public-key generate \
    --service-account-id <service account ID> \
    --output ~/.nebius/sa-credentials.json
projects:
- name: main
  backends:
  - type: nebius
    creds:
      type: service_account
      filename: ~/.nebius/sa-credentials.json

Hot Aisle

Hot Aisle backend now supports multi-GPU VMs such as 2xMI300X and 4xMI300X.

dstack apply -f .local/.dstack.yml --gpu amd:2
The working_dir is not set — using legacy default "/workflow". Future versions will default to the
image's working directory.

 #  BACKEND               RESOURCES                                 INSTANCE TYPE        PRICE
 1  hotaisle              cpu=26 mem=448GB disk=12288GB             2x MI300X 26x Xeon…  $3.98
    (us-michigan-1)       MI300X:192GB:2

What's changed

New contributors

Full changelog: 0.19.31...0.19.32

0.19.31

02 Oct 12:47
6201c2f
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Kubernetes

The kubernetes backend introduces many significant improvements and has now graduated from alpha to beta. It is much more stable and can be reliably used on GPU clusters for all kinds of workloads, including distributed tasks.

Here's what changed:

  • Resource allocation now fully respects the user’s resources specification. Previously, it ignored certain aspects, especially the proper selection of GPU labels according to the specified gpu spec.
  • Distributed tasks now fully work on Kubernetes clusters with fast interconnect enabled. Previously, this caused many issues.
  • Added support privileged.

We’ve also published a dedicated guide on how to get started with dstack on Kubernetes, highlighting important nuances.

Warning

Be aware of breaking changes if you used the kubernetes backend before. The following properties in the Kubernetes backend configuration have been renamed:

  • networkingproxy_jump
  • ssh_hosthostname
  • ssh_portport

Additionally, the "proxy jump" pod and service names now include a dstack- prefix.

GCP

A4 spot instances with B200 GPUs

The gcp backend now supports A4 spot instances equipped with B200 GPUs. This includes provisioning both standalone A4 instances and A4 clusters with high-performance RoCE networking.

To use A4 clusters with high-performance networking, you must configure multiple VPCs in your backend settings (~/.dstack/server/config.yml):

projects:
- name: main
  backends:
  - type: gcp
    project_id: my-project
    creds:
      type: default
    vpc_name: my-vpc-0   # regular, 1 subnet
    extra_vpcs:
    - my-vpc-1   # regular, 1 subnet
    roce_vpcs:
    - my-vpc-mrdma   # RoCE profile, 8 subnets

Then, provision a cluster using a fleet configuration:

type: fleet

nodes: 2
placement: cluster

availability_zones: [us-west2-c]
backends: [gcp]

spot_policy: spot

resources:
  gpu: B200:8

Each instance in the cluster will have 10 network interfaces: 1 regular interface in the main VPC, 1 regular interface in the extra VPC, and 8 RDMA interfaces in the RoCE VPC.

Note

Currently, the gcp backend only supports A4 spot instances. Support for other options, such as flex and calendar scheduling via Dynamic Workload Scheduler, is coming soon.

CLI

dstack project is now faster

The USER column in dstack project list is now shown only when the --verbose flag is used.
This significantly improves performance for users with many configured projects, reducing execution time from ~20 seconds to as little as 2 seconds in some cases.

What's changed

  • [Kubernetes] Request resources according to RequirementsSpec by @un-def in #3127
  • [GCP] Support A4 spot instances with the B200 GPU by @jvstme in #3100
  • [CLI] Move USER to dstack project list --verbose by @jvstme in #3134
  • [Kubernetes] Configure /dev/shm if requested by @un-def in #3135
  • [Backward incompatible] Rename properties in Kubernetes backend config by @un-def in #3137
  • Support GCP A4 clusters by @jvstme in #3142
  • Kubernetes: add multi-node support by @un-def in #3141
  • Fix duplicate server log messages by @jvstme in #3143
  • [Docs] Improve Kubernetes documentation by @peterschmidt85 in #3138

Full changelog: 0.19.30...0.19.31

0.19.30

25 Sep 15:10
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Major changes

  • [Feature] Update CUDA driver in dstack's default aws, gcp, azure, and oci OS images from 535 to 570 by @jvstme in #3099

Major bug-fixes

  • [Bug] dstack CLI logging is broken #3118 by @peterschmidt85 in #3119
  • [AWS]: dstack doesn't use the EFA-enabled Docker image for H100:1 on AWS (p5.4xlarge) by @r4victor in #3111
  • [Bug] dstack misconfigures Git credentials for private repos by @un-def in #3116

Other changes

Full changelog: 0.19.29...0.19.30

0.19.29

16 Sep 10:51
40903db
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Fleets

Over the last few releases, we’ve been reworking how fleets work to radically simplify management and make it fully declarative.

Previously, you had to specify a fleet via fleets explicitly — otherwise, dstack always created a new one. Now, dstack automatically picks an existing fleet if it fits the requirements, creating a new one only when needed.

For more on the fleet roadmap, see this meta issue.

User Interface

Grouping offers by backend

The Offers page in the UI now lets you group available offers by backend, making it easier to compare options across cloud providers.

Breaking changes

  • The tensordock backend hasn’t worked for a long time (due to the API it relied on being deprecated) and has now been removed.

What's changed

Full changelog: 0.19.28...0.19.29

0.19.28

10 Sep 10:35
b8f2ade
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CLI

Argument Handling

The CLI now properly handles unrecognized arguments and rejects them with clear error messages. The ${{ run.args }} interpolation for tasks and services is still supported but now requires the -- pseudo-argument separator:

dstack apply --reuse -- --some=arg --some-option

This change prevents accidental typos in command arguments from being silently ignored.

What's Changed

Full Changelog: 0.19.27...0.19.28

0.19.27

04 Sep 12:33
670859e
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Run configurations

Repo directory

It's now possible to specify the directory in the container where the repo is mounted:

type: dev-environment

ide: vscode

repos:
  - local_path: .
    path: my_repo

  # or using short syntax:
  # - .:my_repo

The path property can be an absolute path or a relative path (with respect to working_dir). It's available inside run as the $DSTACK_REPO_DIR environment variable. If path is not set, the /workflow path is used.

Working directory

Previously, the working_dir property had complicated semantics: it defaulted to the repo path (/workflow), but for tasks and services without commands, the image working directory was used. You could also specify custom working_dir relative to the repo directory. This is now reversed: you specify working_dir as absolute path, and the repo path can be specified relative to it.

Note

During transitioning period, the legacy behavior of using /workflow is preserved if working_dir is not set. In future releases, this will be simplified, and working_dir will always default to the image working directory.

Fleet configuration

Nodes, retry, and target

dstack now indefinitely maintains nodes.min specified for cloud fleets. If instances get terminated for any reason and there are fewer instances than nodes.min, dstack will provision new fleet instances in the background.

There is also a new nodes.target property that specifies the number of instances to provision on fleet apply. Since now nodes.min is always maintained, you may specify nodes.target different from nodes.min to provision more instances than needs to be maintained.

Example:

type: fleet
name: default-fleet
nodes:
  min: 1 # Maintain one instance
  target: 2 # Provision two instances initially
  max: 3

dstack will provision two instances. After deleting one instance, there will be one instances left. Deleting the last instance will trigger dstack to re-create the instance.

Offers

The UI now has a dedicated page showing GPU offers available across all configured backends.

Digital Ocean and AMD Developer Cloud

The release adds native integration with DigitalOcean and
AMD Developer Cloud.

A backend configuration example:

projects:
- name: main
  backends:
  - type: amddevcloud
    project_name: TestProject
    creds:
        type: api_key
        api_key: ...

For DigitalOcean, set type to digitalocean.

The digitalocean and amddevcloud backends support NVIDIA and AMD GPU VMs, respectively, and allow you to run
dev environments (interactive development), tasks
(training, fine-tuning, or other batch jobs), and services (inference).

Security

Important

This update fixes a vulnerability in the cloudrift, cudo, and datacrunch backends. Instances created with earlier dstack versions lack proper firewall rules, potentially exposing internal APIs and allowing unauthorized access.

Users of these backends are advised to update to the latest version and re-create any running instances.

What's changed

Full changelog: 0.19.26...0.19.27

0.19.26

28 Aug 11:00
2c47e64
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Repos

Previously, dstack always required running the dstack init command before use. This also meant that dstack would always mount the current folder as a repo.

With this update, repo configuration is now explicit and declarative. If you want to use a repo in your run, you must specify it with the new repos property. The dstack init command is now only used to provide custom Git credentials when working with private repos.

For example, imagine you have a cloned Git repo with an examples subdirectory containing a .dstack.yml file:

type: dev-environment
name: vscode    

repos:
  # Mounts the parent directory of `examples` (must be a Git repo)
  #   to `/workflow` (the default working directory)
  - ..

ide: vscode

When you run this configuration, dstack fetches the repo on the instance, applies your local changes, and mounts it—so the container always matches your local repo.

Sometimes you may want to mount a Git repo without cloning it locally. In that case, simply provide a URL in repos:

type: dev-environment
name: vscode    

repos:
  # Clone the specified repo to `/workflow` (the default working directory)
  - https://github.com/dstackai/dstack

ide: vscode

If the repo is private, dstack will automatically try to use your default Git credentials (from ~/.ssh/config or ~/.config/gh/hosts.yml).

To configure custom Git credentials, use dstack init.

Note

If you previously initialized a repo via dstack init, it will still be mounted. Be sure to migrate to repos, as implicitly configured repos are deprecated and will stop working in future releases.

If you no longer want to use the implicitly configured repo, run dstack init --remove.

Note

Currently, you can configure only one repo per run configuration.

Fleets

Previously, when dstack added new instances to existing fleets, it ignored the fleet configuration and used only the run configuration for which the instance was created. This could result in fleets containing instances that didn’t match their configuration.

This has now been fixed: fleet configurations and run configurations are intersected so that provisioned instances respect both. For example, given a fleet configuration:

type: fleet
name: cloud-fleet
placement: any
nodes: 0..2
backends:
  - runpod

and a run configuration:

type: dev-environment
ide: vscode
spot_policy: spot
fleets:
  - cloud-fleet

dstack will provision a RunPod spot instance in cloud-fleet.

This change lets you define main provisioning parameters in fleet configurations, while adjusting them in run configurations as needed.

Note

Currently, the run plan does not take fleet configuration into account when showing offers, since the target fleet may not be known beforehand. We plan to improve this by showing offers for all candidate fleets.

Examples

Wan2.2

We've added a new example demonstrating how to use Wan2.2, the new open-source SOTA text-to-video model, to generate videos.

Internals

Pyright integration

We now use pyright for type checking dstack Python code in CI. If you contribute to dstack, we recommend you configure your IDE to use pyright/pylance with standard type checking mode.

What's changed

Full changelog: 0.19.25...0.19.26

0.19.25

20 Aug 16:02
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CLI

dstack offer --group-by

The dstack offer command can now display aggregated information about available offers. For example, to see what GPUs are available in different clouds, use --group-by gpu.

> dstack offer --group-by gpu

 #   GPU              SPOT             $/GPU           BACKENDS                             
 1   T4:16GB:1..8     spot, on-demand  0.1037..1.3797  gcp, aws                             
 2   L4:24GB:1..8     spot, on-demand  0.1829..2.1183  gcp, aws                             
 3   P100:16GB:1..4   spot, on-demand  0.2115..2.4043  gcp, oci                             
 4   V100:16GB:1..8   spot, on-demand  0.3152..4.234   gcp, aws, oci, lambda                
 5   A10G:22GB:1..8   spot, on-demand  0.3623..2.5845  aws                                  
 6   L40S:44GB:1..8   spot, on-demand  0.6392..4.7095  aws                                  
 7   A100:40GB:1..16  spot, on-demand  0.6441..4.0496  gcp, aws, oci, lambda                
 8   A10:24GB:1..4    on-demand        0.75..2         oci, lambda                          
 9   H100:80GB:1..8   spot, on-demand  1.079..15.7236  gcp, aws, lambda                     
 10  A100:80GB:1..8   spot, on-demand  1.2942..5.7077  gcp, aws, lambda

Refer to the docs for information about the available aggregations.

Deprecations

  • Local repos are now deprecated. If you need to deliver a local directory or file to a run, use files instead. If the run doesn't require a repo, use dstack apply --no-repo. Remote repos remain the recommended way to deliver Git repos to runs.

What's changed

New Contributors

Full Changelog: 0.19.24...0.19.25

0.19.24

14 Aug 11:37
5fb7af3
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Migration guide

Warning

This update requires stopping all dstack server replicas before deploying, due to database schema changes.
Make sure no replicas from the previous version and the new version run at the same time.

What's changed

  • [Internal] Replace enums with strings in the DB, JobSubmission.termination_reason, and Run.termination_reason by @r4victor in #2949
  • [Internal] Fix macOS build for shim by @un-def in #2958
  • [Bug] Increase the secrets max character length by @james-boydell in #2971
  • [Internal] Introduce InstanceAvailability.NO_BALANCE (for external integrations) by @peterschmidt85 in #2975
  • [Bug]: Cannot manage secrets in UI as project admin by @olgenn in #2972
  • [Bug] Fix DCGMWrapperInterface nil check in shim by @un-def in #2980

Full changelog: 0.19.23...0.19.24

0.19.23

08 Aug 15:43
5c8450f
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Major bug-fixes

  • This release resolves an issue introduced in 0.19.22 that caused instance provisioning to fail consistently for certain instance types.

Backends

Nebius

The nebius backend now supports spot instances and the NVIDIA B200 GPU.

> dstack offer -b nebius --spot                     

 #  BACKEND               RESOURCES                                          PRICE   
 1  nebius (eu-north1)    cpu=16 mem=200GB disk=100GB H100:80GB:1 (spot)     $1.25   
 2  nebius (eu-north1)    cpu=16 mem=200GB disk=100GB H200:141GB:1 (spot)    $1.45   
 3  nebius (eu-west1)     cpu=16 mem=200GB disk=100GB H200:141GB:1 (spot)    $1.45   
 4  nebius (us-central1)  cpu=16 mem=200GB disk=100GB H200:141GB:1 (spot)    $1.45   
 5  nebius (eu-north1)    cpu=128 mem=1600GB disk=100GB H100:80GB:8 (spot)   $10     
 6  nebius (eu-north1)    cpu=128 mem=1600GB disk=100GB H200:141GB:8 (spot)  $11.6   
 7  nebius (eu-west1)     cpu=128 mem=1600GB disk=100GB H200:141GB:8 (spot)  $11.6   
 8  nebius (us-central1)  cpu=128 mem=1600GB disk=100GB H200:141GB:8 (spot)  $11.6   

> dstack offer -b nebius --gpu 8:b200

 #  BACKEND               RESOURCES                                   PRICE   
 1  nebius (us-central1)  cpu=160 mem=1792GB disk=100GB B200:180GB:8  $44

What's changed

Full Changelog: 0.19.22...0.19.23