Azure, better UI and more¶
The 0.9.1 update introduces Azure support among other improvements.
dstack, our goal is to create a simple and unified interface for ML engineers to run dev environments, pipelines, and
apps on any cloud. With the latest update, we take another significant step in this direction.
We are thrilled to announce that the latest update introduces Azure support, among other things, making it incredibly easy to run dev environments, pipelines, and apps in Azure. Read on for more details.
Using Azure with
dstack is very straightforward. All you need to do is create the corresponding project via the UI and
provide your Azure credentials.
For detailed instructions on setting up
dstack for Azure, refer to the documentation.
Once the project is set up, you can define dev environments, pipelines, and apps as code, and easily run them with just
a single command.
dstack will automatically provision the infrastructure for you.
Logs and artifacts in UI¶
Secondly, with the new update, you now have the ability to browse the logs and artifacts of any run through the user interface.
Try it out¶
Please note that when installing
pip, you now need to specify the exact list of cloud providers you intend to use:
$ pip install "dstack[aws,gcp,azure]" -U
This requirement applies only when you start the server locally. If you connect to a server hosted elsewhere,
you can use the shorter syntax:
pip install dstack.