2020

Here are the highlights of new and updated features for this release:

Saagie has revamped its user interface to streamline your user experience.

For more information, see User interface.

We are migrating our documentation to a new site: docs.saagio.io.
For Legacy or Version 1 documentation, see Saagie Legacy (Version 1).

Now that the Projects module is no longer in beta, the pattern for the platform URLs has changed and must be as follows: prefix-suffix[.subdomain].domain.com.

For more information, see Creating DNS entry.

You can now configure the persistent storage size (between 64MB and 128MB) when creating your apps.
Persistent storage stores an app’s data between instances.

You can now monitor various Saagie metrics with Prometheus. These metrics are exposed via Saagie's HTTP API, allowing Ops teams to centralize and visualize them through Prometheus' multiple graphing and dashboarding modes.

The following technology versions have been added to the official Saagie technology repository:

Here are the highlights of new and updated features for this release:

A breadcrumb trail is now displayed at the top of the page (1).

Breadcrumbs let you know where you are within a project and quickly go back, making navigation much easier.
In addition, new persistent buttons has been added allowing you to refresh the status of jobs or pipelines and display their settings (2).

You can now see at a glance information about technologies and their integrated versions when creating new projects.
Hover over the technology icon when selecting technologies at the creation of the project to get a quick description.

This feature ensures that you have all the information you need to select the right technologies for your project.

The Activity page allows you to get a quick overview of the latest job and pipeline instances executed in each of their projects over the last 12 hours.

This feature can be useful in a production-ready environment to quickly react to job and pipeline execution failures, in addition to email alerts for status changes.

You can now run Python jobs on a GPU node if you have enabled the GPU option.
When creating a job, select run on GPU to allow Saagie to automatically allocate GPU resources to your job.

This feature can be useful for jobs such as deep learning algorithms where using a GPU can significantly speed up processing times.

The following technology versions have been added to the official Saagie technology repository: