---
title: August 2023
description: Read about DataRobot's new public preview and generally available features released in August, 2023.

---

# August 2023 {: #august-2023 }

_August 22, 2023_

With the August 2023 deployment, DataRobot's AI Platform delivered the new GA and Public Preview features listed below. From the release center you can also access:

* [Monthly deployment announcement history](cloud-history/index)
* [Public preview features](public-preview/index)
* [Self-Managed AI Platform release notes](archive-release-notes/index)

### August release {: #august-release }

The following table lists each new feature:

??? abstract "Features grouped by capability"

    Name       |  GA | Public Preview
    ---------- | ---- | ---
	**Modeling** |  :~~:  | :~~:
		[Blueprint repository in Workbench now GA](#blueprint-repository-in-workbench-now-ga) | ✔  |
		[Blueprint JSON endpoints allow mapping to open source](#blueprint-json-endpoints-allow-mapping-to-open-source)  | ✔  |
		[More granular model logging info now available in DataRobot Classic](#more-granular-model-logging-info-now-available-in-datarobot-classic)  | ✔  |


## Modeling enhancements {: #modeling-enhancements }

### GA {: #ga }


#### Blueprint repository in Workbench now GA {: #blueprint-repository-in-workbench-now-ga }

With this deployment, the [blueprint repository](ml-experiment-add#blueprint-repository)&mdash;a library of modeling blueprints&mdash;is now generally available in Workbench for prediction and time-aware projects. After running Quick Autopilot, you can visit the repository to select and run blueprints that DataRobot did not run by default. They will be added to the Leaderboard and your experiment.

Additionally, the [Blueprint visualization](ml-experiment-evaluate#blueprint) is GA in Workbench, providing a graphical representation of the preprocessing steps (tasks), modeling algorithms, and post-processing steps that go into building a model.

![](images/wb-exp-eval-21.png)

#### Blueprint JSON endpoints allow mapping to open source {: #blueprint-json-endpoints-allow-mapping-to-open-source }


With this deployment, model blueprint JSON representation can be retrieved through both the UI and through API and client packages for improved transparency. Now you can access the JSON for DataRobot tasks and map the components to open-source code, creating an open-source equivalent to the DataRobot blueprint. For code-first users, the information can be quickly retrieved programmatically and incorporated into notebooks. Or, it can be copied from the **Describe > Blueprint** JSON tab in the UI. The code then be edited to suit your pipeline needs.  

![](images/blueprint-json.png)

#### More granular model logging info now available in DataRobot Classic {: #more-granular-model-logging-info-now-available-in-datarobot-classic }

With this deployment, additional detail has been added to the [**Model Info**](model-info) and [**Log**](log) tabs, both available under **Describe** in DataRobot Classic. The **Log** tab, which displays the status of successful and errored operations, now displays start and end times for each task within a larger job. **Model Info** has added *Max RAM* and *Cache Time Savings*&mdash;a measure of how much time was saved due to reusing blueprint vertices.

![](images/rn-model-info-enhance.png)


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