Zenml

ZenML now uses Pydantic v2. 🥳

This upgrade comes with a set of critical updates. While your user experience mostly remains unaffected, you might see unexpected behavior due to the changes in our dependencies. Moreover, since Pydantic v2 provides a slightly stricter validation process, you might end up bumping into some validation errors which was not caught before, but it is all for the better 🙂 If you run into any other errors, please let us know either on [GitHub](https://github.com/zenml-io/zenml) or on our [Slack](https://zenml.io/slack-invite).

Changes in some of the critical dependencies

- SQLModel is one of the core dependencies of ZenML and prior to this upgrade, we were utilizing version `0.0.8`. However, this version is relatively outdated and incompatible with Pydantic v2. Within the scope of this upgrade, we upgraded it to `0.0.18`.
- Due to the change in the SQLModel version, we also had to upgrade our SQLAlchemy dependency from V1 to v2. While this does not affect the way that you are using ZenML, if you are using SQLAlchemy in your environment, you might have to migrate your code as well. For a detailed list of changes, feel free to check [their migration guide](https://docs.sqlalchemy.org/en/20/changelog/migration_20.html).

Changes in `pydantic`
Pydantic v2 brings a lot of new and exciting changes to the table. The core logic now uses Rust, and it is much faster and more efficient in terms of performance. On top of it, the main concepts like model design, configuration, validation, or serialization now include a lot of new cool features. If you are using `pydantic` in your workflow and are interested in the new changes, you can check [the brilliant migration guide](https://docs.pydantic.dev/2.7/migration/) provided by the `pydantic` team to see the full list of changes.

Changes in our integrations changes
Much like ZenML, `pydantic` is an important dependency in many other Python packages. That’s why conducting this upgrade helped us unlock a new version for several ZenML integration dependencies. Additionally, in some instances, we had to adapt the functionality of the integration to keep it compatible with `pydantic`. So, if you are using any of these integrations, please go through the changes.

Airflow
As mentioned above upgrading our `pydantic` dependency meant we had to upgrade our `sqlmodel` dependency. Upgrading our `sqlmodel` dependency meant we had to upgrade our `sqlalchemy` dependency as well. Unfortunately, `apache-airflow` is still using `sqlalchemy` v1 and is incompatible with pydantic v2. As a solution, we have removed the dependencies of the `airflow` integration. Now, you can use ZenML to create your Airflow pipelines and use a separate environment to run them with Airflow. You can check the updated docs [right here](https://docs.zenml.io/stack-components/orchestrators/airflow).

AWS
Some of our integrations now require `protobuf` 4. Since our previous `sagemaker` version (`2.117.0`) did not support `protobof` 4, we could not pair it with these new integrations. Thankfully `sagemaker` started supporting `protobuf` 4 with version `2.172.0` and relaxing its dependency solved the compatibility issue.

Evidently
The old version of our `evidently` integration was not compatible with Pydantic v2. They started supporting it starting from version `0.4.16`. As their latest version is `0.4.22`, the new dependency of the integration is limited between these two versions.

Feast
Our previous implementation of the `feast` integration was not compatible with Pydantic v2 due to the extra `redis` dependency we were using. This extra dependency is now removed and the `feast` integration is working as intended.

GCP
The previous version of the Kubeflow dependency (`kfp==1.8.22`) in our GCP integration required Pydantic V1 to be installed. While we were upgrading our Pydantic dependency, we saw this as an opportunity and wanted to use this chance to upgrade the `kfp` dependency to v2 (which has no dependencies on the Pydantic library). This is why you may see some functional changes in the vertex step operator and orchestrator. If you would like to go through the changes in the `kfp` library, you can
find [the migration guide here](https://www.kubeflow.org/docs/components/pipelines/v2/migration/).

Great Expectations
Great Expectations started supporting Pydantic v2 starting from version `0.17.15` and they are closing in on their `1.0` release. Since this release might include a lot of big changes, we adjusted the dependency in our integration to `great-expectations>=0.17.15,<1.0`. We will try to keep it updated in the future once they release the `1.0` version

Kubeflow

Similar to the GCP integration, the previous version of the kubeflow dependency (`kfp==1.8.22`) in our `kubeflow` integration required Pydantic V1 to be installed. While we were upgrading our Pydantic dependency, we saw this as an opportunity and wanted to use this chance to upgrade the `kfp` dependency to v2 (which has no dependencies on the Pydantic library). If you would like to go through the changes in the `kfp` library, you can find [the migration guide here](https://www.kubeflow.org/docs/components/pipelines/v2/migration/). ( We also are considering adding an alternative version of this integration so our users can keep using `kfp` V1 in their environment. Stay tuned for any updates.)

MLflow

`mlflow` is compatible with both Pydantic V1 and v2. However, due to a known issue, if you install `zenml` first and then do `zenml integration install mlflow -y`, it downgrades `pydantic` to V1. This is why we manually added the same duplicated `pydantic` requirement in the integration definition as well. Keep in mind that the `mlflow` library is still using some features of `pydantic` V1 which are deprecated. So, if the integration is installed in your environment, you might run into some deprecation warnings.

Label Studio

While we were working on updating our `pydantic` dependency, the `label-studio-sdk` has released its 1.0 version. In this new version, `pydantic` v2 is also supported. The implementation and documentation of our Label Studio integration have been updated accordingly.

Skypilot

With the switch to `pydantic` v2, the implementation of our `skypilot` integration mostly remained untouched. However, due to an incompatibility between the new version `pydantic` and the `azurecli`, the `skypilot[azure]` flavor can not be installed at the same time, thus our `skypilot_azure` integration is currently deactivated. We are working on fixing this issue and if you are using this integration in your workflows, we recommend staying on the previous version of ZenML until we can solve this issue.

Tensorflow

The new version of `pydantic` creates a drift between `tensorflow` and `typing_extensions` packages and relaxing the dependencies here resolves the issue. At the same time, the upgrade to `kfp` v2 (in integrations like `kubeflow`, `tekton`, or `gcp`) bumps our `protobuf` dependency from `3.X` to `4.X`. To stay compatible with this requirement, the installed version of `tensorflow` needs to be `>=2.12.0`. While this change solves the dependency issues in most settings, we have bumped into some errors while using `tensorflow` 2.12.0 on Python 3.8 on Ubuntu. If you would like to use this integration, please consider using a higher Python version.

Tekton
Similar to the `gcp` and `kubeflow` integrations, the old version of our `tekton` integration was not compatible with `pydantic` V1 due to its `kfp` dependency. With the switch from `kfp` V1 to v2, we have adapted our implementation to use the new version of `kfp` library and updated our documentation accordingly.

Additional Changes

* We have also released a new version of `mlstacks` with Pydantic v2 support. If you are using it in your development environment, you have to upgrade your `mlstacks` package as well.
* Added `zenml.integrations.huggingface.steps.run_with_accelerate` to enable running any step using [`accelerate`](https://huggingface.co/docs/accelerate/en/index). This function is supported by a utility that wraps any step function into a CLI script (which is required by most distributed training tools).
* Fixed a memory leak that was observed while using the ZenML dashboard to view pipeline logs or artifact visualizations logged through an S3 Artifact Store linked to an AWS Service Connector.
* Previously, we had an option called `build_options` that allowed users to pass arguments to the docker build command. However, these options were only applied when building the parent image. On macOS with ARM architecture, one needs to specify `platform=linux/amd64` to the build command to leverage local caching of Docker image layers. We have added a way to specify these build options for the "main" ZenML build as well, not just the parent image build. Additionally, users can now specify a `.dockerignore` file for the parent image build, which was previously not possible.

What's Changed

* Extend migration testing by avishniakov in https://github.com/zenml-io/zenml/pull/2768
* Add retry docs by htahir1 in https://github.com/zenml-io/zenml/pull/2770
* Fix nightly Docker build by strickvl in https://github.com/zenml-io/zenml/pull/2769
* Start CTA and Cloud -> Pro renaming by AlexejPenner in https://github.com/zenml-io/zenml/pull/2773
* Add star CTA to `README` by AlexejPenner in https://github.com/zenml-io/zenml/pull/2777
* Use build python version if available by schustmi in https://github.com/zenml-io/zenml/pull/2775
* Introduced Legacy env var in docs by AlexejPenner in https://github.com/zenml-io/zenml/pull/2783
* Fixing the nlp template for the upcoming pydantic upgrade by bcdurak in https://github.com/zenml-io/zenml/pull/2778
* Full renaming away from cloud to pro by AlexejPenner in https://github.com/zenml-io/zenml/pull/2782
* Adjust docs url for flavors by AlexejPenner in https://github.com/zenml-io/zenml/pull/2772
* Fixed broken unit test on develop and fixed duplicate / by AlexejPenner in https://github.com/zenml-io/zenml/pull/2785
* Added timeout by AlexejPenner in https://github.com/zenml-io/zenml/pull/2786
* Bump NLP template by avishniakov in https://github.com/zenml-io/zenml/pull/2787
* Raise error if Dockerfile does not exist by schustmi in https://github.com/zenml-io/zenml/pull/2776
* Pin `numpy<2.0.0` by avishniakov in https://github.com/zenml-io/zenml/pull/2789
* Fix partial logs loss in step operators with immutable FS in the backend by avishniakov in https://github.com/zenml-io/zenml/pull/2788
* Upgrading to `pydantic` v2 by bcdurak in https://github.com/zenml-io/zenml/pull/2543
* New CI/CD docs by AlexejPenner in https://github.com/zenml-io/zenml/pull/2784
* Improvements for running pipelines from the dashboard by schustmi in https://github.com/zenml-io/zenml/pull/2781
* Accelerate runner helper method by avishniakov in https://github.com/zenml-io/zenml/pull/2746
* Add `--ignore-errors` flag for `zenml artifact prune` by strickvl in https://github.com/zenml-io/zenml/pull/2780
* Enable running a pipeline through the client by schustmi in https://github.com/zenml-io/zenml/pull/2736
* Accelerated template LLMs by avishniakov in https://github.com/zenml-io/zenml/pull/2797
* Separate actions from triggers by schustmi in https://github.com/zenml-io/zenml/pull/2700
* Fix hook type definition and improve code completion for pipeline decorator by schustmi in https://github.com/zenml-io/zenml/pull/2793
* Allow specifying build options for main image build by schustmi in https://github.com/zenml-io/zenml/pull/2749
* Small improvements for yaml config files by schustmi in https://github.com/zenml-io/zenml/pull/2796
* Docs for the `pydantic` migration guide by bcdurak in https://github.com/zenml-io/zenml/pull/2801
* Bump mlflow to v2.14.1 by christianversloot in https://github.com/zenml-io/zenml/pull/2779
* Bugfix fixing the installation script to use the right mlstacks branch by bcdurak in https://github.com/zenml-io/zenml/pull/2803
* Fix S3 artifact store memory leak and other improvements by stefannica in https://github.com/zenml-io/zenml/pull/2802

🥳 Community Contributions 🥳

We'd like to give a special thanks to christianversloot who contributed to this release by bumping the `mlflow` version to 2.14.1

**Full Changelog**: https://github.com/zenml-io/zenml/compare/0.58.2...0.60.0

The 0.58.2 minor release is packed with a set of improvements to the ZenML logging and ZenML Server.

With this release ZenML logging will:
- Offer pagination of the logs during fetching via REST API
- Store the full logs history on GCS Artifact Stores
- Be performant running logging-heavy tasks, like TQDM logging or logging of training in any Deep Learning framework (also TQDM-backed)

What's Changed
* update test-migrations.sh with latest versions by safoinme in https://github.com/zenml-io/zenml/pull/2757
* Fix overriding expiration date for api tokens by schustmi in https://github.com/zenml-io/zenml/pull/2753
* Step logs pagination by schustmi in https://github.com/zenml-io/zenml/pull/2731
* Fix broken links (round 2) by strickvl in https://github.com/zenml-io/zenml/pull/2760
* Remove default system flag in docker UV by avishniakov in https://github.com/zenml-io/zenml/pull/2764
* Another batch of small fixes and expansions by AlexejPenner in https://github.com/zenml-io/zenml/pull/2762
* Server scalability improvements by stefannica in https://github.com/zenml-io/zenml/pull/2752
* Add option to start parallel kubernetes steps with delay by schustmi in https://github.com/zenml-io/zenml/pull/2758
* Move `thread_limiter` to app startup event by avishniakov in https://github.com/zenml-io/zenml/pull/2765
* Logging performance improvements and GCP logging fix by avishniakov in https://github.com/zenml-io/zenml/pull/2755


**Full Changelog**: https://github.com/zenml-io/zenml/compare/0.58.1...0.58.2

The 0.58.1 release brings a set of minor enhancements and bugfix to the ZenML framework, such as the ability to delete all pipeline versions using the Client/CLI, providing greater flexibility and control over pipeline management. Users can now specify Python package installer arguments. Furthermore, a fix has been implemented for the Sentencepiece tokenizer materializer.

We are also excited to introduce breadcrumbs to our dashboard to improve your navigation experience. This new feature allows you to easily visualize the path of your Pipelines, Models, and Artifacts, providing clear orientation, quick return to any section with a single click, and effortless navigation.

We’d like to give a special thanks to eltociear for their first contribution.

Docs re-work

We reworked the structure of our documentation pages to make it easier to find answers to your practical questions. Please do let us know if you have any feedback on the structure or the new style of the 'How To' section!

What's Changed
* Add 0.58.0 to migration testing by avishniakov in https://github.com/zenml-io/zenml/pull/2730
* Print step names in color, again by avishniakov in https://github.com/zenml-io/zenml/pull/2728
* Workflow to create JIRA tickets when Github Issues are created by strickvl in https://github.com/zenml-io/zenml/pull/2724
* Allow specifying python package installer args by schustmi in https://github.com/zenml-io/zenml/pull/2727
* Send workflow dispatch event to Cloud Plugins repo on release by wjayesh in https://github.com/zenml-io/zenml/pull/2633
* Fix Nightly Release by safoinme in https://github.com/zenml-io/zenml/pull/2711
* Fix `zenml go` images visibility in notebook by strickvl in https://github.com/zenml-io/zenml/pull/2742
* Handle error when using `zenml info` with missing dependencies by strickvl in https://github.com/zenml-io/zenml/pull/2725
* Add Discord Alerter into TOC by strickvl in https://github.com/zenml-io/zenml/pull/2735
* Allow deleting all versions of a pipeline using the Client/CLI by schustmi in https://github.com/zenml-io/zenml/pull/2745
* Misc fixes by schustmi in https://github.com/zenml-io/zenml/pull/2732
* Move full SQLite DB migration test to slow CI by strickvl in https://github.com/zenml-io/zenml/pull/2743
* Add system flag as default for uv by schustmi in https://github.com/zenml-io/zenml/pull/2748
* Add how-to section & restructure/update documentation by AlexejPenner in https://github.com/zenml-io/zenml/pull/2705
* Fix typo in help text by eltociear in https://github.com/zenml-io/zenml/pull/2750
* Add support for function types in source utils by schustmi in https://github.com/zenml-io/zenml/pull/2738
* Fix Sentencepiece tokenizer materializer by safoinme in https://github.com/zenml-io/zenml/pull/2751

New Contributors
* eltociear made their first contribution in https://github.com/zenml-io/zenml/pull/2750

**Full Changelog**: https://github.com/zenml-io/zenml/compare/0.58.0...0.58.1

New Annotators
This release brings in three new integrations for our annotator stack component: [Prodigy](https://prodi.gy/), [Argilla](https://github.com/argilla-io/argilla) and [Pigeon](https://github.com/agermanidis/pigeon).
* Pigeon works within Jupyter notebooks and supports a limited feature set but is great for experimentation and demos.
* Argilla works both locally-deployed and when the annotation instance lives in the cloud (i.e. in the Hugging Face Spaces deployment which they recommend).
* Prodigy is a powerful closed-source annotation tool that allows for efficient data labeling. With this integration, users can now connect ZenML with Prodigy and leverage its annotation capabilities in their ML pipelines.

Retry configuration for steps
This release also includes new `retry` configuration for the steps. The following parameters can be set:

- _**max_retries**_: The maximum number of times the step should be retried in case of failure.
- _**delay**_: The initial delay in seconds before the first retry attempt.
- _**backoff**_: The factor by which the delay should be multiplied after each retry attempt.

To use this in your code:

python
from zenml.config.retry_config import StepRetryConfig

step(retry=StepRetryConfig(max_retries=3, delay=10, backoff=2))
def step_3() -> None:
Step implementation
raise Exception("This is a test exception")


or using a `config.yaml`:

yaml
steps:
my_step:
retry:
max_retries: 3
delay: 10
backoff: 2


In addition, this release includes a number of bug fixes and documentation updates, such as a new LLM finetuning template powered by PEFT and BitsAndBytes and instructions for the new annotators.


Breaking changes
* The interface for the base class of the annotator stack component has been updated to account for the fact that not all annotators will launch with a specific URL. So there is no longer an url argument passed in.

🥳 Community Contributions 🥳

We'd like to give a special thanks to christianversloot who contributed to this release by bumping the `mlflow` version to 2.12.2

What's Changed
* Add more failure logs for code repositories and build reuse by schustmi in https://github.com/zenml-io/zenml/pull/2697
* Prodigy annotator by strickvl in https://github.com/zenml-io/zenml/pull/2655
* Bump mlflow support to version 2.12.2 by christianversloot in https://github.com/zenml-io/zenml/pull/2693
* add 0.57.1 to migration test scripts by safoinme in https://github.com/zenml-io/zenml/pull/2702
* Pigeon annotator by strickvl in https://github.com/zenml-io/zenml/pull/2641
* Allow credentials expiry to be configured for service connectors by stefannica in https://github.com/zenml-io/zenml/pull/2704
* Argilla annotator by strickvl in https://github.com/zenml-io/zenml/pull/2687
* Add `MySQL` and `mariadb` migration tests to Slow CI by safoinme in https://github.com/zenml-io/zenml/pull/2686
* Misc small fixes by schustmi in https://github.com/zenml-io/zenml/pull/2712
* Allow resetting server and user metadata by schustmi in https://github.com/zenml-io/zenml/pull/2666
* Fix Docker failures in the CI by avishniakov in https://github.com/zenml-io/zenml/pull/2716
* Add note about helm dependencies by strickvl in https://github.com/zenml-io/zenml/pull/2709
* Add retry config for failing steps by safoinme in https://github.com/zenml-io/zenml/pull/2627
* Update pyparsing version by strickvl in https://github.com/zenml-io/zenml/pull/2710
* New ruff issue by avishniakov in https://github.com/zenml-io/zenml/pull/2718
* PEFT LLM Template by avishniakov in https://github.com/zenml-io/zenml/pull/2719
* Add `model_version_id` as part of the Model config by avishniakov in https://github.com/zenml-io/zenml/pull/2703
* Add more runners to fast CI by safoinme in https://github.com/zenml-io/zenml/pull/2706
* Fail faster on notebook installation and only clone / download the branch we need for `zenml go` by strickvl in https://github.com/zenml-io/zenml/pull/2721
* Make a clear separation between server and dashboard API in the server configuration by stefannica in https://github.com/zenml-io/zenml/pull/2722
* Update pymysql to fix CVE-2024-36039 by stefannica in https://github.com/zenml-io/zenml/pull/2714
* Allow specifying privileged mode for Kubernetes orchestrator containers by schustmi in https://github.com/zenml-io/zenml/pull/2717
* Don't use pod resources/affinity for kubernetes orchestrator pod by schustmi in https://github.com/zenml-io/zenml/pull/2707
* Extra test for artifact listing by avishniakov in https://github.com/zenml-io/zenml/pull/2715
* Pipeline run not tracked in cached artifact version by avishniakov in https://github.com/zenml-io/zenml/pull/2713


**Full Changelog**: https://github.com/zenml-io/zenml/compare/0.57.1...0.58.0

This a minor release that brings a variety of enhancements for
the new dashboard release, a new update to the LLMOps guide (covering the use of rerankers in RAG pipelines), and [an updated README](README.md). It also introduces some new improvements to the service connectors.

We'd like to give a special thanks to ruvilonix for their first contribution.

What's Changed
* Add new versions to migration testing by avishniakov in https://github.com/zenml-io/zenml/pull/2663
* Resource settings import fix by htahir1 in https://github.com/zenml-io/zenml/pull/2664
* Fix env variable for legacy dashboard by schustmi in https://github.com/zenml-io/zenml/pull/2668
* Fix broken links in code examples by strickvl in https://github.com/zenml-io/zenml/pull/2672
* Improve error message when trying to unpack a step artifact by schustmi in https://github.com/zenml-io/zenml/pull/2674
* Prevent special whitespaces in the names of entities by avishniakov in https://github.com/zenml-io/zenml/pull/2665
* Ensure extra flags aren't passed into `uv` integration install command by strickvl in https://github.com/zenml-io/zenml/pull/2670
* `enable_cache` option shouldn't be set to `False` for one of the steps by ruvilonix in https://github.com/zenml-io/zenml/pull/2574
* Add new dashboard links to create/deactivate CLI commands by avishniakov in https://github.com/zenml-io/zenml/pull/2678
* Add reranking section to LLMOps guide by strickvl in https://github.com/zenml-io/zenml/pull/2679
* Updated Readme by AlexejPenner in https://github.com/zenml-io/zenml/pull/2675
* Added Thumbnail by AlexejPenner in https://github.com/zenml-io/zenml/pull/2684
* [k8s orchestrator] Fix credentials refresh and don't use service connector for incluster auth by wjayesh in https://github.com/zenml-io/zenml/pull/2671
* Prepare Release 0.57.1 by safoinme in https://github.com/zenml-io/zenml/pull/2683
* Include email in event by schustmi in https://github.com/zenml-io/zenml/pull/2692
* Set newsletter flag from email opted in by schustmi in https://github.com/zenml-io/zenml/pull/2694
* Only report usage once pipeline run starts by schustmi in https://github.com/zenml-io/zenml/pull/2680
* Reduced thumbnail size by AlexejPenner in https://github.com/zenml-io/zenml/pull/2689
* Fix intermittent timeout issues with service connector sessions by stefannica in https://github.com/zenml-io/zenml/pull/2690
* Include unique constraints in the database backup by stefannica in https://github.com/zenml-io/zenml/pull/2695
* [k8s orch] Add option to specify separate service account for step pods by wjayesh in https://github.com/zenml-io/zenml/pull/2688
* Update GCP registry docs by safoinme in https://github.com/zenml-io/zenml/pull/2676
* Use service connector for boto session if possible by schustmi in https://github.com/zenml-io/zenml/pull/2682
* Send missing user enriched events by schustmi in https://github.com/zenml-io/zenml/pull/2696

New Contributors
* ruvilonix made their first contribution in https://github.com/zenml-io/zenml/pull/2574

**Full Changelog**: https://github.com/zenml-io/zenml/compare/0.57.0...0.57.1

We're excited to announce that we're open-sourcing our new and improved dashboard. This unifies the experience for OSS and cloud users, though OSS users will initially see some dashboard features unavailable in this launch release.

We're open-sourcing our dashboard for a few reasons:

- to ensure that the dashboard experience is consistent across all users, for both the open-source and cloud versions
- to make it easier for us to maintain and develop the dashboard, as we can share components between the two versions
- to allow OSS contributions (and self-hosting and modifications) to the new dashboard
- to open up possibilities for future features, particularly for our OSS users

New users of the ZenML in the dashboard will have a better experience thanks to a much-improved onboarding sequence:

<div align="center">
<img width="80%" src="https://github.com/zenml-io/zenml/assets/31008759/184ce6f0-b973-4d15-a5b3-d4ae11fb3630" alt="Dashboard 2"/>
</div>
The dashboard will guide you through connecting to your server, setting up a stack, connecting to service connectors as well as running a pipeline.

We’ve also improved the ‘Settings’ section of the dashboard and this is the new home for configuration of your repositories, secrets, and connectors, along with some other options.

<div align="center">
<img width="80%" src="https://github.com/zenml-io/zenml/assets/31008759/b488f894-d706-4f1c-b9d9-7bf3ebf8d65a" alt="Dashboard 3"/>
</div>

What It Means for You

If you're already a **cloud user**, not much will change for you. You're already using the new dashboard for pipelines, models and artifacts. Your experience won’t change and for the moment you’ll continue using the old dashboard for certain components (notably for stacks and components).

If you're an **open-source user**, the new dashboard is now available to you as part of our latest release (0.57.0). You'll notice a completely refreshed design and a new DAG visualizer.

<div align="center">
<img width="80%" src="https://github.com/zenml-io/zenml/assets/31008759/9a397bfe-a97b-43c3-be53-e0e27730b58d" alt="Dashboard 4"/>
</div>

Unfortunately, some dashboard features are not yet ready so you'll see instructions on how to access them via the CLI. We hope to have these features returned into the product soon. (If you have a strong opinion as to which you'd like to see first, please let us know!) Specifically, secrets, stacks, and service connectors are not yet implemented in the new dashboard.

How to use the legacy dashboard

The old dashboard is still available to you. To run with the legacy dashboard pass the `--legacy` flag when spinning it up:

bash
zenml up --legacy


Note that you can’t use both the new and old dashboard at the same time.

If you’re self-hosting ZenML instead of using ZenML Cloud, you can specify which dashboard you want to use by setting the `ZEN_SERVER_USE_LEGACY_DASHBOARD` environment variable pre-deployment. Specifying a boolean value for this variable will determine which dashboard gets served for your deployment. (There’s no dynamic switching between dashboards allowed, so if you wish to change which dashboard is used for a deployed server, you’ll need to redeploy the server after updating the environment variable.)

If you’re using [ZenML Cloud](https://cloud.zenml.io/), your experience won’t change with this release and your use of the dashboard remains the same.

What's Changed
* Add Comet to Experiment Trackers in TOC by strickvl in https://github.com/zenml-io/zenml/pull/2637
* Fix Comet docs formatting by strickvl in https://github.com/zenml-io/zenml/pull/2639
* ZenML Server activation and user on-boarding by stefannica in https://github.com/zenml-io/zenml/pull/2630
* Slimmer and more secure Docker container images by stefannica in https://github.com/zenml-io/zenml/pull/2617
* Add dashboard v2 source context by schustmi in https://github.com/zenml-io/zenml/pull/2642
* Support New Dashboard release by avishniakov in https://github.com/zenml-io/zenml/pull/2635
* Fix CI by strickvl in https://github.com/zenml-io/zenml/pull/2645
* Misc/prepare release 0.57.0rc1 by avishniakov in https://github.com/zenml-io/zenml/pull/2646
* Add rate limiting to user password reset operations by stefannica in https://github.com/zenml-io/zenml/pull/2643
* Set zenml server name to default if not customized by stefannica in https://github.com/zenml-io/zenml/pull/2647
* Docker release fix by avishniakov in https://github.com/zenml-io/zenml/pull/2649
* Fix dashboard urls by schustmi in https://github.com/zenml-io/zenml/pull/2648
* Enable analytics during db initialization if specified by schustmi in https://github.com/zenml-io/zenml/pull/2652
* Better checks for user account updates to avoid Mass Assignment attacks by stefannica in https://github.com/zenml-io/zenml/pull/2622
* Prepare 0.57.0-rc2 by avishniakov in https://github.com/zenml-io/zenml/pull/2651
* Fix frontend analytics calls by schustmi in https://github.com/zenml-io/zenml/pull/2653
* Label studio settings and optional port by htahir1 in https://github.com/zenml-io/zenml/pull/2628
* Introduce default value fro enable_analytics by AlexejPenner in https://github.com/zenml-io/zenml/pull/2654
* Fix helm chart notes syntax by wjayesh in https://github.com/zenml-io/zenml/pull/2656
* Add server env variable to fix activation by schustmi in https://github.com/zenml-io/zenml/pull/2657
* Respect analytic ENV in local servers by avishniakov in https://github.com/zenml-io/zenml/pull/2658
* Small fixes in helm docs by schustmi in https://github.com/zenml-io/zenml/pull/2659


**Full Changelog**: https://github.com/zenml-io/zenml/compare/0.56.4...0.57.0