ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
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Published by stefannica 11 months ago
This patch release backports some important fixes that have been introduced in more recent versions
of ZenML to the 0.44.x release line.
Full Changelog: https://github.com/zenml-io/zenml/compare/0.44.3...0.44.4
Published by stefannica 11 months ago
The 0.46.1 release introduces support for Service Accounts and API Keys that
can be used to authenticate with the ZenML server from environments that do not
support the web login flow, such as CI/CD environments, for example.
Also included in this release are some documentation updates and bug fixes,
notably moving the database migration logic deployed with the Helm chart out of
the init containers and into a Kubernetes Job, which makes it possible to scale
out the ZenML server deployments without the risk of running into database
migration conflicts.
<1.0.0
by @strickvl in https://github.com/zenml-io/zenml/pull/2027
job
instead of init-container
to allow replicas by @safoinme in https://github.com/zenml-io/zenml/pull/2021
step.source_code
Cut-Off Limit by @fa9r in https://github.com/zenml-io/zenml/pull/2025
create_new_model_version
arg of ModelConfig
by @avishniakov in https://github.com/zenml-io/zenml/pull/2030
zenml up
prefill username when launching dashboard by @strickvl in https://github.com/zenml-io/zenml/pull/2024
Kaniko
docs by @safoinme in https://github.com/zenml-io/zenml/pull/2019
Full Changelog: https://github.com/zenml-io/zenml/compare/0.46.0...0.46.1
Published by strickvl 12 months ago
This release brings some upgrades, documentation updates and bug fixes. Notably,
our langchain
integration now supports more modern versions and has been
upgraded to a new version at the lower edge of supported packages on account of
a security vulnerability.
Other fixes related to the Model Control Plane which was updated to support the
deletion of model versions via the CLI, for example.
We removed the llama_index
integration in this release. This related to
unsolvable dependency clashes that relate to sqlmodel
and our database. We
expect these clashes to be resolved in the future and then we will add our
integration back in. If you were using the llama_index
materializer that was
part of the integration, you will have to use a custom materializer in the
meanwhile. We apologize for the inconvenience.
gcs bucket
docs error message by @safoinme in https://github.com/zenml-io/zenml/pull/2018
Skypilot
docs configuration by @safoinme in https://github.com/zenml-io/zenml/pull/2017
langchain
, disable llama_index
, and fix Vector Store materializer by @strickvl in https://github.com/zenml-io/zenml/pull/2013
GCPImageBuilder
by @fa9r in https://github.com/zenml-io/zenml/pull/1992
Full Changelog: https://github.com/zenml-io/zenml/compare/0.45.6...0.46.0
Published by stefannica 12 months ago
This release brings an array of enhancements and refinements. Notable improvements include
allowing for disconnecting
service connectors from stack components, adding connector support to the
sagemaker step operator, turning synchronous mode on by default for all orchestrators, and enabling
server-side component config validation.
README.md
and update images by @znegrin in https://github.com/zenml-io/zenml/pull/1986
@step
warning message by @strickvl in https://github.com/zenml-io/zenml/pull/1994
BasePyTorchMaterliazer
-> Materializer
by @cameronraysmith in https://github.com/zenml-io/zenml/pull/1969
Full Changelog: https://github.com/zenml-io/zenml/compare/0.45.5...0.45.6
Published by strickvl 12 months ago
This minor release contains bugfixes and documentation improvements. Notably,
our sqlmodel
dependency has been pinned to 0.0.8 which fixes installation
errors following the release of 0.0.9.
mypy
, ruff
and black
by @strickvl in https://github.com/zenml-io/zenml/pull/1963
0.0.8
by @strickvl in https://github.com/zenml-io/zenml/pull/1973
Full Changelog: https://github.com/zenml-io/zenml/compare/0.45.4...0.45.5
Published by avishniakov 12 months ago
This minor update fixes a database migration bug that you could potentially encounter while upgrading your ZenML version and relates to use of the ExternalArtifact
object.
If you are upgrading from <0.45.x version, this is the recommended release.
PROBLEMS?: If you upgraded to ZenML v0.45.2 or v0.45.3 and are experiencing issues with your database, please consider upgrading to v0.45.4 instead.
ModelConfig
by @avishniakov in https://github.com/zenml-io/zenml/pull/1954
Full Changelog: https://github.com/zenml-io/zenml/compare/0.45.3...0.45.4
Published by strickvl almost 1 year ago
This minor update fixes a database migration bug that you could potentially encounter while upgrading your ZenML version and relates to use of the ExternalArtifact
object.
PROBLEMS?: If you upgraded to ZenML v0.45.2 and are experiencing issues with your database, please either reach out to us on Slack directly or feel free to use this migration script that will manually fix the issue. (Please do backup your database before using the migration script so as to prevent any data loss!)
This release also includes a bugfix from @cameronraysmith relating to the
resolution of our Helm chart OCI location. Thank you!
external_input_artifact
backward compatibility with alembic by @avishniakov in https://github.com/zenml-io/zenml/pull/1957
Full Changelog: https://github.com/zenml-io/zenml/compare/0.45.2...0.45.3
Published by strickvl about 1 year ago
This release replaces 0.45.0 and 0.45.1, and fixes the major migration bugs that were in
that yanked release. Please upgrade directly to 0.45.2 and avoid upgrading to
0.45.0 to avoid unexpected migration issues.
Note that 0.45.0 and 0.45.1 were removed from PyPI due to an issue with the
alembic versions + migration which could affect the database state. This release
fixes that issue.
If you have already upgraded to 0.45.0 please let us know in Slack and we'll happy to assist in rollback and recovery.
This release introduces a major upgrade to ZenML, featuring a new authentication mechanism, performance improvements, the introduction of the model control plane, and internal enhancements.
Our improved authentication mechanism offers a more secure way of connecting to the ZenML server. It initiates a device flow that prompts you to log in via the browser dashboard:
zenml connect --url <YOUR_SERVER_URL>
This eliminates the need for explicit credential input. The previous method (zenml connect --url <URL> --username <USERNAME> --password <PASSWORD>
) remains operational but is less recommended due to security concerns.
Critical This change disrupts existing pipeline schedules. After upgrading, manually cancel and reschedule pipelines using the updated version of ZenML.
For more information, read about the device flow in our documentation.
Internal API adjustments have reduced the footprint of ZenML API objects by up to 35%. This will particularly benefit users with large step and pipeline configurations. Further reductions will be implemented in our next release.
ZenML now includes a preliminary version of the model control plane, a feature for registering models and their metadata on a single ZenML dashboard view. Future releases will provide more details. To test this early version, follow this example.
ZENML_AUTH_TYPE
and ZENML_JWT_SECRET_KEY
have been renamed to ZENML_SERVER_AUTH_SCHEME
and ZENML_SERVER_JWT_SECRET_KEY
, respectively.UnmaterializedArtifact
has been relocated to zenml.artifacts
. Change your import statement from from zenml.materializers import UnmaterializedArtifact
to from zenml.artifacts.unmaterialized_artifact import UnmaterializedArtifact
.zenml.steps.external_artifact.ExternalArtifact
has moved to zenml.artifacts.external_artifact.ExternalArtifact
.neptune-client
> neptune
by @fa9r in https://github.com/zenml-io/zenml/pull/1837
develop
by @strickvl in https://github.com/zenml-io/zenml/pull/1842
README
for examples
folder by @strickvl in https://github.com/zenml-io/zenml/pull/1860
user
param to be specified (successfully) in DockerSettings
by @strickvl in https://github.com/zenml-io/zenml/pull/1857
get_pipeline_context
by @avishniakov in https://github.com/zenml-io/zenml/pull/1870
upgrade
migration script after the database changes by @bcdurak in https://github.com/zenml-io/zenml/pull/1877
click
decorator in model CLI command by @safoinme in https://github.com/zenml-io/zenml/pull/1932
Skypilot
orchestrator setting docs section by @safoinme in https://github.com/zenml-io/zenml/pull/1931
Full Changelog: https://github.com/zenml-io/zenml/compare/0.44.3...0.45.0
Published by htahir1 about 1 year ago
This release replaces 0.45.0, and fixes the major migration bugs that were in that yanked release. Please upgrade directly to 0.45.1 and avoid upgrading to 0.45.0 to avoid unexpected migration issues.
This release introduces a major upgrade to ZenML, featuring a new authentication mechanism, performance improvements, the introduction of the model control plane, and internal enhancements.
Our improved authentication mechanism offers a more secure way of connecting to the ZenML server. It initiates a device flow that prompts you to log in via the browser dashboard:
zenml connect --url <YOUR_SERVER_URL>
This eliminates the need for explicit credential input. The previous method (zenml connect --url <URL> --username <USERNAME> --password <PASSWORD>
) remains operational but is less recommended due to security concerns.
Critical This change disrupts existing pipeline schedules. After upgrading, manually cancel and reschedule pipelines using the updated version of ZenML.
For more information, read about the device flow in our documentation.
Internal API adjustments have reduced the footprint of ZenML API objects by up to 35%. This will particularly benefit users with large step and pipeline configurations. Further reductions will be implemented in our next release.
ZenML now includes a preliminary version of the model control plane, a feature for registering models and their metadata on a single ZenML dashboard view. Future releases will provide more details. To test this early version, follow this example.
ZENML_AUTH_TYPE
and ZENML_JWT_SECRET_KEY
have been renamed to ZENML_SERVER_AUTH_SCHEME
and ZENML_SERVER_JWT_SECRET_KEY
, respectively.UnmaterializedArtifact
has been relocated to zenml.artifacts
. Change your import statement from from zenml.materializers import UnmaterializedArtifact
to from zenml.artifacts.unmaterialized_artifact import UnmaterializedArtifact
.zenml.steps.external_artifact.ExternalArtifact
has moved to zenml.artifacts.external_artifact.ExternalArtifact
.neptune-client
> neptune
by @fa9r in https://github.com/zenml-io/zenml/pull/1837
develop
by @strickvl in https://github.com/zenml-io/zenml/pull/1842
README
for examples
folder by @strickvl in https://github.com/zenml-io/zenml/pull/1860
user
param to be specified (successfully) in DockerSettings
by @strickvl in https://github.com/zenml-io/zenml/pull/1857
get_pipeline_context
by @avishniakov in https://github.com/zenml-io/zenml/pull/1870
upgrade
migration script after the database changes by @bcdurak in https://github.com/zenml-io/zenml/pull/1877
click
decorator in model CLI command by @safoinme in https://github.com/zenml-io/zenml/pull/1932
Skypilot
orchestrator setting docs section by @safoinme in https://github.com/zenml-io/zenml/pull/1931
Full Changelog: https://github.com/zenml-io/zenml/compare/0.44.3...0.45.0
Published by safoinme about 1 year ago
This release introduces a major upgrade to ZenML, featuring a new authentication mechanism, performance improvements, the introduction of the model control plane, and internal enhancements.
Our improved authentication mechanism offers a more secure way of connecting to the ZenML server. It initiates a device flow that prompts you to log in via the browser dashboard:
zenml connect --url <YOUR_SERVER_URL>
This eliminates the need for explicit credential input. The previous method (zenml connect --url <URL> --username <USERNAME> --password <PASSWORD>
) remains operational but is less recommended due to security concerns.
Critical This change disrupts existing pipeline schedules. After upgrading, manually cancel and reschedule pipelines using the updated version of ZenML.
For more information, read about the device flow in our documentation.
Internal API adjustments have reduced the footprint of ZenML API objects by up to 35%. This will particularly benefit users with large step and pipeline configurations. Further reductions will be implemented in our next release.
ZenML now includes a preliminary version of the model control plane, a feature for registering models and their metadata on a single ZenML dashboard view. Future releases will provide more details. To test this early version, follow this example.
ZENML_AUTH_TYPE
and ZENML_JWT_SECRET_KEY
have been renamed to ZENML_SERVER_AUTH_SCHEME
and ZENML_SERVER_JWT_SECRET_KEY
, respectively.UnmaterializedArtifact
has been relocated to zenml.artifacts
. Change your import statement from from zenml.materializers import UnmaterializedArtifact
to from zenml.artifacts.unmaterialized_artifact import UnmaterializedArtifact
.zenml.steps.external_artifact.ExternalArtifact
has moved to zenml.artifacts.external_artifact.ExternalArtifact
.neptune-client
> neptune
by @fa9r in https://github.com/zenml-io/zenml/pull/1837
develop
by @strickvl in https://github.com/zenml-io/zenml/pull/1842
README
for examples
folder by @strickvl in https://github.com/zenml-io/zenml/pull/1860
user
param to be specified (successfully) in DockerSettings
by @strickvl in https://github.com/zenml-io/zenml/pull/1857
get_pipeline_context
by @avishniakov in https://github.com/zenml-io/zenml/pull/1870
upgrade
migration script after the database changes by @bcdurak in https://github.com/zenml-io/zenml/pull/1877
click
decorator in model CLI command by @safoinme in https://github.com/zenml-io/zenml/pull/1932
Skypilot
orchestrator setting docs section by @safoinme in https://github.com/zenml-io/zenml/pull/1931
Full Changelog: https://github.com/zenml-io/zenml/compare/0.44.3...0.45.0
This release, introduces SkyPilot, a new VM orchestrator for ZenML that lets users run pipelines on their choice of cloud provider VMs, offering a GPU option without Kubernetes or serverless orchestrators. This release also brings bug fixes and improvements, including a streamlined 'connect' command, interactive configuration for 'zenml stack deploy,' and enhanced documentation covering SageMaker, GCP, and service connectors with MFA.
This release introduces a new orchestrator called SkyPilot. SkyPilot is a VM orchestrator
that can be used to run ZenML pipelines on a VM of choice in one of the three supported
cloud providers. It is an excellent choice for users who want to run ZenML pipelines on a GPU
instance, but don't want to use Kubernetes or serverless orchestrators like SageMaker.
This release fixes several bugs and improves the user experience of the CLI and the
documentation. The most notable changes are:
connect
command that allows connecting all stack components within a stack to azenml stack deploy
command that allows users torich
and uvicorn
by @jlopezpena in https://github.com/zenml-io/zenml/pull/1750
SECURITY.md
file for vulnerability disclosures. by @strickvl in https://github.com/zenml-io/zenml/pull/1824
zenml stack describe
to show mlstacks
outputs by @strickvl in https://github.com/zenml-io/zenml/pull/1826
code_repository
for error message by @strickvl in https://github.com/zenml-io/zenml/pull/1832
zenml stack deploy
by @strickvl in https://github.com/zenml-io/zenml/pull/1829
README
file for helm chart by @strickvl in https://github.com/zenml-io/zenml/pull/1830
generative_chat
example README by @bhatt-priyadutt in https://github.com/zenml-io/zenml/pull/1836
Full Changelog: https://github.com/zenml-io/zenml/compare/0.44.2...tes
Published by fa9r about 1 year ago
This release contains updates for some of the most popular integrations, as well as several bug fixes and documentation improvements.
zenml list
commands was reduced to 20 (from 50) to speed up the runtime of such commands.mlflow
integration now supports the newest MLflow version 2.6.0
.evidently
integration now supports the latest Evidently version 0.4.4
.aws
integration now supports authentication via service connectors.bandit
to CI for security linting by @strickvl in https://github.com/zenml-io/zenml/pull/1775
mlstacks
compatibility check to CI by @strickvl in https://github.com/zenml-io/zenml/pull/1767
StepContext
visibility to materializers by @avishniakov in https://github.com/zenml-io/zenml/pull/1769
develop
by @strickvl in https://github.com/zenml-io/zenml/pull/1788
MLflow
version to allow support for 2.6.0 by @safoinme in https://github.com/zenml-io/zenml/pull/1782
ConnectionError
error message by @fa9r in https://github.com/zenml-io/zenml/pull/1783
Full Changelog: https://github.com/zenml-io/zenml/compare/0.44.1...0.44.2
Published by safoinme about 1 year ago
This release brings various improvements over the previous version, mainly focusing on using the newly refactored mlstacks
package, ZenML's logging
module and the changes in our analytics.
Note: 0.44.0 was removed from Pypi due to an issue with the alembic versions which could affect the database state. A branch occurred in the versions: 0.42.1 -> [0.43.0, e1d66d91a099] -> 0.44.0. This release fixes the issue.
The primary issue arises when deploying version 0.44.0 using a MySQL backend. Although the alembic migration executes all tasks up to 0.44.0, the alembic version represented in the database remains at 0.43.0. This issue persists irrespective of the measures taken, including trying various versions after 0.43.0.
This imbalance leads to failure when running a second replica migration because the database's state is at 0.44.0 while the alembic version remains at 0.43.0. Similarly, attempts to run a second replica or restart the pod fail as the alembic tries to migrate from 0.43.0 to 0.44.0, which is not possible because these changes already exist in the database.
Please note: If you encounter this problem, we recommend you roll back to previous versions and upgrade to 0.43.0. If you still experience difficulties, please join our Slack community at https://zenml.io/slack. We're ready to help you work through this issue.
mlstacks
repo name change by @strickvl in https://github.com/zenml-io/zenml/pull/1754
qemu
/colima
Github Actions bug by @safoinme in https://github.com/zenml-io/zenml/pull/1760
ruff
and mypy
by @strickvl in https://github.com/zenml-io/zenml/pull/1762
MYSQL
Database during DB migrations by @safoinme in https://github.com/zenml-io/zenml/pull/1763
mlstacks
integration (and deprecation of old deployment logic) by @strickvl in https://github.com/zenml-io/zenml/pull/1721
zenml
version specified in TOC for SDK docs by @strickvl in https://github.com/zenml-io/zenml/pull/1770
Full Changelog: https://github.com/zenml-io/zenml/compare/0.43.0...0.44.1
Published by bcdurak about 1 year ago
This release has been removed from pypi due to an issue with the alembic versions which could affect the database state. A branch occurred in the versions: 0.42.1 -> [0.43.0, e1d66d91a099] -> 0.44.0.
The primary issue arises when deploying version 0.44.0 using a MySQL backend. Although the alembic migration executes all tasks up to 0.44.0, the alembic version represented in the database remains at 0.43.0. This issue persists irrespective of the measures taken, including trying various versions after 0.43.0.
This imbalance leads to failure when running a second replica migration because the database's state is at 0.44.0 while the alembic version remains at 0.43.0. Similarly, attempts to run a second replica or restart the pod fail as the alembic tries to migrate from 0.43.0 to 0.44.0, which is not possible because these changes already exist in the database.
Please note: If you encounter this problem, we recommend that you rollback to previous versions and then upgrade to 0.43.0. If you still experience difficulties, please join our Slack community at https://zenml.io/slack. We're ready to help you work through this issue.
This release brings various improvements over the previous version, mainly
focusing on the usage of newly refactored mlstacks
package, ZenML's logging
module and the changes in our analytics.
mlstacks
repo name change by @strickvl in https://github.com/zenml-io/zenml/pull/1754
qemu
/colima
Github Actions bug by @safoinme in https://github.com/zenml-io/zenml/pull/1760
ruff
and mypy
by @strickvl in https://github.com/zenml-io/zenml/pull/1762
MYSQL
Database during DB migrations by @safoinme in https://github.com/zenml-io/zenml/pull/1763
mlstacks
integration (and deprecation of old deployment logic) by @strickvl in https://github.com/zenml-io/zenml/pull/1721
Full Changelog: https://github.com/zenml-io/zenml/compare/0.43.0...0.44.0
Published by avishniakov about 1 year ago
This release brings limited support for Python 3.11, improves quickstart experience with the fully reworked flow, enhances the user experience while dealing with ZenML docs, offers new extended templates for projects and fixes GCP connector creation issue.
This release adds limited support for Python 3.11.
The following integrations are currently not tested and may behave unexpectedly with Python 3.11:
This is because:
A minor breaking change in CLI for zenml init
:
--starter
--template-with-defaults
MLflow
configuration as environment variables before deployment subprocess by @safoinme in https://github.com/zenml-io/zenml/pull/1705
list_model_versions
by @avishniakov in https://github.com/zenml-io/zenml/pull/1703
transition_model_stage
to transition_model_version_stage
by @avishniakov in https://github.com/zenml-io/zenml/pull/1707
predict
by @avishniakov in https://github.com/zenml-io/zenml/pull/1715
ignore_cols
in evidently_report_step
by @avishniakov in https://github.com/zenml-io/zenml/pull/1711
ruff
to 0.0.282 by @strickvl in https://github.com/zenml-io/zenml/pull/1730
MLflow
to 2.5.0 by @safoinme in https://github.com/zenml-io/zenml/pull/1708
init --template
CLI for new templates by @avishniakov in https://github.com/zenml-io/zenml/pull/1731
Full Changelog: https://github.com/zenml-io/zenml/compare/0.42.0...0.43.0
Published by stefannica about 1 year ago
This is a minor release that fixes a couple of minor issues and improves the
quickstart example.
The implicit authentication methods supported by cloud Service Connectors method
may constitute a security risk, because they can give users access to the same
cloud resources and services that the ZenML Server itself is allowed to access.
For this reason, the default behavior of ZenML Service Connectors has been
changed to disable implicit authentication methods by default. If you try to
configure any of the AWS, GCP or Azure Service Connectors using the implicit
authentication method, you will now receive an error message.
To enable implicit authentication methods, you have to set the
ZENML_ENABLE_IMPLICIT_AUTH_METHODS
environment variable or the ZenML helm
chart enableImplicitAuthMethods
configuration option to true
.
MLflow
configuration as environment variables before deployment subprocess by @safoinme in https://github.com/zenml-io/zenml/pull/1705
Full Changelog: https://github.com/zenml-io/zenml/compare/0.42.0...0.42.1
Published by fa9r about 1 year ago
This release brings major user experience improvements to how ZenML logs are managed and displayed, removes Python 3.7 support, and fixes the Python 3.10 PyYAML issues caused by the Cython 3.0 release.
The log messages written by ZenML when running pipelines or executing ZenML CLI commands are now more concise and easier to digest and the log message colors were adjusted to be more intuitive. Additionally, all log messages, including custom prints to stdout, now show up as step logs in the dashboard.
Python 3.7 reached its end of life on on June 27th, 2023. Since then, several MLOps tools have stopped supporting Python 3.7. To prevent dependency issues with our integrations and other open-source packages, ZenML will also no longer support Python 3.7 starting from this release.
ZenML now requires PyYAML 6 since older versions are broken under Python 3.10. Subsequently, the following integrations now require a higher package version:
kfp==1.8.22
kfk-tekton==1.7.1
evidently==0.2.7
or evidently==0.2.8
fastapi
dependency version by @fa9r in https://github.com/zenml-io/zenml/pull/1675
teams.yaml
by @avishniakov in https://github.com/zenml-io/zenml/pull/1688
Full Changelog: https://github.com/zenml-io/zenml/compare/0.41.0...0.42.0
Published by fa9r over 1 year ago
ZenML release 0.41.0 comes with a second round of updates to the pipeline and step interface with major changes in how step outputs are defined, how information about previous runs can be fetched programmatically, and how information about the current run can be obtained.
See this docs page for an overview of all pipeline interface changes introduced since release 0.40.0 and for more information on how to migrate your existing ZenML pipelines to the latest syntax.
The entire syntax of fetching previous runs programmatically was majorly redesigned. While the overall user flow is still almost identical, the new approach does not contain pipeline-versioning-related inconsistencies, has a more intuitive syntax, and is also easier for users to learn since the new syntax uses the ZenML Client and response models natively instead of requiring the zenml.post_execution
util functions and corresponding ...View
wrapper classes.
How to fetch information about the current pipeline run from within the run has been majorly redesigned:
StepContext
is now a singleton that can be accessed via the new zenml.get_step_context()
function.StepContext
is now decoupled from the StepEnvironment
and the StepEnvironment
is deprecated.StepContext
now contains the full PipelineRunResponseModel
and StepRunResponseModel
so all information about the run is accessible, not just the name / id / params.Instead of using the zenml.steps.Output
class to annotate steps with multiple outputs, ZenML can now handle Tuple
annotations natively and output names can now be assigned to any step output using typing_extensions.Annotated
.
StepContext
by @fa9r in https://github.com/zenml-io/zenml/pull/1648
zenml deploy
story by @wjayesh in https://github.com/zenml-io/zenml/pull/1651
Full Changelog: https://github.com/zenml-io/zenml/compare/0.40.3...0.41.0
Published by stefannica over 1 year ago
This is a minor ZenML release that introduces a few new features around Service Connectors and Dashboard improvements:
Service Connectors can now also be managed through the ZenML Dashboard
the Azure Service Connector is now available in addition to the AWS and GCP ones. It can be used to connect ZenML and Stack Components to Azure cloud infrastructure resources like Azure Blob Storage, Azure Container Registry and Azure Kubernetes Service.
added ability to view pipeline run logs in the ZenML Dashboard
adds zenml secret export
CLI command to export secrets from the ZenML Secret Store to a local file
adds the ability to create/update ZenML secrets from JSON/YAML files or command line arguments (courtesy of @bhatt-priyadutt)
In addition to that, this release also contains a couple of bug fixes and improvements, including:
zenml secret export
CLI command by @fa9r in https://github.com/zenml-io/zenml/pull/1607
Full Changelog: https://github.com/zenml-io/zenml/compare/0.40.3...0.40.2
Published by htahir1 over 1 year ago
Minor release with a few docs changes and preparation of the MLOps Platform Sandbox
zenml show
by @fa9r in https://github.com/zenml-io/zenml/pull/1570
mlflow_tracking
example test by @strickvl in https://github.com/zenml-io/zenml/pull/1581
ruff
and mypy
by @strickvl in https://github.com/zenml-io/zenml/pull/1590
config.yaml
references in example docs by @strickvl in https://github.com/zenml-io/zenml/pull/1585
Github
repo token optional by @safoinme in https://github.com/zenml-io/zenml/pull/1593
Full Changelog: https://github.com/zenml-io/zenml/compare/0.40.1...0.40.2