Version 1.8.0

Major Features and Improvements

• Added experimental exit_handler support for KubeflowDagRunner.
• Enabled custom labels to be submitted to CAIP training jobs.
• Enabled custom Python function-based components to share pipeline Beam configuration by [inheriting from BaseBeamComponent] (https://www.tensorflow.org/tfx/guide/custom_function_component)

Breaking Changes

For Pipeline Authors

• N/A

For Component Authors

• N/A

Deprecations

• N/A

Bug Fixes and Other Changes

• LatestBlessedModelStrategy gracefully handles the case where there are no blessed model at all (e.g. first run).
• Fix that the resolver with custom ResolverStrategy (assume correctly packaged) fails.
• Fixed ElwcBigQueryExampleGen data serializiation error that was causing an assertion failure on Beam.
• Added dark mode styling support for InteractiveContext notebook formatters.
• (Python 3.9+) Supports list and dict in type definition of execution properties.
• Populate Artifact proto name field when name is set on the Artifact python object.
• Temporarily capped apache-airflow version to 2.2.x to avoid dependency conflict. We will rollback this change once kfp releases a new version.
• Fixed a compatibility issue with apache-airflow 2.3.0 that is failing with "unexpected keyword argument 'default_args'".
• StatisticsGen will raise an error if unsupported StatsOptions (i.e., generators or experimental_slice_functions) are passed.

Dependency Updates

Package Name	Version Constraints	Previously (in v1.7.0)	Comments
apache-beam[gcp]	>=2.38,<3	>=2.36,<3	Synced release train

Documentation Updates

• N/A