Change Log

All notable changes to this project will be documented in this file.

[1.3.0] - 2024-5-22

Added

Changed

Refactored code to follow OOP paradigm
Made kfp a required dependency of AutoMLOps
kfp v2 code is now generated and required for use with AutoMLOps; before this version, kfp<2.0.0 was required. kfp v2 is not always backwards compatibile with v1
Removed support for reading/writing kfp components directly. AutoMLOps now only supports our standard AutoMLOps.component and AutoMLOps.pipeline syntax rather than dsl.component
Removed requirement that input parameters for AutoMLOps.component be python primitives only
Removed the need for .AutoMLOps-cache; files are no longer written to an itermediary location and stored in memory instead
Updated examples directory to support new changes/updates

Fixed

[1.2.9] - 2024-1-18

Added

Added setup_model_monitoring parameter to AutoMLOps.generate and orchestration/configs.py
Added the creation of a model_monitoring/ directory and create_model_monitoring_job.sh script to generate
Added a new AutoMLOps.monitor function, along with relevant templates and tests
Added in a monitoring section into the generated config/defaults.yaml file
Added logging.googleapis.com to the list of potentially required apis.
Created 2 new functions for giving warnings when running AutoMLOps.monitor: get_model_monitoring_min_permissions and get_model_monitoring_recommended_roles in utils.py

Changed

Updated the services/submission_service/main.py.j2 to include elements for automatic retraining based on monitoring anomaly logs, and adding in labels to the submit.
Updated services/submission_service/requirements.txt to include google-cloud-storage.
Updated the README.md.j2 to reflect the optional creation of the new model_monitoring/ directory.
Changed the format for how config/defaults.yaml file gets written; this file is now written using the write_yaml_file function (yaml.safe_dump) in utils.py.
Updated the account_permissions_warning function in utils.py to include a new operation: operation='model_monitoring'
Updated the introductory example, readme, and user guide to reflect the new monitoring capabilities.
Renamed validate_schedule in utils.py to validate_use_ci to reflect new requirements for model monitoring.

Fixed

[1.2.8] - 2024-1-09

Added

Support for Output annotations with AutoMLOps.component

Changed

Fixed

[1.2.7] - 2023-11-06

Added

Changed

Updated state_bucket naming schema
Updated unit tests to reflect state_bucket naming schema
Updated outputs.tf block to not include csr if use_ci=False

Fixed

[1.2.6] - 2023-10-05

Added

Changed

Updated default to not disable api services
Changed required_permissions and recommend_roles from set to list
Updated required_permissions and recommend_roles lists to be dynamic based on user tooling selection
Changed google_project_iam_member block to use a local list for setting iam roles
Moved csr creation to only occur if use_ci=True
Updated github_actions config to use source_repo_branch parameter into of default automlops branch

Fixed

Fixed run local issue regarding dockerfile pathing
Fixed cloudbuild trigger terraform bug with ignored_files

[1.2.5] - 2023-10-05

Added

Changed

Fixed

Fixed bug with generating .github/workflows directories

[1.2.4] - 2023-10-03

Added

Changed

Only will create .github/ directory if using github-actions

Fixed

Pinned the python docker container step for the cloudbuild yaml to python:3.10, this address some dependency issues with the latest python docker image

[1.2.3] - 2023-09-29

Added

Support for Github Actions integration
Added workload identity federation integration

Changed

Updated documentation
.git and relevant files are now placed inside the AutoMLOps/ base directory

Fixed

Set default cloud functions registry to the artifact-registry that is created as part of the provision operation

[1.2.2] - 2023-09-25

Added

Changed

Commented out change from 1.2.1 to set cloud functions default registry to artifact-registry; there appears to be an auth bug with this setting
Updated documentation

Fixed

Removed legacy ml.googleapis.com API that is deprecated as of 9/25/2023

[1.2.1] - 2023-09-20

Added

Support for Vertex AI experiments
Added in an include statement for the build trigger (only runs on changes to AutoMLOps/**)

Changed

Set default cloud functions registry to artifact-registry
Changed recommended roles and permissions for deploying with use_ci=False.

Fixed

Fixed issues with use_ci=False provision directory not being created properly
Fixed issues with use_ci=False terraform config

[1.2.0] - 2023-09-13

Added

Major version updates:

Code is now broken down into 5 main operations: generate, provision, deprovision, deploy, and launchAll
Uses jinja2 templates for storing code templates and writing to files
Additional package dependencies using Jinja2 templates and deploying with precheck function
Provides additional warnings and checks for giving IAM permissions visibility to the user
Creates a .gitignore by default
Support for cloud-functions in addition to cloud-run for the submission service
Added 2 new generated folders: provision/ and services/
Added naming_prefix parameter to allow for differentiating between AutoMLOps pipelines in the same project
Significant generalization in terms of tooling (now allows for specifying provisioning_frameworks, deployment_frameworks, etc.)
Renamed backend src code folder to google_cloud_automlops to avoid naming confusion
Added enum and config files, which is different than previous approach of class inheritance

Changed

Updated README.md and documentation
Templatized code has now been pulled out and placed into jinja2 templates.
Gitops workflow placed into separate folder and file, will only version AutoMLOps/ directory instead of the whole cwd.
Reworked deployment workflow and build configuration (submission service and cloud scheduler are now created as part of the provision step).
Update notebook examples
Changed wording and branding descriptions
Significant updates to unit tests

Fixed

Bugs related to provisioning with terraform

[1.1.4] - 2023-07-25

Added

Writes .gitkeep to scripts/pipeline_spec directory by default
Generates a readme.md into generated AutoMLOps codebase now by default

Changed

Two newlines after functions (linting)
Parameter mapping (list -> JsonArray, map -> JsonObject)
Updated documentation: added examples section into main readme, changed package version deps in examples notebooks

Fixed

Migration issues with pyyaml 5.4.1 since release of cython>3.0; Fixed by updating pyyaml version to 6.0.1.

[1.1.3] - 2023-07-07

Added

Added a BQML retail notebook example
Major unit tests added for kfp framework and cloudbuild deployments

Changed

Updated the git workflow to check that the remote is pointing to the correct project id.

Fixed

Pinned all kfp versions to kfp<2.0.0. to address the recent migration to kfp2+.

[1.1.2] - 2023-05-26

Added

Added in optional parameter for specifying a base_image.
Created an example notebook that walks the user through a transfer learning example using a GPU.
Added in a clear_cache function which deletes all files within the tmpfiles directory.

Changed

Updated readme and implementation guide.
Long-term change: .tmpfiles/ subdirectory to .AutoMLOps-cache/
Long-term change: removed use_kfp_spec from parameter lists and switched to determining this at run-time.

Fixed

Removed redundant code for cloudbuild config generation.
Updated constants.py file to remove constants no longer being used.
Fixed custom imports mismatch between kfp spec and custom automlops spec.
Verified custom_training_jobs_specs works as intended.

[1.1.1] - 2023-05-17

Added

Refactored backend modules to be structured based on frameworks (e.g. kfp, tfx, etc.) and deployments (e.g. cloudbuild, github actions, etc.)
Added some unit tests for the utils.py module.

Changed

Moved unit tests to /tests directory.

[1.1.0] - 2023-04-28

Added

New interface for defining AutoMLOps components and Pipelines. Removed the need to call Jupyter cell decorators and replaced them with Python function based decorators instead.
New feature updates allow for running AutoMLOps outside of Jupyter Notebooks.
Examples for running AutoMLOps outside of a notebook, as well as an example inferencing pipeline.
Faster build jobs

Changed

Updated readme and implementation guide.
Better logging
Better handling of requirements.txt (remove dups, infer from pipreqs, option to input explicit versions, sorted order)
Better versioning of models

Fixed

Bug that can change current working directory on failure with run_local=True.

[1.0.5] - 2023-03-06

Official release on PyPI.

[1.0.3] - 2023-03-06

Staging for PyPI.

Changed

Cleaning up wheel and egg files from repo.
Remove dist/ and build/ directories.

[1.0.2] - 2023-03-06

Added feature to allow for accelerated/distributed model training.

Added

Support for custom training job specs (specifies which resources to use for pipeline jobs).

Changed

Updated readme and implementation guide.
New custom_training_job_specs parameter.
Changed workflow for PipelineBuilder

Fixed

Bug related to grep substring match for create_resources script.

[1.0.1] - 2023-02-01

Reworked process to submit jobs to cloud runner service.

Added

Cloud Tasks Queue; API enabling, queue creation, and task generation.

Changed

run() workflow reduced; submission to cloud runner service now takes place as part of the cloudbuild script.
Creation of schedule job is now part of the cloudbuild script.
Removed submit_to_runner_svc.sh and create_scheduler.sh.
Added support for vpc_connectors.

Fixed

Bug related to waiting for cloudbuild job to complete before submitting to cloud runner service.
Bug related to elevated IAM privileges in order to authenticate before submitting to cloud runner service.

[1.0.0] - 2023-01-19

First major release