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Releases: Azure/mlops-v2

v1.1.0 Release

09 Feb 14:24
@setuc setuc
v1.1.0
a963d1f
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The repository now contains the following patterns that have been implemented:

1. Classical / Tabular Machine Learning Model
a. Supports Azure DevOps and GitHub Actions including the deployment of Infrastructure with both the platforms.
b. Supports Azure Data Explorer based Monitoring, Data Drift and Anomaly Detection. It is enabled for Terraform and can be invoked via Python SDKv1 or Azure ML CLI v2 (aml-cli-v2).
c. Can deploy both online as well as batch end points.
d. Supports MLOPs pipelines with Azure ML (AML) CLI v2, Python SDK V1 and V2.
e. Contains Responsible AI and python test modules.
f. Support for Feathr Feature store.

2. Computer Vision (CV) Model
a. Supports Azure DevOps and GitHub Actions. Note that GitHub Actions are only working for Azure ML CLI v2 (aml-cli-v2).
b. Supports MLOPs pipelines with Azure ML (AML) CLI v2, and Python SDK V1.
c. Can deploy both online as well as batch end points.

3. Natural Language Processing (NLP) Model
a. Supports for Azure DevOps and GitHub Actions. Note that GitHub Actions are only working for Azure ML CLI v2 (aml-cli-v2).
b. Supports MLOPs pipelines with Azure ML (AML) CLI v2, and Python SDK V2.
c. Can deploy both online as well as batch end points.

Other Patterns included in the release:

  • Improve documentation for GitHub Actions and Azure DevOps available on the main GitHub Link
  • Templates for using individual / repeatable steps in your template. These templates are available for GitHub Actions and Azure DevOps (CLI and SDK). The Template repo can be found here: https://github.com/Azure/mlops-templates
  • Registration of Multiple Datasets
  • Using 3rd party / external containers. Support for dependabot python package scans via pip install in docker container.
  • Support for secure workspaces
  • Quick Deploy Examples with Azure DevOps (ADO); GitHub and Microsoft Learn
  • Feathr Feature Store: Integration of Feathr as an enterprise scale feature store in the MLOps V2 extended architectures, deployment of Feathr using Terraform script and running a simple classical ML example.

What's Changed

  • Update sparse_checkout.sh by @cindyweng in #53
  • update documentation to reflect GHA infra by @cindyweng in #57
  • change pointer to correct repo by @cindyweng in #60
  • Update QUICKSTART.md by @akritim in #61
  • Add azure devops repo init by @drosevear in #54
  • Feature/issue templates by @setuc in #70
  • Update repository-issue.md by @setuc in #73
  • Updated the issue template by @setuc in #74
  • Main dec31 by @setuc in #80
  • Fix broken links to deployment guides by @sdonohoo in #82
  • Update ADO project initialization and matching documentation by @sdonohoo in #84
  • Delete repository_arch.png:Zone.Identifier as it causes a cloning issue by @timschps in #86
  • Update to deployguide_gha.md to be more complete for users by @timschps in #87
  • Adding context/clarification for when using WSL (#89)

New Contributors

Full Changelog: v1.0.0...v1.1.0

Contributors

sdonohoo, cindyweng, and 4 other contributors
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v1.0.0 Release

02 Sep 12:02
@setuc setuc
v1.0.0
fc5cccb
This commit was created on GitHub.com and signed with GitHub’s verified signature. The key has expired.
GPG key ID: 4AEE18F83AFDEB23
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v1.0.0 Release

The repository now contains the following patterns that have been implemented:

1. Classical / Tabular Machine Learning Model
a. Supports Azure DevOps and GitHub Actions. Note that GitHub Actions are only working for Azure ML CLI v2 (aml-cli-v2).
b. Supports Azure Data Explorer based Monitoring, Data Drift and Anomaly Detection. It is enabled for Terraform and can be invoked via python sdk v1 or Azure ML CLI v2 (aml-cli-v2).
c. Can deploy both online as well as batch end points.

2. Computer Vision (CV) Model
a. Supports Azure DevOps and GitHub Actions. Note that GitHub Actions are only working for Azure ML CLI v2 (aml-cli-v2).
b. Currently there is no monitoring support for this.
c. Can deploy both online as well as batch end points.

3. Natural Language Processing (NLP) Model
a. Supports only support Azure DevOps via Azure ML CLI v2 (aml-cli-v2).
b. Currently there is no monitoring support for this.
c. Can deploy both online as well as batch end points.

Other Patterns included in the release

  • Templates for using individual / repeatable steps in your template. These templates are available for GitHUb Actions and Azure DevOps (CLI and SDK). The Template repo can be found here: https://github.com/Azure/mlops-templates
  • Registration of Multiple Datasets
  • Using 3rd party / external containers. Support for dependabot python package scans via pip install in docker container.

Full Changelog: https://github.com/Azure/mlops-project-template/commits/v1.0.0

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