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The DataOps Initiative puts together technical material and guides for users interested in the end-to-end process of deploying Machine Learning (ML) applications and models within their organizations.

By developing an inclusive set of DataOps and DevOps best practices for engineers, we can empower developers, architects, and decision-makers to effectively leverage open source tools and frameworks for streamlined, secure, and scalable ML application deployment.

What is DataOps?

  • Develop a series of high-level blog posts to raise awareness and flesh out the course material, test out ideas, in conjunction with OPEA and the CD Foundation
  • Develop the course materials, including practical implementations and code checks, and set up environments for developer and end users
  • Publish the course on Linux Foundation Training as a certification

Why are we putting this together?

Organizations face complex challenges in managing technical and data debt when deploying data-intensive applications and machine learning models, from initial development to operational maintenance. This process requires seamless integration of CI/CD practices, containerization, data infrastructure, MLOps, and security measures. We believe that agile methodologies, infrastructure as code, and cloud native development will be the foundation of modern Data Reliability Engineering and Machine Learning Platforms.

Who should participate?

We are looking for various folks to fill the following roles for each part of the curriculum.

  • Technical Writer
  • Technical Editor (code reviews)
  • Proofreader (content reviews)

Roadmap

  • Develop a series of high-level blog posts to raise awareness and flesh out the course material, test out ideas, in conjunction with OPEA and the CD Foundation
  • Develop the course materials, including practical implementations and code checks, and set up environments for developer and end users
  • Publish the course on Linux Foundation Training as a certification

Proposed Curriculum

Below is the proposed curriculum for the DataOps Initiative.

DataOps Curriculum

Fortnightly Meetings

We meet every two weeks on Wednesdays. View the schedule on the community calendar. To get an invitation, simply fill out this form.

Contributors

Lisa N Cao

Lisa Cao
Datastrato

Vivek Mangipudi

Vivek Mangipudi
Bayer Crop Science

Kierra Dotson

Kierra Dotson
IBM

Muktesh Mishra

Muktesh Mishra
Adobe

Roxanne Joncas

Roxanne Joncas
CD Foundation

Victor Lu

Victor Lu
Independent

Events & Recordings

Here are past and upcoming events related to DataOps or this initiative.

Workshop: Fundamentals of DataOps

This session discusses strategies and a complete beginner’s roadmap for groups trying to implement their own DataOps infrastructures from scratch by empowering developers, architects, and decision-makers to effectively leverage open-source tools and frameworks for streamlined, secure, and scalable ML application deployments. Register here

Techstrong.TV: Modern DataOps

Panel discusses their experiences around what modern DataOps has become, perspectives on evolving technologies, as well as future trends and pitfalls. DataOps is the intersection of DevOps and Data Engineering, which includes MLOps and AIOps. The discussion covers concerns such as pipeline orchestration, containerization, observability, as well as how the tooling should evolve in the space. Watch here

Blog Posts

Contact Us

If you have any issues with the form or any other questions, email us. info@cd.foundation

Connect with us

Subscribe to mailing list | Join #DataOps Slack Channel | View repo.

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