MLOps lifecycle stages

Fully Automated MLOps

Arturo Opsetmoen Amador

Senior Consultant - Machine Learning

The MLOps lifecycle

The MLOps lifecycle includes three core stages:

Image of the MLOps lifecycle. Three circle cycles connected to each other. The names of each circle from left to right are: Design, Development, Deployment.

  • The three stages are iterative
  • The three stages are interconnected and rely on each other
  • It is normal to go back and forth between stages
Fully Automated MLOps

MLOps in the ML lifecycle - Design

The Design stage includes:

  • Business understanding
    $$
  • Data understanding
    $$
  • Designing the ML solution

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A figure with a circular cycle with the word Design in the center

Fully Automated MLOps

MLOps in the ML lifecycle - Design

The Design stage includes:

  • Business understanding
    $$
    • Understanding the business context
    • Establishing the business goals

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A figure with a circular cycle with the word Design in the center

Fully Automated MLOps

MLOps in the ML lifecycle - Design

The Design stage includes:

  • Data understanding
    $$
    • Data exploration
    • Data visualization

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A figure with a circular cycle with the word Design in the center

Fully Automated MLOps

MLOps in the ML lifecycle - Design

The Design stage includes:

  • System Design
    $$
    • System architecture design
      • Data security
      • Data privacy

$$

A figure with a circular cycle with the word Design in the center

Fully Automated MLOps

MLOps in the ML lifecycle - Design

The Design stage includes:

  • Business understanding
    $$
  • Data understanding
    $$
  • Designing the ML solution

$$

Much of the design phase can't be automated

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A figure with a circular cycle with the word Design in the center

Fully Automated MLOps

MLOps in the ML lifecycle - Development

The ML experimentation and development stage includes: $$

  • Developing Proof-of-Concepts (PoCs)
    $$
  • Data engineering
    $$
  • Model development

$$

A figure with a circular cycle with the word Development in the center

Fully Automated MLOps

MLOps in the ML lifecycle - Development

The ML experimentation and development stage includes:

  • Developing Proof-of-Concepts (PoCs)
    $$
    • Combination of process & automation
    • Use of frameworks

$$

A figure with a circular cycle with the word Development in the center

Fully Automated MLOps

MLOps in the ML lifecycle - Development

The ML experimentation and development stage includes:

  • Data engineering (PoCs)
    $$
    • Use of automation --> Quality assurance

$$

A figure with a circular cycle with the word Development in the center

Fully Automated MLOps

MLOps in the ML lifecycle - Development

The ML experimentation and development stage includes:

  • Model development (PoCs)
    $$
    • Experiment tracking
    • Automated training
    • Automated hyperparameter tuning

$$

A figure with a circular cycle with the word Development in the center

Fully Automated MLOps

MLOps in the ML lifecycle - Deployment

The ML deployment and operations phase include:

  • Productionization
    • Testing
    • Versioning
    • Continuous delivery
    • Monitoring

$$

A figure with a circular cycle with the word Deployment in the center

Fully Automated MLOps

Building for scale: Automation first

We use process streamlining, best practices, and automation

Image of the MLOps lifecycle. Three circle cycles connected to each other. The names of each circle from left to right are: Design, Development, Deployment.

When no automation, process streamlining:

  • CRISP-DM
  • TDSP [1]
1 https://www.ibm.com/docs/en/spss-modeler/saas?topic=dm-crisp-help-overview
Fully Automated MLOps

Process streamlining and best practices

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Design phase

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  • Best practices

    • Include domain expertise

    • Involve business stakeholders

    • Get feedback from end-users

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Development phase

$$

  • Best practices

    • Write clean code
    • Document our work
Fully Automated MLOps

Let's practice!

Fully Automated MLOps

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