Rollback strategies for failed updates in MLOps - Mini Project: Build & Apply

Rollback Strategies for Failed Updates

📖 Scenario: You are managing a machine learning model deployment system. Sometimes, new model updates fail and you need to rollback to the previous stable version quickly to keep the service running smoothly.

🎯 Goal: Build a simple Python script that tracks deployed model versions and implements a rollback strategy to revert to the last stable version if the current update fails.

📋 What You'll Learn

Create a dictionary to store model versions and their status

Add a variable to hold the current deployed version

Write logic to check if the current version failed and rollback to the last stable version

Print the final deployed version after rollback if needed

💡 Why This Matters

🌍 Real World

In real machine learning deployments, updates can fail and cause service disruption. Rollback strategies help maintain service availability by reverting to a stable model quickly.

💼 Career

Understanding rollback strategies is essential for MLOps engineers and DevOps professionals to ensure reliable and resilient machine learning systems.

1

Create model versions dictionary

Create a dictionary called model_versions with these exact entries: 'v1.0': 'stable', 'v1.1': 'failed', 'v1.2': 'stable'.

MLOps

# Your code here

Need a hint?

Use curly braces to create a dictionary with keys as version names and values as their status.

2

Set current deployed version

Create a variable called current_version and set it to the string 'v1.1' to represent the currently deployed model version.

MLOps

model_versions = {'v1.0': 'stable', 'v1.1': 'failed', 'v1.2': 'stable'}
# Your code here

Need a hint?

Assign the string 'v1.1' to the variable current_version.

3

Implement rollback logic

Write an if statement to check if model_versions[current_version] equals 'failed'. If true, set current_version to 'v1.0' as the rollback version.

MLOps

model_versions = {'v1.0': 'stable', 'v1.1': 'failed', 'v1.2': 'stable'}
current_version = 'v1.1'
# Your code here

Need a hint?

Use an if statement to check the status and assign the rollback version.

4

Print final deployed version

Write a print statement to display the text "Deployed model version: " followed by the value of current_version.

MLOps

model_versions = {'v1.0': 'stable', 'v1.1': 'failed', 'v1.2': 'stable'}
current_version = 'v1.1'
if model_versions[current_version] == 'failed':
    current_version = 'v1.0'
# Your code here

Need a hint?

Use print() with string concatenation to show the deployed version.