liveBook · Manning

Proportional response

As explained in Machine Learning System Design

Proportional response is an incident-management principle in which postincident actions are scaled according to the failure’s impact and likelihood of recurrence.

Proportional response scales postincident actions to a failure’s impact and the likelihood of recurrence. Use it to turn production failures into learning without making every incident a major program. section 16.1

From a runbook update to a reliability initiative

A small incident may merit a ten-minute discussion and a paragraph added to the runbook. A severe outage can justify a company-wide reliability initiative, especially when its causes could recur across systems. section 16.1

How Machine Learning System Design covers it

How deep it goes
Defines proportional sizing and illustrates it through discussion, runbook updates, and a company-wide reliability initiative.
Examples
Uses a spiky-load outage, a brief discussion with a runbook addition, and a company-wide release-reliability initiative.
What you can do after
Apply it by selecting remediation and learning activities that match incident severity and recurrence risk.
How it connects
Connects incident response with retrospectives, postmortems, runbooks, and reliability improvement.
Cover of Machine Learning System Design
liveBookmanning.com
Read Machine Learning System Design on liveBook Get the book at manning.com

This explainer was generated by Manning's knowledge graph from the text of Machine Learning System Design. The section links point to the parts of the book it draws on.