Auto-remediation
Trace a recommendation through the 3-step remediation workflow.
7 lessons. 1 quiz.
Read in order, or jump to what you need.
The 3-step workflow (precondition → action → validate)
By the end of this lesson, you will be able to trace any auto-remediation through its 3-4 step workflow, understand why each step exists, and reason about timing and failure modes.
The auto-remediation allowlist: auto, guided, advisory
By the end of this lesson, you will be able to identify which rules can be one-click auto-remediated, explain the two checks a recommendation passes before an Apply button appears, and plan adoption by deciding who in your org may start a remediation.
The approval gate
By the end of this lesson, you will be able to predict when a remediation waits for approval, act on an approval request as an admin, and set up your org's roles so destructive changes get a second look without stalling.
Three error classes: user_action, transient, system
By the end of this lesson, you will be able to triage any remediation failure into the right error class, execute the appropriate fix path, and avoid the support-ticket reflex for issues you can fix yourself.
Why ZopNight never auto-mutates customer databases
By the end of this lesson, you will be able to defend the database denylist to security audiences, explain the risk-reward math behind it, and distinguish what IS allowed (start/stop) from what isn't (modify/delete).
Remediation notifications: what is sent and where to look
By the end of this lesson, you will be able to name the three remediation notifications and when each is sent, route the approval notice to a team channel, and follow remediation outcomes when no completion email arrives.
The Recommendation Safety Gate
By the end of this lesson, you will be able to explain the two-tier model that decides whether a lever runs automatically, name the four authoritative evidence keys, and predict when a rule is demoted to advisory.
Module quiz.
Take it once the lessons are done.