Question 400
At the Juniper housing nonprofit after a wider deployment, a plug-in runs on every update and repeatedly recalculates a score for irrelevant column changes. The operations team needs a supportable remediation with evidence for the handover. Which ongoing engineering control would most directly reduce recurrence?
Explanation
Correct Answer
The most relevant long-term safeguard is to review filtering attributes when the business data model changes. It preserves the remediation to register the Update step with only the relevant filtering attributes and guard execution as operating conditions change. In the Juniper housing nonprofit, assess this against the documented update filtering attributes scenario.
Incorrect Answers
“Monitor post-operation extensions for excessive execution time” checks a different ongoing risk rather than the reported failure: at the Juniper housing nonprofit after a wider deployment, a plug-in runs on every update and repeatedly recalculates a score for irrelevant column changes. The operations team needs a supportable remediation with evidence for the handover. The relevant mechanism is a broad Update registration triggers unnecessary executions. The directly matched preventive control is “Review filtering attributes when the business data model changes”.
That safeguard is appropriate for maintaining prevalidation rejection. It would not primarily prevent the reported failure, for which the relevant control is to review filtering attributes when the business data model changes. For case R082-PL400-CASE-0100, the decisive context is the 2 deployment setting at the Juniper housing nonprofit.
“Reassess MCP permissions and tool schemas when adding operations” checks a different ongoing risk rather than the reported failure: at the Juniper housing nonprofit after a wider deployment, a plug-in runs on every update and repeatedly recalculates a score for irrelevant column changes. The operations team needs a supportable remediation with evidence for the handover. The relevant mechanism is a broad Update registration triggers unnecessary executions. The directly matched preventive control is “Review filtering attributes when the business data model changes”.