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This article describes how to use the ModelOp Command Center as the central station to monitor your models. It also describes the MLC processes that generate the alerts, and how to react to alerts, tasks and notifications reported by the MLC.

The primary audience for this article is the Model ModelOps Support Team.

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Table of Contents

Table of Contents

ModelOp Command Center Dashboard

ModelOps Command Center Dashboard provides visibility into the health of the system and any events, conditions or tasks that need attention. You can customize an MLC process to test for technical problems within the model, underlying business problems that are revealed in the data set, and for the efficacy of a model using metrics that warn the operator when the metrics fall outside of the configured range.

Operators in the MLC are configured to produce messages that are accessible through the Dashboard.

Brendan Kelly (Deactivated) screenshot with overlay

ModelOp Center Messages

The types messages generated from the monitoring infrastructure include:

  • Alerts - test failures and model errors that require a response.

  • Tasks - user tasks such as approve a model, acknowledge a failed test, etc.

    • For details about viewing and responding to test failures, see Addressing User Tasks on this page.

  • Notifications - includes system status, engine status and errors, and model errors

Model Test Failures

  1. Click Test Failure in the Models pane.

  2. Triage

Model Errors or Engine Errors

  1. Click Model Error.

  2. Triage

Addressing User Tasks

User tasks are displayed under the Tasks & Alerts tab in the column on the left. Tasks are filtered by All Open Tasks and Tasks in Progress.

ModelOps has a task management tool and also integrates with the task management tool of your choise, such as ServiceNow or Jira.

  1. Click the Tasks and Alerts icon in the left column. Tasks are filtered by All Open Tasks and Tasks in Progress. 

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RunTime/ Engine Monitoring

The Runtime monitor displays the following information about the Runtime environment:

  • Endpoint throughput

  • User CPU utilization and Kernel CPU usage

  • Real-time system resource usage

  • A diagram of the MLC process currently managing the model

  • A live scroll of the logs

http://mocaasin.modelop.com/#/engine_overview/engine_view

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