Reporting running duration and inference units used - Rekognition

Reporting running duration and inference units used

If you trained and started your model after August 2022, you can use the InServiceInferenceUnits Amazon CloudWatch metric to determine how many hours a model has run for and the number of inference units used during those hours.

Note

If you only have one model in an AWS region, you can also get the running time for the model by tracking successful calls to StartprojectVersion and StopProjectVersion in CloudWatch. This approach doesn't work if you run more that one model in the AWS Region as the metrics don't include information about the model.

Alternatively, you can use AWS CloudTrail to track calls to StartProjectVersion and StopProjectVersion (which includes the model ARN in the requestParameters field of the event history). CloudTrail events are limited to 90 days, but you can store events for up to 7 years in a CloudTrail Lake.

The following procedure creates graphs for the following:

  • The number of hours that a model has run for.

  • The number of inference units that a model has used.

You can choose a time period up to 15 months in the past. For more information about metric retention, see Metrics retention.

To determine model duration and inference units used for a model

  1. Sign in to the AWS Management Console and open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.

  2. In the left navigation pane, choose All metrics under Metrics.

  3. In the content pane, choose the Source tab.

  4. Make sure that the Dashboard button is selected.

  5. In the edit box, replace the existing JSON with the following JSON. Change the following values:

    • Project_Name — The project that contains the model that you want to graph.

    • Version_Name — The version of the model that you want to graph.

    • AWS_Region — The AWS Region that contains the model. Make sure that the CloudWatch console is in the same AWS Region, by checking the Region selector in the navigation bar at the top of the page. Update as necessary.

    {
    "sparkline": true,
    "metrics": [
        [
            {
                "expression": "SUM(m1)*m1",
                "label": "Inference units used",
                "id": "e1"
            }
        ],
        [
            {
                "expression": "DATAPOINT_COUNT(m1)*m1/m1",
                "label": "Hours running",
                "id": "e2"
            }
        ],
        [
            "AWS/Rekognition",
            "InServiceInferenceUnits",
            "ProjectName",
            "Project_Name",
            "VersionName",
            "Version_Name",
            {
                "id": "m1",
                "visible": false
            }
        ]
    ],
    "view": "singleValue",
    "stacked": false,
    "region": "AWS_Region",
    "stat": "Average",
    "period": 3600,
    "title": "Hours run and inference units used"
}

  6. Choose Update.

  7. At the top of the page, choose a timeline. You should see numbers for inference units used and hours running during the timeline. Gaps in the graph indicate times when the model wasn't running. The screenshot of the console below showing inference units used and hours running over time periods, with a custom time of 2 weeks set, with the highest values of 214 inference units and 209 hours running.

    Graph showing inference units.

  8. (Optional) Add the graph to a dashboard by choosing Actions and then Add to dashboard - improved.