Model monitoring metrics

Generative AI on Vertex AI provides a prebuilt model observability dashboard to view the behavior, health, and performance of fully-managed models. Fully-managed models, also known as Model as a Service (MaaS), are provided by Google and include Google's Gemini models and partner models with managed endpoints. Metrics from self-hosted models aren't included in the dashboard.

Generative AI on Vertex AI automatically collects and reports activity from MaaS models to help you quickly troubleshoot latency issues and monitor capacity.

A sample model observability dashboard in the Cloud Console — ^{Model observability dashboard example}

Available monitoring metrics

The model observability dashboard displays a subset of metrics that are collected by Cloud Monitoring, such as model request per second (QPS), token throughput, and first token latencies. View the dashboard to see all the available metrics.

Use case

As an application developer, you can view how your users are interacting with the models that you've exposed. For example, you can view how model usage (model requests per second) and the compute intensity of user prompts (model invocation latencies) are trending over time. Consequently, because these metrics are related to model usage, you can also estimate costs for running each model.

When an issue arises, you can quickly troubleshoot from the dashboard. You can check if models are responding reliably and in a timely manner by viewing API error rates, first token latencies, and token throughput.

Limitations

Vertex AI captures dashboard metrics only for API calls to a model's endpoint. Google Cloud console usage, such as metrics from Vertex AI Studio, aren't added to the dashboard.

View the dashboard

In the Vertex AI section of the Google Cloud console, go to the Dashboard page.

Go to Vertex AI
In the Model observability section, click Show all metrics to view the model observability dashboard in the Google Cloud Observability console.

Note: The observability section is available only if you or another user has made API calls to a MaaS model in your project.
To view metrics for a specific model or in a particular location, set one or more filters at the top of the dashboard page.

For descriptions of each metric, see the "aiplatform" section on the Google Cloud metrics page.

Additional resources

To create alerts for your dashboard, see the Alerting overview page in the Monitoring documentation.
For information about metrics data retention, see the Monitoring quotas and limits.
For information about data at rest, see Protecting data at rest.
To view a list of all metrics that Cloud Monitoring collects, see the "aiplatform" section on the Google Cloud metrics page.