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Monitoring performance data in the console

To view real time performance data, make sure that your app uses a Performance Monitoring SDK version that's compatible with real time data processing. Learn more.

Track key metrics in your dashboard

To learn how your key metrics are trending, add them to your metrics board at the top of the Performance dashboard. You can quickly identify regressions by seeing week-over-week changes or verify that recent changes in your code are improving performance.

an image of the metrics board in the Firebase Performance Monitoring dashboard

Here are some example trends that you could track:

  • An improvement in first input delay as you've changed when your app loads certain JavaScript files
  • A decrease in the time for first contentful paint after switching to use a CDN for assets
  • A drop in response payload size for a network request since you implemented the use of thumbnails
  • An increase in network response time for a third-party API call during an ecosystem outage

Each member of a Firebase project can configure their own metrics board. You can track metrics that are important to you, while other project members can track completely different sets of key metrics on their own boards.

To add a metric to your metrics board, go to the Performance dashboard in the Firebase console, then click the Dashboard tab. Click an empty metric card, then select an existing metric to add to your board. Click on a populated metric card for more options, like to replace or remove a metric.

The metrics board shows collected metric data over time, both in graphical form and as a numerical percentage change.

  • Each metric card displays the percentage change in the metric's value over the selected time range, as well as the metric's most recently collected value. The statement at the top of the metrics board is an interpretation of the percentage change.
  • By default, the metrics board displays the metric's median value. If you'd like to view how different segments of your users experience your app, select a different percentile from the dropdown at the top of the dashboard page.

What do the red, green, and grey colors mean?

Most metrics have a desired trending direction, so the metrics board uses color to display an interpretion of whether the metric's data is trending in a good or bad direction.

For example, say you're tracking a page's first input delay (a value that should be small). If this value is increasing, then the metrics board displays the metric's percentage change in red, calling attention to a possible issue. However, if the value is decreasing or unchanged, then the metrics board displays the percentage in green or grey, respectively.

If a metric doesn't have an obvious desired trending direction, like the response payload size for a network request, then the metrics board always displays the metric's percentage change in grey, regardless of how the data is trending.

What do the solid and dashed lines mean?

  • dark blue solid line — the metric's value over time

  • light blue dashed line — the metric's value at a specific time in the past
    For example, if you select to show a chart of the last 7 days, and you hover over August 30, then the light blue dashed line tells you the metric's value on August 23.

View traces and their data

You can view all traces for your app in the traces table, which is at the bottom of the Performance dashboard. The table groups each type of trace within an appropriate subtab. For example, all network request traces are listed under the Network requests subtab.

The traces table displays the values for some top metrics for each trace, along with the percentage change for each metric's value. These values are calculated based on the selections of percentile and time range set at the top of the Dashboard tab. Here are some examples:

  • If you select a percentile of 50% and a time range of Last 7 days, then the metric's value will be the median of collected data from the most recent day, and the percentage change will be the change since 7 days prior.

  • If you then change the time range to Last 24 hours, then the metric's value will be the median of collected data from the most recent hour, and the percentage change will be the change since 24 hours prior.

You can sort the list of traces in each subtab by the metric's value or by the percentage change for a specific metric. This can help you quickly identify potential problems in your app.

To view all the metrics and data for a specific trace, click the trace name in the traces table. The following sections of this page provide more details.

View more data for a specific trace

If you click a trace name in the traces table, you can then click through various screens to explore the trace and drill down into metrics of interest. On most pages, you can use the Filter button (top-left of the screen) to filter the data by attribute, for example:

an image of Firebase Performance Monitoring data being filtered by attribute
  • Filter by Page URL to view data for a specific page of your site
  • Filter by Effective connection type to learn how a 3g connection impacts your app
  • Filter by Country to make sure your database location isn't affecting a specific region

View all collected metrics for a trace

If you click a trace name in the traces table, you'll see an overview of the trace's data on metric cards.

Use the options in the top-right of the screen to view the data in aggregate or over time.

  • Network request traces — The available metric cards are response time and response payload size.
  • Custom code traces — The Duration metric card is always available (the default metric for this type of trace). If you added any custom metrics to a custom code trace, those metric cards are also shown.
  • Page load traces — The available metric cards include first paint, first contentful paint, first input delay, and DOM-related events.

View in-depth information about the data

If you click View more on any metric card, you can review more in-depth information about the collected data and use richer analysis features. For example, you can filter and segment the data by attribute.