Step : Create a Metric Dashboard and Chart

Now that you’ve sent metrics to Lightstep, it’s time to build a dashboard and chart to monitor that data.

Run Your Service or App

The first step is to run your app so that it starts generating metrics you can see immediately in Lightstep. Let it run for a few minutes before you start building the dashboard.

Create a Metric Dashboard

Dashboards contain charts that are built on queries of your metric data.

1. From the navigation bar, click Dashboards.

2. Click Create a dashboard.

3. Click Create a Metrics dashboard from the modal. A new blank dashboard displays.

4. Click in the title to rename your dashboard.

   You’re now ready to add a chart to the dashboard.

Add a Metric Chart

1. In your dashboard, click Add a Chart.

2. In the Chart Builder window, click into the title to name your chart.

3. Build the query for your chart

   • Search for a metric to plot: Click into the search field. Lightstep displays all metrics that it’s currently ingesting. Choose one, or to search, start typing the name of a metric. Lightstep starts auto-completing to match available metrics.

     

     Click the info icon to view and edit the metric’s details (like the description or units) in the details panel.

     When you select a metric, Lightstep expands the query builder and begins to chart the metric.

   • Choose an operator for the data:

     Lightstep automatically configures the operator for distribution type metrics. If the distribution is a gauge, the operator is set to latest. If it is a counter (delta or cumulative), the operator is set to rate by default, but you can change it to count.

     • Latest: Graphs the latest value in a time series for a point in time.

     The latest operator can only be used with gauge-type metrics.

     • Count: Computes and graphs the total number of increments as whole numbers. Counts are most useful for infrequent events and are best visualized as stacked bar charts.

     • Rate: Graphs the number of operations per second. Rates are most useful for ongoing operations and are best visualized as line charts.

       For example, this chart uses Count and shows there are a total of 364.474 requests at 11:45 am.

       This chart has the same query but uses Rate, and shows there are 8.099 requests per second at 11:45 am.

   • Compute percentiles (distribution type metrics only): When the metric data is a distribution type (a set of values for each point in time), Lightstep can compute the 50th, 90th, 99th, and 99.9th percentiles for you.

     For existing Lightstep customers interested in tracking distribution metrics, please opt-in here. For new customers to Lightstep, this feature is already enabled in your account.

     You can control the percentiles displayed on the chart using the display toggles.

     

   • Filter the data: By default, all data for the metric is displayed. You can filter the data using metric tags found on the data. You can include or exclude data with a given tag and value. You can add more than one tag to a filter where it makes sense (Lightstep prunes the available list as you add tags).

   Multiple selections use AND to join filters.

   Change Intelligence works best when it can focus on a single service and its dependencies. If your query includes metrics coming from many services, use filters to choose one service to focus on.

   

   By default, Lightstep displays tags that it’s seen in the last three days. But you can type in a tag not in the dropdown and Lightstep will find it.

   • Group the data: By default, Lightstep aggregates the data from the metric into one line.

     Instead, you can show lines for each available tag value (group by). Select a tag to display lines for each of the tag’s values. In this example, by choosing to group by the method tag, you can see the metrics for the individual tag values.

     Grouping isn’t available on big number charts.

   • Aggregation method: Choose how you want the data aggregated into the chart.

     • Count (non-null): The number of values found that are not null. For example, given the values of [10, 15, null, 50] the count is 3.
       • Count (non-zero): The number of values found that are not zero (null is counted). For example, given the values of [10, 15, null, 0 50] the count is 4.
       • Mean: The average (sum of the data divided by the count) of the data.
         For example, given the values of [10, 15, 50] the mean is 25.
       • Min: The lowest point in the data.
         For example, given the values of [10, 15, 50] the min is 10.
       • Max: The highest point in the data.
         For example, given the values of [10, 15, 50] the max is 50.
       • Sum: The total of all points in the data.
         For example, given the values of [10, 15, 50] the sum is 75.

Distribution type metrics are automatically summed and then aggregated into percentiles.

1. Click Save to save your changes. The chart now displays on the dashboard.

You can add as many charts as you need for the dashboard.

Now that you have your metric data reporting and displayed in Lightstep, it’s time to see how that data and data from trace instrumentation work together to find root causes of metric deviations deep in your stack.

What Did We Learn?

• Dashboards can contain any number of charts.
• Charts are built from queries to your metric data. You can aggregate, filter, and group that data so that the chart reports just the data you need.