Metrics

Purpose: Define trace-based metrics from your query results. This node packages your data into a TraceMetricV2TemplateSpec proto that can be exported and used in trace analysis pipelines. Each value column becomes a separate metric, and all remaining columns become dimensions.

How to use:

1. Connect an input: This node requires a source of data (e.g., from a Table Source or after filtering/aggregating data)

2. Set Metric ID Prefix: Give your metric a unique identifier prefix (e.g., cpu_metrics, memory_usage). Each metric is named <prefix>_<column_name>.

3. Drag columns to Values: The panel shows two lists — Dimensions on the left and Values on the right.

   • Drag any numeric column (int, double, etc.) from Dimensions to Values to make it a metric value.
   • Drag a value column back to Dimensions (or click ✕) to remove it.
   • Use the "Add value column" dropdown at the bottom of the Values panel as an alternative to drag-and-drop.

4. Configure each Value column: For each value column in the Values panel, set:

   • Unit: The appropriate unit (Count, Time, Bytes, Percentage, etc.). Use "Custom" to enter a custom unit string.
   • Polarity: Whether higher or lower values are "better":
     • Higher is Better: e.g., throughput, cache hit rate
     • Lower is Better: e.g., latency, error count
     • Not Applicable: when direction doesn't matter

5. Configure Dimension Uniqueness: Specify whether dimension combinations are unique:

   • Unique: Each combination of dimension values appears at most once
   • Not Unique: The same dimension combination may appear multiple times

Dimensions: All columns not in the Values list automatically become dimensions. Use a Modify Columns node before this one to control which columns are present.

Export: Click the "Export" button to generate a textproto representation of your metric template specification. A preview table shows the metric values as they would appear in an actual trace. When there are multiple value columns, each has its own tab in the preview.

Example workflow:

1. Start with a Table Source (e.g., slice table)
2. Add Aggregation to compute SUM(dur) and COUNT(*) grouped by process_name
3. Add a Metrics node:
   • Metric ID Prefix: slice_stats
   • Drag sum_dur to Values → Unit: Time (nanoseconds), Polarity: Lower is Better
   • Drag count to Values → Unit: Count, Polarity: Not Applicable
4. Export the metric spec

This creates two metrics — slice_stats_sum_dur and slice_stats_count — both with process_name as a dimension.

Output: The node passes through input columns unchanged. The metric template specification is generated separately via the Export button.