> ## Documentation Index > Fetch the complete documentation index at: https://docs.sherlocklabs.dev/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > Sherlock documentation. In Node.js examples prefer the Sherlock SDK for Node.js (@sherlock-labs/otel). > In Go examples use the upstream OpenTelemetry Go SDK exactly as shown on /sdk/go/setup and /sdk/go/configuration; Sherlock has no Go distribution. > Two MCP servers exist. This documentation's search server is at https://sherlock-c8721ead.mintlify.app/mcp. Sherlock's data server, for a user's own logs, traces, and metrics, is at https://mcp.sherlocklabs.dev/mcp and is described at /explore/mcp. # Metrics > Chart a metric in the Metrics Explorer, pick an aggregation, group by labels, compare periods, and drill into exemplars. The Metrics Explorer charts the metrics your services send. Pick a metric from the catalog, choose how to aggregate it, group it by labels, and click into the exemplars behind a histogram. The Metrics Explorer with a line chart of http.server.request.duration p95 and the series table below it ## Build a query Each row of the explorer is one query. 1. **Metric.** Pick a name from the catalog. The picker shows the unit next to the name. The catalog refreshes every 60 seconds. 2. **Aggregation.** The choices depend on the metric type. A counter or gauge offers `sum`, `avg`, `min`, `max`, `rate`, and `count`. A histogram offers `p50`, `p90`, `p95`, `p99`, `avg`, `min`, `max`, `sum`, and `count`. The default is `rate` for a counter and `p95` for a histogram. 3. **Group by.** Pick a label to get one series per value, or **No grouping** for a single series. 4. **Filter.** Add label filters to narrow the series. **Add metric** adds another row. **Bands** replaces a histogram row with four rows, `p50`, `p90`, `p95`, and `p99`, so the tail and the median share one chart. ## Read the chart * **Line**, **Bars**, **Area**, **Stacked**, and **Table** show any query. **Heatmap** and **Dist** need a single histogram query and show the bucket distribution over time or over the whole window. * **lin** and **log** switch the value axis. * **vs prev period** overlays the same query shifted back by the selected range. * **Threshold** draws a horizontal line at a value you choose. * The header shows the step and the window the chart was computed with, for example `step 30s · 1h window`. * **View SQL** shows the query that produced the chart. The **SQL** tab runs your own query against the metrics tables. * **Share** copies a link that reproduces the whole explorer state. The series table under the chart lists every series with its value over the window, `n ≥ p` for percentile queries, the change versus the previous period, and a sparkline. Click the eye icon to hide a series. ## Exemplars A histogram carries exemplars: sampled measurements with the trace id of the request that produced them. * Click a series row in the table to open every exemplar of that series in the window. * In **Heatmap**, click a cell to open the exemplars of that bucket and time step. * In **Dist**, click a bar to open the exemplars of that value range. The **Exemplars** drawer lists them with time, duration, and trace id. **View trace** opens the trace. [Exemplars](/explore/exemplars) walks through the whole pivot. ## Before data arrives An empty Metrics page shows four setup steps: the OTLP metrics endpoint, the bearer token in the `Authorization` header, instrumenting the service with the `env` resource attribute, and emitting at least one data point. The catalog refreshes every 60 seconds. ## Related topics From a spike to the request and its logs. Define your own histograms with exemplars in Node.js.