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+# Dtail Metrics Example
+
+This page walks through using Epimetheus watch mode with a CSV that could come from a tool like [Dtail](https://dtail.dev/) or any similar log/aggregation export.
+
+## Scenario
+
+You have a CSV file (e.g. `dtail.csv`) with columns that mix numeric stats and identifiers (host, service, etc.). You want to turn those into Prometheus metrics so you can graph them in Grafana.
+
+## Steps
+
+1. **Ensure the CSV has a header row**  
+   First line = column names. Epimetheus will sanitize them for use as metric names and labels.
+
+2. **Identify numeric vs string columns**  
+   - Numeric columns (e.g. `count`, `avg_latency_ms`, `p99`) become metric values.
+   - String columns (e.g. `host`, `service`, `region`) become labels.
+
+3. **Run watch mode** with a base metric name and your Prometheus (or Prometheus-compatible) write URL:
+
+   ```bash
+   ./epimetheus -mode=watch \
+       -file=dtail.csv \
+       -metric-name=dtail \
+       -prometheus=http://localhost:9090/api/v1/write
+   ```
+
+4. **Optional: resolve IPs to hostnames**  
+   If one of your label columns contains IPs (e.g. `host` or `ip`), you can resolve them:
+
+   ```bash
+   ./epimetheus -mode=watch \
+       -file=dtail.csv \
+       -metric-name=dtail \
+       -prometheus=http://localhost:9090/api/v1/write \
+       -resolve-ip-labels=host
+   ```
+
+5. **Query in Prometheus / Grafana**  
+   Metrics will appear as `dtail_<column_name>` with your string columns as labels, e.g.:
+
+   ```promql
+   dtail_avg_latency_ms{service="api", region="eu"}
+   ```
+
+## References
+
+- [CSV Format Flexibility](csv-format-flexibility.md) – how column types and names are interpreted.
+- [DNS Resolution](dns-resolution.md) – IP-to-hostname resolution.
+- [Operating Modes](modes.md) – all watch mode options.