Analyze Ingestion Volume in SigNoz

This guide walks you through identifying which signal, service, and environment is responsible for your ingestion volume, so you know where to focus before making any changes.

Step 1: Import the Cost Meter Dashboard

The Cost Meter module (accessible from the sidebar under Cost Meter) is built into SigNoz, no import required. The Cost Meter Dashboard Template below is a separate importable JSON dashboard that provides a service- and environment-level breakdown not available in the built-in module. Use the built-in module for a quick overview; import this template when you need to drill down by service or environment.

Navigate to Dashboards > New Dashboard > Import JSON and import our official template:

Cost Meter Dashboard Template

Set your timeframe (e.g., Last 1 week) to match the time period you are investigating.
Review the breakdown of volumes by signal.
Review the breakdown by service.name and deployment.environment.
Conclusion: e.g., "Traces generated by the payment-worker service in the Production environment is the highest driver."

Metrics: Use Sample Count, Not Size: When reviewing metrics cost in the Cost Meter Dashboard, focus on the sample count panel (signoz.meter.metric.datapoint.count). Metric ingestion in SigNoz is measured by sample count, not bytes. Size-based panels in the dashboard apply to logs and traces only.

Step 2: Drill Down with the Ingestion Analysis Dashboard

For a granular breakdown of ingestion by individual metric names, span operation names, and log severities, import the Ingestion Analysis Dashboard.

This dashboard provides more granularity than the Cost Meter Dashboard. For example, it identifies which specific span operation or metric name within a service is responsible for the volume.

15-Minute Window: The Ingestion Analysis Dashboard shows only the last 15 minutes of data. If you are investigating a historical time window, this dashboard does not cover it. Use the Explorers below.

Historical Analysis via Explorers

If the Ingestion Analysis Dashboard does not cover the time window you need, use native Explorers. Pick the option below matching the signal you're investigating.

Option A: Historical Logs

Navigate to Logs and swap to the Table tab. If the Cost Meter Dashboard identified a specific service, filter by service.name and deployment.environment. Group by severity_text over your target timeframe to see if DEBUG or INFO lines are dominating the output.

Sorting by count surfaces the highest-frequency severity or operation, not necessarily the highest byte volume. A lower-count group with larger average payloads (for example, verbose stack traces) can outweigh a higher-count group of short lines. Cross-check candidates against the Cost Meter Dashboard's GB breakdown before committing to a fix.

Logs Explorer grouped by severity_text showing log count per severity level — *Logs Explorer: group by severity_text to identify which log levels dominate volume*

Option B: Historical Traces

Navigate to Traces > Trace Explorer and swap to the Table tab. Filter by your target environment/service, group by name (the span's operation name), and sort by total count. This reveals which span operations are generating the highest volume.

Trace Explorer table view grouped by span operation name showing count per operation — *Trace Explorer: group by name and sort by count to find the highest-volume span operations*

Option C: Historical Metrics

Navigate to Metrics > Metrics Explorer. The list view shows all ingested metrics with their sample count and time series count.

Set the aggregate to Samples and select your target time window.
Sort by sample count. This shows which metric names are consuming the most samples and by how much.

Metrics Explorer list view sorted by sample count — *Metrics Explorer: sort by sample count to identify the highest-volume metrics*

Next Steps

Once you have identified the highest-volume metric, trace route, or log stream driving the noise, proceed directly to the matching execution guide:

Get Help

If you need help with the steps in this topic, please reach out to us on SigNoz Community Slack. If you are a SigNoz Cloud user, please use in product chat support located at the bottom right corner of your SigNoz instance or contact us at cloud-support@signoz.io.