Telemetry
Explore

Filter, aggregate, and visualize a table without starting from blank SQL

Explore gives operators and product teams a fast path from event fields to samples, tables, lines, bars, and stacked areas while keeping the generated query visible.

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Outcomes

  • Validate new instrumentation with exact sample rows.
  • Build common time-series views with filters and aggregations.
  • Hand the generated SQL to a deeper analysis when the question outgrows the controls.

How it works

A reviewable workflow from signal to decision

1

Inspect samples first

Confirm that fields contain the expected values and types before aggregating them. This catches instrumentation mistakes early.

2

Choose the metric and grain

Select the aggregation, numeric field, time bucket, and filters that match the question. Keep incomplete newest buckets in mind.

3

Promote useful views

Add the result to a dashboard or alert when it becomes part of a recurring workflow. Use Query for multi-table and multi-CTE logic.

Capabilities

What is included

Samples and table views for raw event inspection
Line, bar, and stacked-area charts
Count, sum, average, min, max, and percentile aggregations
Time ranges, nested-field filters, split series, and explicit columns
Add-to-dashboard and create-alert actions from results

Documentation

Quick start and ExploreCreating dashboardsCreating alerts

See the analysis

SQL recipes that use this capability

Calculate API Error Rate by Route

Use SQL to rank API routes by 5xx error rate while protecting the result from low-volume noise.

Open recipe

Measure Background Job Retry and Failure Rate

Find unreliable jobs by comparing successful runs, retries, failures, and tail duration.

Open recipe

Calculate LLM Cost by Feature and Model

Attribute model spend, tokens, request volume, and cost per request to product features.

Open recipe

Start with one production workflow

Use a focused prompt, send synthetic events, and verify the first useful query before expanding coverage.

Open prompt pack