1. Event contract
One row in api_requests, with the types used by the query made explicit.
- timestamp_utc
- Timestamp
- route_template
- Utf8
- status_code
- Int64
- latency_ms
- Float64
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.
Exploring structured events
A real product capture moving from event samples to filters, aggregation, and a visual result.
Boundaries
What this does not replace
- Explore is optimized for one-table investigation; joins, several CTEs, and reusable analytical definitions belong in Query.
- A chart cannot compensate for incomplete instrumentation, mixed units, or unstable route and event names.
- High-cardinality raw identifiers are better used for restricted drill-down than as top-level chart dimensions.
Inspectable proof path
From event contract to a visible answer
This example uses a declared schema, read-only SQL, and deterministic synthetic results. It demonstrates the workflow without presenting sample data as a customer benchmark.
2. Read-only SQL
Which API routes have the highest meaningful 5xx error rate?
SELECT
route_template,
COUNT(*) AS requests,
SUM(CASE WHEN status_code >= 500 THEN 1 ELSE 0 END) AS errors,
100.0 * SUM(CASE WHEN status_code >= 500 THEN 1 ELSE 0 END)
/ NULLIF(COUNT(*), 0) AS error_rate_pct
FROM api_requests
WHERE timestamp_utc >= now() - INTERVAL '24 hours'
GROUP BY route_template
HAVING COUNT(*) >= 20
ORDER BY error_rate_pct DESC
LIMIT 10;3. Synthetic result
The checkout route is the clearest reliability risk even though search has more total traffic.
| route_template | requests | errors |
|---|---|---|
| /api/checkout | 25 | 5 |
| /api/search | 25 | 1 |
| /api/profile | 20 | 0 |
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
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 recipeMeasure Background Job Retry and Failure Rate
Find unreliable jobs by comparing successful runs, retries, failures, and tail duration.
Open recipeCalculate LLM Cost by Feature and Model
Attribute model spend, tokens, request volume, and cost per request to product features.
Open recipeCustomer evidence
How teams use this workflow
“Telemetry is one of the easiest ways to go from dumping in your data to actually understanding it.”
Shayan Taslim, LogSnag
Review the documented workflow“Telemetry makes it super easy to track, analyze, and visualize what's going on in my business. It's the perfect mix of simple and powerful.”
Namu Kang, Browserflow
Review the documented workflowRelated capabilities
Continue the event-to-decision workflow
Shared dashboards
Keep operational and product signals readable in one shared view
Explore capabilityThreshold alerts
Notify people when a queryable signal moves outside its expected range
Explore capabilityAI agent monitoring
Monitor AI agent cost, tool use, and outcomes with structured events
Explore capabilityStart with one production workflow
Use a focused prompt, send synthetic events, and verify the first useful query before expanding coverage.