Row grain
One terminal request outcome before grouping by route template.
Decision supported
Prioritize an endpoint for release comparison, dependency inspection, or rollback review.
Metric contract
Put the denominator and units beside the chart
Adapt these names to your contract while preserving the declared grain. Inspect the linked event schema before mapping fields from production producers.
- Request volume
- Error rate
- p50 latency
- p95 latency
p95 ms
Demonstration data, not a customer result or benchmark
Review the query before adapting the fields
This public query is a starting definition. Add a bounded time filter, complete-bucket policy, environment, and minimum volume appropriate to your production event contract.
SELECT
endpoint,
COUNT(*) AS requests,
ROUND(
100.0 * SUM(CASE WHEN status = 'error' THEN 1 ELSE 0 END)
/ NULLIF(COUNT(*), 0),
2
) AS error_rate_pct,
approx_percentile_cont(latency_ms, 0.50) AS p50_ms,
approx_percentile_cont(latency_ms, 0.95) AS p95_ms
FROM api_requests
GROUP BY endpoint
ORDER BY error_rate_pct DESC, requests DESC;Prove these before publishing the result
- Endpoint values are bounded route templates rather than raw URLs.
- Latency uses one end-to-end millisecond definition across producers.
- Operational charts omit the newest incomplete time bucket.
Checks that keep the dashboard trustworthy
- Add a bounded time filter before using this query in production.
- Keep request volume beside every percentile and rate.
- Segment by release and error type after detecting a regression.
Interpretation boundary
What this result cannot prove by itself
Always show request count beside a percentile. A high p95 from a tiny group is not equivalent to broad customer impact.
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