docs: add example query for HTTP requests duration per percentile (#103)

Co-authored-by: Marcelo Trylesinski <marcelotryle@gmail.com>

docs/integrations/use_cases/web_frameworks.md

@@ -41,3 +41,34 @@ To replace the `Authorization` header value with `[REDACTED]` to avoid leaking u
 ```
 OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS="Authorization"
 ```
+
+## Query HTTP requests duration per percentile
+
+It's usually interesting to visualize HTTP requests duration per percentile. Instead of having an average, which may be influenced by extreme values, percentiles allow us know the maximum duration for 50%, 90%, 95% or 99% of the requests.
+
+Here is a sample query to compute those percentiles for HTTP requests duration:
+
+```sql
+WITH dataset AS (
+  SELECT
+    time_bucket('%time_bucket_duration%', start_timestamp) AS x,
+    (extract(epoch from end_timestamp - start_timestamp) * 1000) as duration_ms
+  FROM records
+  WHERE attributes ? 'http.method'
+)
+SELECT
+  x,
+  percentile_cont(0.99) WITHIN GROUP (ORDER BY duration_ms) as percentile_99,
+  percentile_cont(0.95) WITHIN GROUP (ORDER BY duration_ms) as percentile_95,
+  percentile_cont(0.90) WITHIN GROUP (ORDER BY duration_ms) as percentile_90,
+  percentile_cont(0.50) WITHIN GROUP (ORDER BY duration_ms) as percentile_50
+FROM dataset
+GROUP BY x
+ORDER BY x DESC;
+```
+
+Notice how we filtered on records that have the `http.method` attributes set. It's a good starting point to retrieve traces that are relevant for HTTP requests, but depending on your setup, you might need to add more filters.
+
+This query is a good candidate for a Time Series chart in a dashboard:
+
+![Requests duration per percentile as Time Series chart](../../images/integrations/use_cases/web_frameworks/logfire-screenshot-chart-percentiles.png)