💄 Trunk fmt

docs/metrics-analysis-prometheus/collected-reported-metrics.md

@@ -108,6 +108,7 @@ cost = (cost_per_flavor + cost_per_storage) * cost_of_bandwidth / 100
 ```
 
 !!! note
+
     GCP and AWS costs are quite the same for the same flavors.
 
 ### The different tags and their associated cost
@@ -128,6 +129,7 @@ cost = (cost_per_flavor + cost_per_storage) * cost_of_bandwidth / 100
 | GCP      | `n2-standard-8`      | 0.01             |
 
 !!! note
+
     Please note that the names of large GitHub hosted runners
     may not be explicitly the same as shown below, but this is
     the naming convention recommended by GitHub.

docs/metrics-analysis-prometheus/prometheus.md

@@ -45,10 +45,11 @@ within a specified time range.
    repositories with a value greater than zero.
 
 !!! info
-   Using Grafana enhances the visualization of Prometheus data and
-   provides powerful querying capabilities. Within Grafana, apply filters,
-   combine queries, and utilize variables for dynamic filtering. It's important
-   to understand `__interval` (time interval between data points) and `__range`
-   (selected time range) when working with Prometheus data in Grafana. This
-   integration enables efficient data exploration and analysis for better
-   insights and decision-making.
+
+      Using Grafana enhances the visualization of Prometheus data and
+      provides powerful querying capabilities. Within Grafana, apply filters,
+      combine queries, and utilize variables for dynamic filtering. It's important
+      to understand `__interval` (time interval between data points) and `__range`
+      (selected time range) when working with Prometheus data in Grafana. This
+      integration enables efficient data exploration and analysis for better
+      insights and decision-making.