Update readme

Author: monodot

README.md

@@ -4,6 +4,8 @@ This demo app shows how a Spring Boot application can expose a Prometheus metric
 
 🚼 The app was initially created with [Spring Initializr][init] and then by following the [RESTful service tutorial on spring.io][rest-tutorial].
 
+## To run
+
 To run the app:
 
     mvn clean spring-boot:run
@@ -24,6 +26,19 @@ This will expose Prometheus metrics at `/actuator/prometheus`. This is a simple
     tomcat_sessions_alive_max_seconds 0.0
     ...    
 
+## Timing a custom method
+
+The method in the application which responds to the REST request has been annotated with `@Timed`, so Micrometer will capture the execution time of this method:
+
+```java
+@GetMapping("/greeting")
+@Timed(value = "greeting.time", description = "Time taken to return greeting",
+        percentiles = {0.5, 0.90})
+public Greeting greeting(@RequestParam(value = "name", defaultValue = "World") String name) {
+    return new Greeting(counter.incrementAndGet(), String.format(template, name));
+}
+```
+
 Once you make a request to the service at <http://localhost:8080/greeting>, you will also see a new metric exposed, `greeting_time_seconds` exposed, which shows the execution time of the `greeting` method:
 
     # HELP greeting_time_seconds Time taken to return greeting
@@ -43,6 +58,8 @@ From the [Micrometer docs][timerdocs]:
 
 > All implementations of _Timer_ report at least the total time and count of events as separate time series.
 
+## Getting metrics into Prometheus
+
 Now we need to get these metrics into Prometheus.
 
 In another terminal, use Podman to start an ephemeral Prometheus in a container, and use the `host` networking option, which will allow the container to access the Spring Boot app on `localhost`: