java 45 lines · 8 steps

Instrumenting orders with Micrometer in Spring

A Spring service records order metrics using Micrometer counters, summaries, timers, and gauges.

Explained by highlit
Spring Intermediate metrics micrometer observability dependency-injection generics
1@Service
2public class OrderMetricsService {
3 
4 private final MeterRegistry registry;
5 private final Counter placedOrders;
6 private final Counter failedOrders;
7 
8 public OrderMetricsService(MeterRegistry registry) {
9 this.registry = registry;
10 this.placedOrders = Counter.builder("orders.placed")
11 .description("Number of successfully placed orders")
12 .baseUnit("orders")
13 .register(registry);
14 this.failedOrders = Counter.builder("orders.failed")
15 .description("Number of orders that failed to process")
16 .register(registry);
17 }
18 
19 public void recordPlaced(Order order) {
20 placedOrders.increment();
21 registry.summary("orders.value", "currency", order.getCurrency())
22 .record(order.getTotal().doubleValue());
23 registry.counter("orders.items", "channel", order.getChannel())
24 .increment(order.getItemCount());
25 }
26 
27 public void recordFailed(String reason) {
28 failedOrders.increment();
29 registry.counter("orders.failed.reasons", "reason", reason).increment();
30 }
31 
32 public <T> T timeCheckout(String paymentProvider, Supplier<T> checkout) {
33 return Timer.builder("orders.checkout.duration")
34 .tag("provider", paymentProvider)
35 .publishPercentiles(0.5, 0.95, 0.99)
36 .register(registry)
37 .record(checkout);
38 }
39 
40 public void trackPending(Supplier<Number> pendingCount) {
41 Gauge.builder("orders.pending", pendingCount)
42 .description("Orders awaiting fulfillment")
43 .register(registry);
44 }
45}
01 / 01
STEP 01

Walkthrough

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Three takeaways
  1. 1Register hot-path counters once at construction and reuse them, but build tagged metrics on demand to avoid cardinality explosions from unbounded tag values.
  2. 2Different metric types answer different questions: counters count events, summaries track value distributions, timers measure latency, and gauges sample live state.
  3. 3A gauge holds a reference to a supplier rather than a value, so it re-reads the current state each time metrics are scraped.

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