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Micrometer to OpenTelemetry Bridge
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//// | ||
This guide is maintained in the main Quarkus repository | ||
and pull requests should be submitted there: | ||
https://github.com/quarkusio/quarkus/tree/main/docs/src/main/asciidoc | ||
//// | ||
[id=telemetry-micrometer-opentelemetry] | ||
= Micrometer and OpenTelemetry extension | ||
include::_attributes.adoc[] | ||
:extension-status: preview | ||
:diataxis-type: reference | ||
:categories: observability | ||
:summary: Guide to send Micrometer data to OpenTelemetry. | ||
:topics: observability,opentelemetry,metrics,micrometer,tracing,logs | ||
:extensions: io.quarkus:quarkus-micrometer-opentelemetry | ||
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This extension provides support for both Micrometer and OpenTelemetry in Quarkus applications. It streamlines integration by incorporating both extensions along with a bridge that enables sending Micrometer metrics via OpenTelemetry. | ||
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include::{includes}/extension-status.adoc[] | ||
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[NOTE] | ||
==== | ||
- The xref:telemetry-micrometer.adoc[Micrometer Guide] is available for detailed information about the Micrometer extension. | ||
- The xref:opentelemetry.adoc[OpenTelemetry Guide] provides information about the OpenTelemetry extension. | ||
==== | ||
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The extension allows the normal use of the Micrometer API, but have the metrics handled by the OpenTelemetry extension. | ||
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As an example, the `@Timed` annotation from Micrometer is used to measure the execution time of a method: | ||
[source,java] | ||
---- | ||
import io.micrometer.core.annotation.Timed; | ||
//... | ||
@Timed(name = "timer_metric") | ||
public String timer() { | ||
return "OK"; | ||
} | ||
---- | ||
The output telemetry data is handled by the OpenTelemetry SDK and sent by the `quarkus-opentelemetry` extension exporter using the OTLP protocol. | ||
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This reduces the overhead of having an independent Micrometer registry plus the OpenTelemetry SDK in memory for the same application when both `quarkus-micrometer` and `quarkus-opentelemetry` extensions are used independently. | ||
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*The OpenTelemetry SDK will handle all metrics.* Either Micrometer metrics (manual or automatic) and OpenTelemetry Metrics can be used. All are available with this single extension. | ||
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All the configurations from the OpenTelemetry and Micrometer extensions are available with `quarkus-micrometer-opentelemetry`. | ||
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The bridge is more than the simple OTLP registry found in Quarkiverse. In this extension, the OpenTelemetry SDK provides a Micrometer registry implementation based on the https://github.com/open-telemetry/opentelemetry-java-instrumentation/tree/main/instrumentation/micrometer/micrometer-1.5/library[`micrometer/micrometer-1.5`] OpenTelemetry instrumentation library. | ||
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== Usage | ||
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If you already have your Quarkus project configured, you can add the `quarkus-micrometer-opentelemetry` extension to your project by running the following command in your project base directory: | ||
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:add-extension-extensions: micrometer-opentelemetry | ||
include::{includes}/devtools/extension-add.adoc[] | ||
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This will add the following to your build file: | ||
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[source,xml,role="primary asciidoc-tabs-target-sync-cli asciidoc-tabs-target-sync-maven"] | ||
.pom.xml | ||
---- | ||
<dependency> | ||
<groupId>io.quarkus</groupId> | ||
<artifactId>quarkus-micrometer-opentelemetry</artifactId> | ||
</dependency> | ||
---- | ||
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[source,gradle,role="secondary asciidoc-tabs-target-sync-gradle"] | ||
.build.gradle | ||
---- | ||
implementation("io.quarkus:quarkus-micrometer-opentelemetry") | ||
---- | ||
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== Configuration | ||
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When the extension is present, Micrometer is enabled by default as are OpenTelemetry tracing, metrics and logs. | ||
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OpenTelemetry metrics auto-instrumentation for HTTP server and JVM metrics are disabled by default because those metrics can be collected by Micrometer. | ||
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Specific automatic Micrometer metrics are all disabled by default and can be enabled by setting, for example in the case of JVM metrics: | ||
[source,properties] | ||
---- | ||
quarkus.micrometer.binder.jvm=true | ||
---- | ||
in the `application.properties` file. | ||
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For this and other properties you can use with the extension, Please refer to: | ||
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* xref:telemetry-micrometer.adoc#configuration-reference[Micrometer metrics configuration properties] | ||
* xref:opentelemetry.adoc#configuration-reference[OpenTelemetry configuration properties] | ||
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== Metric differences between Micrometer and OpenTelemetry | ||
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=== API differences | ||
The metrics produced with each framework follow different APIs and the mapping is not 1:1. | ||
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One fundamental API difference is that Micrometer uses a https://docs.micrometer.io/micrometer/reference/concepts/timers.html[Timer] and OpenTelemetry uses a https://opentelemetry.io/docs/specs/otel/metrics/data-model/#histogram[Histogram] to record latency (execution time) metrics and the frequency of the events. | ||
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When using the `@Timed` annotation with Micrometer, 2 different metrics are https://github.com/open-telemetry/opentelemetry-java-instrumentation/blob/324fdbdd452ddffaf2da2c5bf004d8bb3fdfa1dd/instrumentation/micrometer/micrometer-1.5/library/src/main/java/io/opentelemetry/instrumentation/micrometer/v1_5/OpenTelemetryTimer.java#L31[created on the OpenTelemetry side], one `Gauge` for the `max` value and one `Histogram`. | ||
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The `DistributionSummary` from Micrometer is transformed into a `Histogram` and a `DoubleGauge` for the `max` value. If service level objectives (slo) are set to `true` when creating a `DistributionSummary`, an additional histogram is created for them. | ||
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This table shows the differences between the two frameworks: | ||
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|=== | ||
|Micrometer |OpenTelemetry | ||
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|DistributionSummary | ||
|`<Metric name>` (Histogram), `<Metric name>.max` (DoubleGauge) | ||
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|DistributionSummary with SLOs | ||
|`<Metric name>` (Histogram), `<Metric name>.max` (DoubleGauge), `<Metric name>.histogram` (DoubleGauge) | ||
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|LongTaskTimer | ||
|`<Metric name>.active` (ObservableLongUpDownCounter), `<Metric name>.duration` (ObservableDoubleUpDownCounter) | ||
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|Timer | ||
|`<Metric name>` (Histogram), `<Metric name>.max` (ObservableDoubleGauge) | ||
|=== | ||
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=== Semantic convention differences | ||
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The 2 frameworks follow different semantic conventions. The OpenTelemetry Metrics are based on the https://opentelemetry.io/docs/concepts/semantic-conventions/[OpenTelemetry Semantic Conventions] and are still under active development (early 2025). Micrometer metrics convention format is around for a long time and has not changed much. | ||
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When these 2 configurations are set in the `application.properties` file: | ||
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[source,properties] | ||
---- | ||
quarkus.micrometer.binder.jvm=true | ||
quarkus.micrometer.binder.http-server.enabled=true | ||
---- | ||
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The JVM and HTTP server metrics are collected by Micrometer. | ||
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Next, are examples of the metrics collected by Micrometer and a comparison of what would be the `quarkus-micrometer-registry-prometheus` output vs the one on this bridge. A link to the equivalent OpenTelemetry Semantic Convention is also provided for reference and is not currently used in the bridge. | ||
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|=== | ||
|Micrometer Meter |Quarkus Micrometer Prometheus output | This bridge OpenTelemetry output name | Related OpenTelemetry Semantic Convention (not applied) | ||
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|Using the @Timed interceptor. | ||
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|method.timed (Histogram), method.timed.max (DoubleGauge) | ||
|NA | ||
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|Using the @Counted interceptor. | ||
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|method.counted (DoubleSum) | ||
|NA | ||
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|`http.server.active.requests` (Gauge) | ||
|`http_server_active_requests` (Gauge) | ||
|`http.server.active.requests` (DoubleGauge) | ||
|https://opentelemetry.io/docs/specs/semconv/http/http-metrics/#metric-httpserveractive_requests[`http.server.active_requests`] (UpDownCounter) | ||
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|`http.server.requests` (Timer) | ||
|`http_server_requests_seconds_count`, `http_server_requests_seconds_sum`, `http_server_requests_seconds_max` (Gauge) | ||
|`http.server.requests` (Histogram), `http.server.requests.max` (DoubleGauge) | ||
|https://opentelemetry.io/docs/specs/semconv/http/http-metrics/#metric-httpserverrequestduration[`http.server.request.duration`] (Histogram) | ||
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|`http.server.bytes.read` (DistributionSummary) | ||
|`http_server_bytes_read_count`, `http_server_bytes_read_sum` , `http_server_bytes_read_max` (Gauge) | ||
|`http.server.bytes.read` (Histogram), `http.server.bytes.read.max` (DoubleGauge) | ||
|https://opentelemetry.io/docs/specs/semconv/http/http-metrics/#metric-httpserverrequestbodysize[`http.server.request.body.size`] (Histogram) | ||
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|`http.server.bytes.write` (DistributionSummary) | ||
|`http_server_bytes_write_count`, `http_server_bytes_write_sum` , `http_server_bytes_write_max` (Gauge) | ||
|`http.server.bytes.write` (Histogram), `http.server.bytes.write.max` (DoubleGauge) | ||
|https://opentelemetry.io/docs/specs/semconv/http/http-metrics/#metric-httpserverresponsebodysize[`http.server.response.body.size`] (Histogram) | ||
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|`http.server.connections` (LongTaskTimer) | ||
|`http_server_connections_seconds_active_count`, `http_server_connections_seconds_duration_sum` `http_server_connections_seconds_max` (Gauge) | ||
|`http.server.connections.active` (LongSum), `http.server.connections.duration` (DoubleGauge) | ||
| N/A | ||
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|`jvm.threads.live` (Gauge) | ||
|`jvm_threads_live_threads` (Gauge) | ||
|`jvm.threads.live` (DoubleGauge) | ||
|https://opentelemetry.io/docs/specs/semconv/runtime/jvm-metrics/#metric-jvmthreadcount[`jvm.threads.live`] (UpDownCounter) | ||
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|`jvm.threads.started` (FunctionCounter) | ||
|`jvm_threads_started_threads_total` (Counter) | ||
|`jvm.threads.started` (DoubleSum) | ||
|https://opentelemetry.io/docs/specs/semconv/runtime/jvm-metrics/#metric-jvmthreadcount[`jvm.threads.live`] (UpDownCounter) | ||
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|`jvm.threads.daemon` (Gauge) | ||
|`jvm_threads_daemon_threads` (Gauge) | ||
|`jvm.threads.daemon` (DoubleGauge) | ||
|https://opentelemetry.io/docs/specs/semconv/runtime/jvm-metrics/#metric-jvmthreadcount[`jvm.threads.live`] (UpDownCounter) | ||
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|`jvm.threads.peak` (Gauge) | ||
|`jvm_threads_peak_threads` (Gauge) | ||
|`jvm.threads.peak` (DoubleGauge) | ||
|N/A | ||
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|`jvm.threads.states` (Gauge per state) | ||
|`jvm_threads_states_threads` (Gauge) | ||
|`jvm.threads.states` (DoubleGauge) | ||
|https://opentelemetry.io/docs/specs/semconv/runtime/jvm-metrics/#metric-jvmthreadcount[`jvm.threads.live`] (UpDownCounter) | ||
|=== | ||
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[NOTE] | ||
==== | ||
Some metrics might be missing from the output if they contain no data. | ||
==== | ||
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== See the output | ||
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=== Grafana-OTel-LGTM Dev Service | ||
You can use the xref:observability-devservices-lgtm.adoc[Grafana-OTel-LGTM] Dev Service. | ||
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This Dev Service includes Grafana for visualizing data, Loki to store logs, Tempo to store traces and Prometheus to store metrics. | ||
It also provides an OTel collector to receive the data | ||
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=== Logging exporter | ||
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You can output all metrics to the console by setting the exporter to `logging` in the `application.properties` file: | ||
[source, properties] | ||
---- | ||
quarkus.otel.metrics.exporter=logging <1> | ||
quarkus.otel.metric.export.interval=10000ms <2> | ||
---- | ||
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<1> Set the exporter to `logging`. | ||
Normally you don't need to set this. | ||
The default is `cdi`. | ||
<2> Set the interval to export the metrics. | ||
The default is `1m`, which is too long for debugging. | ||
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Also add this dependency to your project: | ||
[source,xml] | ||
---- | ||
<dependency> | ||
<groupId>io.opentelemetry</groupId> | ||
<artifactId>opentelemetry-exporter-logging</artifactId> | ||
</dependency> | ||
---- |
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