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Copy file name to clipboardExpand all lines: _versions/main/guides/command-mode-reference.adoc
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----
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=== Mocking
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=== Limitations
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`@QuarkusMainTest` does **not** support the following features:
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- Injection of CDI beans
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- Using Panache entities
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- Using mocks with `@InjectMock`
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Usually, it's best to use a combination of `@QuarkusMainTest` tests for testing application externals, and `@QuarkusTest` tests for fine-grained testing which requires access to application internals.
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==== Mocking
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CDI injection is not supported in the `@QuarkusMainTest` tests.
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Consequently, mocking CDI beans with `QuarkusMock` or `@InjectMock` is not supported either.
WARNING: In situations where all that is needed to build a container image and no push to a registry is necessary (essentially by having set `quarkus.container-image.build=true` and left `quarkus.container-image.push` unset - it defaults to `false`), then this extension creates a container image and registers
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To use this feature, add the following extension to your project.
The `quarkus-container-image-docker` extension is capable of https://docs.docker.com/buildx/working-with-buildx/#build-multi-platform-images/[creating multi-platform (or multi-arch)] images using https://docs.docker.com/engine/reference/commandline/buildx_build/[`docker buildx build`]. See the `quarkus.docker.buildx.*` configuration items in the <<#DockerOptions,Docker Options>> section below.
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To use this feature, add the following extension to your project.
NOTE: When using the buildpack container image extension it is strongly advised to avoid adding `quarkus.container-image.build=true` in your properties configuration as it might trigger nesting builds within builds. It's preferable to pass it as an option to the build command instead.
Copy file name to clipboardExpand all lines: _versions/main/guides/opentelemetry-metrics.adoc
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Using an unbounded set of dimensional data (many different values like a userId) can lead to a "cardinality explosion", an exponential increase in the creation of new time series.
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Avoid!
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OpenTelemetry provides many other types of Counters: `LongUpDownCounter`, `DoubleCounter`, `DoubleUpDownCounter` and also Observable, async counters like `ObservableLongCounter`, `ObservableDoubleCounter`, `ObservableLongUpDownCounter` and `ObservableDoubleUpDownCounter`.
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OpenTelemetry provides many other types of Counters: `LongUpDownCounter`, `DoubleCounter`, `UpDownCounter`, `DoubleUpDownCounter` and also Observable, async counters like `ObservableLongCounter`, `ObservableDoubleCounter`, `ObservableLongUpDownCounter` and `ObservableDoubleUpDownCounter`.
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For more details please refer to the https://opentelemetry.io/docs/languages/java/instrumentation/#using-counters[OpenTelemetry Java documentation about Counters].
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For more details please refer to the https://opentelemetry.io/docs/languages/java/api/#counter[OpenTelemetry Java documentation about Counters].
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=== Gauges
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Observable Gauges should be used to measure non-additive values.
Copy file name to clipboardExpand all lines: _versions/main/guides/rest.adoc
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The link:{jdkapi}/java/util/concurrent/CompletionStage.html[`CompletionStage`] return
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type is also supported.
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==== Request cancellation
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Async endpoints that return `Uni` support request cancellation, which means that if the underlying HTTP connection is closed for whatever reason,
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the request pipeline defined by the returned `Uni` is also cancelled. This can be very useful in avoiding unnecessary work on the server
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when the client isn't going to use the response anyway.
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If instead of cancelling the pipeline, it should be completed regardless of the state of the HTTP connection, Quarkus REST provides the `org.jboss.resteasy.reactive.server.Cancellable` annotation
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which can be applied to REST classes or methods to control the cancellation behavior.
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=== Streaming support
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If you want to stream your response element by element, you can make your endpoint method return a
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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Next, are examples of the metrics collected by Micrometer compared with what would be the `quarkus-micrometer-registry-prometheus` endpoint output (`/q/metrics`) vs the OTLP protocol output on this bridge.
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A link to the equivalent OpenTelemetry Semantic Convention is also provided for reference and is not currently used by the bridge.
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.Micrometer metrics output comparison. Prometheus registry vs. OpenTelemetry bridge
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|===
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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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|Micrometer Meter Java definition |Quarkus Micrometer Prometheus output (as seen at `/q/metrics/`) | This bridge OpenTelemetry output name (as seen in the OTLP output) | Related OpenTelemetry Semantic Convention (not applied)
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|Using the @Timed interceptor.
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|Using the xref:telemetry-micrometer#create-a-timer[@Timed] interceptor.
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