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Enhancements for MicroProfile Metrics and a new training course in 24.0.0.7

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David Mueller on Jul 16, 2024
announcements , microprofile , release , metrics , community , developer-experience ,
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The 24.0.0.7 release includes enhancements for histogram and timer metrics in MicroProfile 3.0 and 4.0. Also, a new beginner-level training course is now available to teach you the essentials of cloud-native Java application development with Open Liberty.

In Open Liberty 24.0.0.7:

View the list of fixed bugs in 24.0.0.7.

Check out previous Open Liberty GA release blog posts.

Develop and run your apps using 24.0.0.7

If you’re using Maven, include the following in your pom.xml file:

<plugin>
    <groupId>io.openliberty.tools</groupId>
    <artifactId>liberty-maven-plugin</artifactId>
    <version>3.10.3</version>
</plugin>

Or for Gradle, include the following in your build.gradle file:

buildscript {
    repositories {
        mavenCentral()
    }
    dependencies {
        classpath 'io.openliberty.tools:liberty-gradle-plugin:3.8.3'
    }
}
apply plugin: 'liberty'

Or if you’re using container images:

FROM icr.io/appcafe/open-liberty

Or take a look at our Downloads page.

If you’re using IntelliJ IDEA, Visual Studio Code or Eclipse IDE, you can also take advantage of our open source Liberty developer tools to enable effective development, testing, debugging, and application management all from within your IDE.

Ask a question on Stack Overflow

Enhanced histogram and timer metrics in MicroProfile 3.0 and 4.0

This release introduces MicroProfile Config properties for MicroProfile 3.0 and 4.0 that are used for configuring the statistics that are tracked and outputted by the histogram and timer metrics. These changes are already available in MicroProfile Metrics 5.1.

In previous MicroProfile Metrics 3.0 and 4.0 releases, histogram and timer metrics tracked only the following values:

  • Min/max recorded values

  • The sum of all values

  • The count of the recorded values

  • A static set of percentiles for the 50th, 75th, 95th, 98th, 99th, and 99.9th percentile.

These values are output to the /metrics endpoint in Prometheus format.

The new properties can define a custom set of percentiles as well as custom set of histogram buckets for the histogram and timer metrics. Other new configuration properties can enable a default set of histogram buckets, including properties that define an upper and lower bound for the bucket set.

With these properties, you can define a semicolon-separated list of value definitions that use the following syntax:

<metric name>=<value-1>[,<value-2>...<value-n>]

Some properties can accept multiple values for a given metric name, while others can accept only a single value.

You can use an asterisk (*) as a wildcard at the end of the metric name.

Property

Description

mp.metrics.distribution.percentiles

Defines a custom set of percentiles for matching Histogram and Timer metrics to track and output. Accepts a set of integer and decimal values for a metric name pairing. Can be used to disable percentile output if no value is provided with a metric name pairing.

mp.metrics.distribution.histogram.buckets

Defines a custom set of (cumulative) histogram buckets for matching Histogram metrics to track and output. Accepts a set of integer and decimal values for a metric name pairing.

mp.metrics.distribution.timer.buckets

Defines a custom set of (cumulative) histogram buckets for matching Timer metrics to track and output. Accepts a set of decimal values with a time unit appended (ms, s, m, or h, for example) for a metric name pairing.

mp.metrics.distribution.percentiles-histogram.enabled

Configures any matching Histogram or Timer metric to provide a large set of default histogram buckets to allow for percentile configuration with a monitoring tool. Accepts a true/false value for a metric name pairing.

mp.metrics.distribution.histogram.max-value

When percentile-histogram is enabled for a Timer, this property defines an upper bound for the buckets reported. Accepts a single integer or decimal value for a metric name pairing.

mp.metrics.distribution.histogram.min-value

When percentile-histogram is enabled for a Timer, this property defines a lower bound for the buckets reported. Accepts a single integer or decimal value for a metric name pairing.

mp.metrics.distribution.timer.max-value

When percentile-histogram is enabled for a Histogram, this property defines an upper bound for the buckets reported. Accepts a single decimal value with a time unit appended (ms, s, m, or h, for example) for a metric name pairing.

mp.metrics.distribution.timer.min-value

When percentile-histogram is enabled for a Histogram, this property defines a lower bound for the buckets reported. Accepts a single decimal value with a time unit appended (ms, s, m, or h, for example) for a metric name pairing.

You can define the mp.metrics.distribution.percentiles property similar to the following example.

mp.metrics.distribution.percentiles=alpha.timer=0.5,0.7,0.75,0.8;alpha.histogram=0.8,0.85,0.9,0.99;delta.*=

This property creates the alpha.timer timer metric to track and output the 50th, 70th, 75th, and 80th percentile values. The alpha.histogram histogram metric outputs the 80th, 85th, 90th, and 99th percentile values. Percentiles for any histogram or timer metric that matches with delta.* are disabled.

We’ll expand on this example and define histogram buckets for the alpha.timer timer metric by using the mp.metrics.distribution.timer.buckets property.

mp.metrics.distribution.timer.buckets=alpha.timer=100ms,200ms,1s

This configuration tells the metrics runtime to track and output the count of durations that fall within 0-100ms, 0-200ms and 0-1 seconds. This output is due to the histogram buckets working in a cumulative fashion.

The corresponding prometheus output for the alpha.timer metric at the /metrics REST endpoint is similar to the following example:

# TYPE application_alpha_timer_mean_seconds gauge
application_alpha_timer_mean_seconds 2.9700022497975187
# TYPE application_alpha_timer_max_seconds gauge
application_alpha_timer_max_seconds 5.0
# TYPE application_alpha_timer_min_seconds gauge
application_alpha_timer_min_seconds 1.0
# TYPE application_alpha_timer_stddev_seconds gauge
application_alpha_timer_stddev_seconds 1.9997750210918204
# TYPE alpha_timer_seconds histogram (1)
application_alpha_timer_seconds_bucket{le="0.1"} 0.0 (2)
application_alpha_timer_seconds_bucket{le="0.2"} 0.0 (2)
application_alpha_timer_seconds_bucket{le="1.0"} 1.0 (2)
application_alpha_timer_seconds_bucket{le="+Inf"} 2.0 (2) (3)
application_alpha_timer_seconds_count 2
application_alpha_timer_seconds_sum 6.0
application_alpha_timer_seconds{quantile="0.5"} 1.0
application_alpha_timer_seconds{quantile="0.7"} 5.0
application_alpha_timer_seconds{quantile="0.75"} 5.0
application_alpha_timer_seconds{quantile="0.8"} 5.0
1 The Prometheus metric type is histogram. Both the quantiles/percentile and buckets are represented under this type.
2 The le tag represents less than and is for the defined buckets, which are converted to seconds.
3 Prometheus requires that a +Inf bucket counts all hits.

Learn to develop applications with Open Liberty in the new "Essentials for Cloud-Native Java Application Development" course

The Essentials for Cloud-Native Java Application Development course is published on the cognitiveclass.ai site.

This course teaches you the essential skills and technologies to create a basic cloud-native Java application with Open Liberty. You’ll learn about REST applications, contexts and dependency injection (CDI), externalizing application configuration, and more. If you score 80% or higher on the final quiz (20 multiple-choice questions), you’ll receive the Liberty Developer Essentials badge from Credly.

Get Open Liberty 24.0.0.7 now

Available through Maven, Gradle, Docker, and as a downloadable archive.