CAS Metrics

CAS via Spring Boot registers the following core metrics when applicable:

JVM metrics, report utilization of:

  • Various memory and buffer pools
  • Statistics related to garbage collection
  • Threads utilization
  • Number of classes loaded/unloaded
  • CPU metrics
  • File descriptor metrics
  • Logback metrics: record the number of events logged to Logback at each level
  • Uptime metrics: report a gauge for uptime and a fixed gauge representing the application’s absolute start time
  • Tomcat metrics
  • Spring Integration metrics

Support is enabled by including the following module in the Overlay:

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<dependency>
     <groupId>org.apereo.cas</groupId>
     <artifactId>cas-server-support-metrics</artifactId>
     <version>${cas.version}</version>
</dependency>

Auto-configuration enables the instrumentation of all available DataSource objects with a metric named jdbc. Data source instrumentation results in gauges representing the currently active, maximum allowed, and minimum allowed connections in the pool. Each of these gauges has a name that is prefixed by jdbc. Metrics are also tagged by the name of the DataSource computed based on the bean name. Also, Hikari-specific metrics are exposed with a hikaricp prefix. Each metric is tagged by the name of the Pool.

Auto-configuration enables the instrumentation of all available Caches on startup with metrics prefixed with cache. Cache instrumentation is standardized for a basic set of metrics. Additional, cache-specific metrics are also available.

Auto-configuration will enable the instrumentation of all available RabbitMQ connection factories with a metric named rabbitmq.

CAS Metrics are accessed and queried using the CAS actuator admin endpoints. Navigating to the endpoint displays a list of available meter names. You can drill down to view information about a particular meter by providing its name as a selector.

See this guide to learn more.

Custom Metrics

To register custom metrics, inject MeterRegistry into your component, as shown in the following example:

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public class Dictionary {
    private final List<String> words = new CopyOnWriteArrayList<>();

    Dictionary(final MeterRegistry registry) {
        registry.gaugeCollectionSize("dictionary.size", Tags.empty(), this.words);
    }
}

If you find that you repeatedly instrument a suite of metrics across components or applications, you may encapsulate this suite in a MeterBinder implementation. By default, metrics from all MeterBinder beans will be automatically bound to the Spring-managed MeterRegistry.

Customizing Metrics

If you need to apply customizations to specific Meter instances you can use the io.micrometer.core.instrument.config.MeterFilter interface. By default, all MeterFilter beans will be automatically applied to the micrometer MeterRegistry.Config.

For example, if you want to rename the mytag.region tag to mytag.area for all meter IDs beginning with com.example, you can do the following:

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@Bean
public MeterFilter renameRegionTagMeterFilter() {
    return MeterFilter.renameTag("com.example", "mytag.region", "mytag.area");
}

Storage

CAS metrics may be routed to varying types of databases for storage and analytics. The following options are available:

  • Simple (In Memory)
  • Graphite
  • Ganglia
  • JMX
  • Atlas
  • Signal FX
  • Statsd
  • InfluxDb
  • Prometheus
  • Wavefront
  • New Relic
  • CloudWatch
  • …

To see the relevant list of CAS properties, please review this guide.