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JMX 🔗

The Splunk Distribution of OpenTelemetry Collector uses the Smart Agent receiver with the jmx monitor type to run an arbitrary Groovy script to convert JMX MBeans fetched from a remote Java application to SignalFx data points. This is a more flexible alternative to the GenericJMX monitor.

You can use the following utility helpers in the Groovy script within the util variable, which is set in the script’s context:

  • util.queryJMX(String objectName): This helper queries the pre-configured JMX application for the given objectName, which can include wildcards. In any case, the return value will be a List of zero or more GroovyMBean objects, which are a convenience wrapper that Groovy provides to make accessing attributes on the MBean simple. See http://groovy-lang.org/jmx.html for more information about the GroovyMBean object. You can use the Groovy .first() method on the returned list to access the first MBean is you are only expecting one.

  • util.makeGauge(String name, double val, Map<String, String> dimensions): A convenience function to create a SignalFx gauge data point. This creates a DataPoint instance that can be fed to output.sendDatapoint[s]. This does not send the data point, only creates it.

  • util.makeCumulative(String name, double val, Map<String, String> dimensions): A convenience function to create a SignalFx cumulative counter data point. This creates a DataPoint instance that can be fed to output.sendDatapoint[s]. This does not send the data point, it only creates it.

The output instance available in the script context is used to send data to Observability Cloud. It contains the following methods:

  • output.sendDatapoint(DataPoint dp): Emit the given data point to SignalFx. Use the util.make[Gauge|Cumulative] helpers to create the DataPoint instance.

  • output.sendDatapoints(List<DataPoint> dp): Emit the given data points to SignalFx. We recommend using the util.make[Gauge|Cumulative] helpers to create the DataPoint instance. It’s slightly more efficient to send multiple data points at once, but this doesn’t matter that much unless you’re sending very high volumes of data.

Benefits 🔗

After you configure the integration, you can access these features:

  • View metrics. You can create your own custom dashboards, and most monitors provide built-in dashboards as well. For information about dashboards, see View dashboards in Observability Cloud.

  • View a data-driven visualization of the physical servers, virtual machines, AWS instances, and other resources in your environment that are visible to Infrastructure Monitoring. For information about navigators, see Splunk Infrastructure Monitoring navigators.

  • Access the Metric Finder and search for metrics sent by the monitor. For information, see Use the Metric Finder.

Installation 🔗

Follow these steps to deploy this integration:

  1. Deploy the Splunk Distribution of OpenTelemetry Collector to your host or container platform:

  2. Configure the monitor, as described in the Configuration section.

  3. Restart the Splunk Distribution of OpenTelemetry Collector.

Configuration 🔗

To use this integration of a Smart Agent monitor with the Collector:

  1. Include the Smart Agent receiver in your configuration file.

  2. Add the monitor type to the Collector configuration, both in the receiver and pipelines sections.

Example 🔗

To activate this integration, add the following to your Collector configuration:

receivers:
  smartagent/jmx:
    type: jmx
    ...  # Additional config

Next, add the monitor to the service > pipelines > metrics > receivers section of your configuration file:

service:
  pipelines:
    metrics:
      receivers: [smartagent/jmx]

Configuration settings 🔗

The following table shows the configuration options for this integration:

Option

Required

Type

Description

host

no

string

Host will be filled in by auto-discovery if this monitor has a discovery rule.

port

no

integer

Port will be filled in by auto-discovery if this monitor has a discovery rule. (default: 0)

serviceURL

no

string

The service URL for the JMX RMI/JMXMP endpoint. If empty it will be filled in with values from host and port using a standard JMX RMI template: service:jmx:rmi:///jndi/rmi://<host>:<port>/jmxrmi. If overridden, host and port will have no effect. For JMXMP endpoint the service URL must be specified. The JMXMP endpoint URL format is service:jmx:jmxmp://<host>:<port>.

groovyScript

yes

string

A literal Groovy script that generates data points from JMX MBeans. See the top-level jmx monitor doc for more information on how to write this script. You can put the Groovy script in a separate file and refer to it here with ${include:/<my_path>/jmx.groovy}. For more information on using the include config, see https://github.com/signalfx/splunk-otel-collector/tree/main/internal/configsource/includeconfigsource. Or, you can put it straight in YAML by using the | block indicator.

username

no

string

Username for JMX authentication, if applicable.

password

no

string

Password for JMX authentication, if applicable.

keyStorePath

no

string

The key store path is required if client authentication is activated on the target JVM.

keyStorePassword

no

string

The key store file password if required.

keyStoreType

no

string

The key store type. (default: jks)

trustStorePath

no

string

The trusted store path if the TLS profile is required.

trustStorePassword

no

string

The trust store file password if required.

jmxRemoteProfiles

no

string

Supported JMX remote profiles are TLS in combination with SASL profiles: SASL/PLAIN, SASL/DIGEST-MD5 and SASL/CRAM-MD5. Thus valid jmxRemoteProfiles values are: SASL/PLAIN, SASL/DIGEST-MD5, SASL/CRAM-MD5, TLS SASL/PLAIN, TLS SASL/DIGEST-MD5 and TLS SASL/CRAM-MD5.

realm

no

string

The realm is required by profile SASL/DIGEST-MD5.

The following is an example Groovy script that replicates some of the data presented by the Cassandra nodetool status utility:

// Query the JMX endpoint for a single MBean.
ss = util.queryJMX("org.apache.cassandra.db:type=StorageService").first()

// Copied and modified from https://github.com/apache/cassandra
def parseFileSize(String value) {
	if (!value.matches("\\d+(\\.\\d+)? (GiB|KiB|MiB|TiB|bytes)")) {
		throw new IllegalArgumentException(
			String.format("value %s is not a valid human-readable file size", value));
	}
	if (value.endsWith(" TiB")) {
		return Math.round(Double.valueOf(value.replace(" TiB", "")) * 1e12);
	}
	else if (value.endsWith(" GiB")) {
		return Math.round(Double.valueOf(value.replace(" GiB", "")) * 1e9);
	}
	else if (value.endsWith(" KiB")) {
		return Math.round(Double.valueOf(value.replace(" KiB", "")) * 1e3);
	}
	else if (value.endsWith(" MiB")) {
		return Math.round(Double.valueOf(value.replace(" MiB", "")) * 1e6);
	}
	else if (value.endsWith(" bytes")) {
		return Math.round(Double.valueOf(value.replace(" bytes", "")));
	}
	else {
		throw new IllegalStateException(String.format("FileUtils.parseFileSize() reached an illegal state parsing %s", value));
	}
}

localEndpoint = ss.HostIdToEndpoint.get(ss.LocalHostId)
dims = [host_id: ss.LocalHostId, cluster_name: ss.ClusterName]

output.sendDatapoints([
	// Equivalent of "Up/Down" in the `nodetool status` output.
	// 1 = Live; 0 = Dead; -1 = Unknown
	util.makeGauge(
		"cassandra.status",
		ss.LiveNodes.contains(localEndpoint) ? 1 : (ss.DeadNodes.contains(localEndpoint) ? 0 : -1),
		dims),

	util.makeGauge(
		"cassandra.state",
		ss.JoiningNodes.contains(localEndpoint) ? 3 : (ss.LeavingNodes.contains(localEndpoint) ? 2 : 1),
		dims),

	util.makeGauge(
		"cassandra.load",
		parseFileSize(ss.LoadString),
		dims),

	util.makeGauge(
		"cassandra.ownership",
		ss.Ownership.get(InetAddress.getByName(localEndpoint)),
		dims)
	])

Make sure that your script is carefully tested before using it to monitor a production JMX service. In general, scripts should only read attributes, but nothing enforces that.

Metrics 🔗

There are no metrics available for this integration.

Troubleshooting 🔗

If you are not able to see your data in Splunk Observability Cloud, try these tips:

To learn about even more support options, see Splunk Customer Success.