Micrometer Adapter¶

Declare the DefaultsMeterBinderListProvider as a component¶

The Micrometer has an interface called MeterBinder (external site) .

The collection of frequently used metrics, such as JVM memory usage and CPU usage, is provided in advance as a class that implements this interface. (e.g., JvmMemoryMetrics (external site) for JVM memory usage and ProcessorMetrics (external site) for CPU usage)

DefaultMeterBinderListProvider is a class that provides this MeterBinder (external site) list , which can be used to collect metrics such as JVM memory usage and CPU usage.

First, add this DefaultMeterBinderListProvider declaration to src/main/resources/web-component-configuration.xml .

<component name="meterBinderListProvider"
           class="nablarch.integration.micrometer.DefaultMeterBinderListProvider" />

For a specific description of the metrics that are collected, see Metrics collected by the DefaultMeterBinderListProvider .

Target the DefaultsMeterBinderListProvider for disposal¶

Because the DefaultMeterBinderListProvider is a component that needs to be disposed of, declare it for disposal as follows.

<component name="disposer"
    class="nablarch.core.repository.disposal.BasicApplicationDisposer">

  <property name="disposableList">
    <list>
      <component-ref name="meterBinderListProvider"/>
    </list>
  </property>

</component>

For the object disposal process, see Handling the disposal of objects .

Declare the registry’s factory class as a component¶

<component class="nablarch.integration.micrometer.logging.LoggingMeterRegistryFactory">
  <property name="meterBinderListProvider" ref="meterBinderListProvider" />
  <property name="applicationDisposer" ref="disposer" />
</component>

Next, declare the factory class as a component, which is provided for each registry to be used.

In doing so, configure two properties, meterBinderListProvider and applicationDisposer . For each property, configure DefaultMeterBinderListProvider and BasicApplicationDisposer as declared above.

The factory classes provided by this adapter are listed in Registry factory .

Creating a configuration file¶

Finally, create a text file named micrometer.properties under src/main/resources .

Describe the contents as follows.

# Output metrics every 5 seconds (1 minute in default)
nablarch.micrometer.logging.step=5s
# Configuring to output log at disposal process
# even if the application is terminated earlier than the time specified in step.
nablarch.micrometer.logging.logInactive=true

Execution Result¶

Now you can collect metrics using the LoggingMeterRegistry .

Launching the application, can see that the collected metrics are output to standard output as follows

2020-09-04 15:33:40.689 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.gc.count{memory.manager.name=PS Scavenge} throughput=2.6/s
2020-09-04 15:33:40.690 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.gc.count{memory.manager.name=PS MarkSweep} throughput=0.4/s
2020-09-04 15:33:40.691 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.buffer.count{id=mapped} value=0 buffers
2020-09-04 15:33:40.691 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.buffer.count{id=direct} value=2 buffers
2020-09-04 15:33:40.692 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.buffer.memory.used{id=direct} value=124 KiB
2020-09-04 15:33:40.692 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.buffer.memory.used{id=mapped} value=0 B
2020-09-04 15:33:40.692 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.buffer.total.capacity{id=mapped} value=0 B
2020-09-04 15:33:40.692 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.buffer.total.capacity{id=direct} value=124 KiB
2020-09-04 15:33:40.693 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.classes.loaded{} value=9932 classes
2020-09-04 15:33:40.693 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.gc.live.data.size{} value=0 B
2020-09-04 15:33:40.693 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.gc.max.data.size{} value=2.65918 GiB
2020-09-04 15:33:40.694 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.committed{area=heap,id=PS Old Gen} value=182.5 MiB
2020-09-04 15:33:40.694 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.committed{area=heap,id=PS Survivor Space} value=44 MiB
2020-09-04 15:33:40.694 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.committed{area=heap,id=PS Eden Space} value=197 MiB
2020-09-04 15:33:40.694 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.committed{area=nonheap,id=Code Cache} value=29.125 MiB
2020-09-04 15:33:40.694 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.committed{area=nonheap,id=Compressed Class Space} value=6.796875 MiB
2020-09-04 15:33:40.695 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.committed{area=nonheap,id=Metaspace} value=55.789062 MiB
2020-09-04 15:33:40.695 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.max{area=heap,id=PS Old Gen} value=2.65918 GiB
2020-09-04 15:33:40.695 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.max{area=heap,id=PS Survivor Space} value=44 MiB
2020-09-04 15:33:40.696 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.max{area=nonheap,id=Code Cache} value=240 MiB
2020-09-04 15:33:40.696 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.max{area=nonheap,id=Metaspace} value=-1 B
2020-09-04 15:33:40.696 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.max{area=heap,id=PS Eden Space} value=1.243652 GiB
2020-09-04 15:33:40.696 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.max{area=nonheap,id=Compressed Class Space} value=1 GiB
2020-09-04 15:33:40.697 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.used{area=nonheap,id=Code Cache} value=28.618713 MiB
2020-09-04 15:33:40.697 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.used{area=nonheap,id=Compressed Class Space} value=6.270714 MiB
2020-09-04 15:33:40.697 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.used{area=nonheap,id=Metaspace} value=54.118324 MiB
2020-09-04 15:33:40.698 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.used{area=heap,id=PS Old Gen} value=69.320663 MiB
2020-09-04 15:33:40.698 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.used{area=heap,id=PS Survivor Space} value=7.926674 MiB
2020-09-04 15:33:40.698 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.memory.used{area=heap,id=PS Eden Space} value=171.750542 MiB
2020-09-04 15:33:40.698 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.threads.daemon{} value=28 threads
2020-09-04 15:33:40.698 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.threads.live{} value=29 threads
2020-09-04 15:33:40.699 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.threads.peak{} value=31 threads
2020-09-04 15:33:40.702 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.threads.states{state=blocked} value=0 threads
2020-09-04 15:33:40.703 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.threads.states{state=runnable} value=9 threads
2020-09-04 15:33:40.703 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.threads.states{state=new} value=0 threads
2020-09-04 15:33:40.703 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.threads.states{state=timed-waiting} value=3 threads
2020-09-04 15:33:40.703 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.threads.states{state=terminated} value=0 threads
2020-09-04 15:33:40.704 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: jvm.threads.states{state=waiting} value=17 threads
2020-09-04 15:33:41.199 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: process.cpu.usage{} value=0.111672
2020-09-04 15:33:41.199 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: process.start.time{} value=444222h 33m 14.544s
2020-09-04 15:33:41.199 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: process.uptime{} value=26.729s
2020-09-04 15:33:41.200 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: system.cpu.count{} value=8
2020-09-04 15:33:41.200 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: system.cpu.usage{} value=0.394545

Placement¶

Create a configuration file for this adapter to be placed directly under the classpath with the name micrometer.properties .

Format¶

Describe it in the following format

nablarch.micrometer.<subPrefix>.<key>=<value>

The value specified for <subPrefix> is different for each registry factory used.

For each registry factory, the following table lists the values to specify for <subPrefix>.

<key> should be the same name as the method defined in configuration class (external site) that Micrometer provides per registry.

For example, there is a configuration class named DatadogConfig (external site) for DatadogMeterRegistry (external site) . And in this configuration class, a method named apiKey (external site) is defined.

Therefore, can configure your apiKey by writing in your micrometer.properties like this.

nablarch.micrometer.datadog.apiKey=XXXXXXXXXXXXXXXXXXXX

Override with OS environment variables or system properties¶

The configuration values in micrometer.properties can be overridden by OS environment variables or system properties.

The configuration values are adopted in the following order of priority.

1. The value specified in system properties
2. Value specified in OS environment variables
3. Configuration values for micrometer.properties

For example, suppose you have the following conditions set.

micrometer.properties

nablarch.micrometer.example.one=PROPERTIES
nablarch.micrometer.example.two=PROPERTIES
nablarch.micrometer.example.three=PROPERTIES

OS environment variables

$ export NABLARCH_MICROMETER_EXAMPLE_TWO=OS_ENV

$ export NABLARCH_MICROMETER_EXAMPLE_THREE=OS_ENV

system properties

-Dnablarch.micrometer.example.three=SYSTEM_PROP

In this case, each set value will eventually adopt the following values

For rules on naming when overwriting with OS environment variables, see About the names of OS environment variables .

Changing the configuration prefix¶

The configuration prefix (nablarch.micrometer.<subPrefix>) can be changed by specifying the prefix property for each registry factory.

Below is an example of changing the prefix.

<component name="meterRegistry" class="nablarch.integration.micrometer.logging.LoggingMeterRegistryFactory">
  <property name="meterBinderListProvider" ref="meterBinderListProvider" />
  <property name="applicationDisposer" ref="disposer" />

  <!-- Configuring the prefix property with an arbitrary prefix -->
  <property name="prefix" value="sample.prefix" />
</component>

In this case, the micrometer.properties can be configured as follows

sample.prefix.step=10s

Changing the place of the configuration file¶

The place of the configuration file (micrometer.properties) can be changed in the following ways.

First, specify the path of the XML file to load the configuration file in xmlConfigPath property of the registry factory.

<component name="meterRegistry" class="nablarch.integration.micrometer.logging.LoggingMeterRegistryFactory">
  <property name="meterBinderListProvider" ref="meterBinderListProvider" />
  <property name="applicationDisposer" ref="disposer" />

  <!-- Specify the path of the XML file to load the configuration file -->
  <property name="xmlConfigPath" value="config/metrics.xml" />
</component>

And, place the XML file to load the configuration file at the place specified in the xmlConfigPath property. In the following configuration, config/metrics.properties in the classpath will be loaded as a configuration file.

<?xml version="1.0" encoding="UTF-8"?>
<component-configuration
        xmlns="http://tis.co.jp/nablarch/component-configuration"
        xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
        xsi:schemaLocation="http://tis.co.jp/nablarch/component-configuration https://nablarch.github.io/schema/component-configuration.xsd">

  <!-- Load Micrometer adapter Configuration -->
  <config-file file="config/metrics.properties" />

</component-configuration>

Working with Datadog¶

Adding Dependencies

<dependency>
  <groupId>io.micrometer</groupId>
  <artifactId>micrometer-registry-datadog</artifactId>
  <version>1.13.0</version>
</dependency>

Declare the Registry Factory

<component name="meterRegistry" class="nablarch.integration.micrometer.datadog.DatadogMeterRegistryFactory">
  <property name="meterBinderListProvider" ref="meterBinderListProvider" />
  <property name="applicationDisposer" ref="disposer" />
</component>

Configuring the API key

nablarch.micrometer.datadog.apiKey=XXXXXXXXXXXXXXXX

The API key can be set in nablarch.micrometer.datadog.apiKey .

Configuring the site URL

nablarch.micrometer.datadog.uri=<SITE_URL>

The site URL can be set in nablarch.micrometer.datadog.uri .

See DatadogConfig (external site) for other configuration.

Disable the registry

nablarch.micrometer.datadog.enabled=false
nablarch.micrometer.datadog.apiKey=XXXXXXXXXXXXXXXX

You can disable the registry by setting nablarch.micrometer.datadog.enabled to false in micrometer.properties. You can override this configuration by environment variable. Therefor, you can enable the registry by setting true with environment variable only at production.

Important

Even if you disable the registry, you still need to set some value for nablarch.micrometer.datadog.apiKey. You can set dummy value to the apiKey.

Working with CloudWatch¶

Adding Dependencies

<dependency>
  <groupId>io.micrometer</groupId>
  <artifactId>micrometer-registry-cloudwatch2</artifactId>
  <version>1.13.0</version>
</dependency>

Declare the Registry Factory

<component name="meterRegistry" class="nablarch.integration.micrometer.cloudwatch.CloudWatchMeterRegistryFactory">
  <property name="meterBinderListProvider" ref="meterBinderListProvider" />
  <property name="applicationDisposer" ref="disposer" />
</component>

Configure the region, access keys, etc

$ export AWS_REGION=ap-northeast-1

$ export AWS_ACCESS_KEY_ID=XXXXXXXXXXXXXXXXXXXXX

$ export AWS_SECRET_ACCESS_KEY=YYYYYYYYYYYYYYYYYYYYY

The micrometer-registry-cloudwatch2 module uses the AWS SDK. Therefore, the configuration of the region, access keys, etc. follows the AWS SDK ways.

The above describes an example of how to set up an OS environment variable in Linux. For more information, see the AWS documentation (external site) .

Configuring the namespace

nablarch.micrometer.cloudwatch.namespace=test

Custom metrics namespaces can be configured in nablarch.micrometer.cloudwatch.namespace .

See CloudWatchConfig (external site) for more configuration information.

More detailed configuration

If want more detailed configuration that cannot be specified in the OS environment variables and configuration files, you can write a custom provider that implements CloudWatchAsyncClientProvider .

package example.micrometer.cloudwatch;

import nablarch.integration.micrometer.cloudwatch.CloudWatchAsyncClientProvider;
import software.amazon.awssdk.services.cloudwatch.CloudWatchAsyncClient;

public class CustomCloudWatchAsyncClientProvider implements CloudWatchAsyncClientProvider {
    @Override
    public CloudWatchAsyncClient provide() {
        return CloudWatchAsyncClient
                .builder()
                .asyncConfiguration(...) // Do your own configuration
                .build();
    }
}

CloudWatchAsyncClientProvider has a provide() method that provides the CloudWatchAsyncClient . A custom provider implements the provide() method to build and return the CloudWatchAsyncClient with your desired configuration.

<component name="meterRegistry" class="nablarch.integration.micrometer.cloudwatch.CloudWatchMeterRegistryFactory">
  <property name="meterBinderListProvider" ref="meterBinderListProvider" />
  <property name="applicationDisposer" ref="disposer" />

  <!-- Configure a custom provider for the cloudWatchAsyncClientProvider property -->
  <property name="cloudWatchAsyncClientProvider">
    <component class="example.micrometer.cloudwatch.CustomCloudWatchAsyncClientProvider" />
  </property>
</component>

The custom provider you write will be configured in the cloudWatchAsyncClientProvider property of the CloudWatchMeterRegistryFactory .

This enables the CloudWatchAsyncClient generated by the custom provider to be used in the cooperation of the metrics.

Tip

By default, the instance created by CloudWatchAsyncClient.create() (external site) is used.

Disable the registry

nablarch.micrometer.cloudwatch.enabled=false
nablarch.micrometer.cloudwatch.namespace=test

You can disable the registry by setting nablarch.micrometer.cloudwatch.enabled to false in micrometer.properties. You can override this configuration by environment variable. Therefor, you can enable the registry by setting true with environment variable only at production.

Important

Even if you disable the registry, you still need to set some value for nablarch.micrometer.cloudwatch.namespace. You also need to set the environment variable AWS_REGION.

You can set dummy values to the namespace and AWS_REGION.

Working with Azure¶

How to send metrics to Azure with Micrometer

Azure provides the library using the Java agent (Java 3.0 agent) for sending metrics from Java applications to Azure.

• Java codeless application monitoring Azure Monitor Application Insights(external site)

The Java 3.0 agent automatically collects metrics output to Micrometer’s Global Registry(external site), and sends to Azure.

• Send custom telemetry from your application(external site)

Important

The Java 3.0 agent loads a large number of jar files during the initialization process. This may cause frequent GC during the initialization process of the Java 3.0 agent.

Therefore, note that the performance may temporarily deteriorate due to GC for a while after the application is launched.

Also, under heavy load, the overhead caused by the processing of the Java 3.0 agent may affect the performance. Therefore, you should confirm the performance in the performance test with the Java 3.0 agent as in production.

For information on how to set up a Java 3.0 agent, see Distributed Tracing in Azure .

How to configure Micrometer adaptor

You need to configure following settings to send metrics to Azure with Micrometer adaptor.

• Add the Java 3.0 agent to your application’s JVM args
• Define a MeterRegistry component using the Global Registry

See the Azure documentation(external site) for how to set JVM args.

This adaptor provides GlobalMeterRegistryFactory for factory of Global Registry component. The following is an example of a component definition for this factory class.

<component name="meterRegistry" class="nablarch.integration.micrometer.GlobalMeterRegistryFactory">
  <property name="meterBinderListProvider" ref="meterBinderListProvider" />
  <property name="applicationDisposer" ref="disposer" />
</component>

This configuration makes the Global Registry to collect metrics. The Java 3.0 agent sends metrics collected by the Global Registry to Azure.

Tip

MeterRegistry is not used in this approach using Java 3.0 agent. Therefore, you can send metrics without additional dependent modules for Azure.

Configuration

The metrics are sent by the Java 3.0 agent provided by Azure. Therefore, you must use configuration options provided by the Java 3.0 agent.

For more information, see Configuration Options(external site).

Important

The configuration file for this adapter, micrometer.properties, is not used. However, you must place the micrometer.properties file (the content can be empty).

Disable the registry

You can disable to send metrics by launching application without the Java 3.0 agent.

Working with Datadog using StatsD¶

Datadog supports DogStatsD (external site), which is a cooperation using the StatsD (external site) protocol.

Therefore, Can use micrometer-registry-statsd module to connect to Datadog with StatsD.

In this section, we will use the case of cooperation with Datadog using the StatsD protocol as an example. For more information on how to install DogStatsD, refer to Datadog’s site (external site) .

Adding Dependencies

<dependency>
  <groupId>io.micrometer</groupId>
  <artifactId>micrometer-registry-statsd</artifactId>
  <version>1.13.0</version>
</dependency>

Declare the Registry Factory

<component name="meterRegistry" class="nablarch.integration.micrometer.statsd.StatsdMeterRegistryFactory">
  <property name="meterBinderListProvider" ref="meterBinderListProvider" />
  <property name="applicationDisposer" ref="disposer" />
</component>

Write a configuration file if necessary

The configuration for working with the StatsD daemon has been adjusted so that the default values match those of DogStatsD installed in its default configuration.

Therefore, if DogStatsD is installed in the default configuration, the cooperation by DogStatsD will work without any explicit settings.

If you have installed a non-default configuration, refer to StatsdConfig (external site) to configure it for actual environment.

# Change Port
nablarch.micrometer.statsd.port=9999

Disable the registry

nablarch.micrometer.statsd.enabled=false

You can disable the registry by setting nablarch.micrometer.statsd.enabled to false in micrometer.properties. You can override this configuration by environment variable. Therefor, you can enable the registry by setting true with environment variable only at production.

Using OpenTelemetry Protocol (OTLP)¶

Many monitoring services support OpenTelemetry (external site) and can collect metrics using the OpenTelemetry Protocol (hereafter OTLP) as the communication protocol. The micrometer-registry-otlp module allows OTLP to work with various monitoring services.

Important

When collecting metrics with OpenTelemetry, check the information on the monitoring service to be used, as the appropriate (and available) linking method depends on the monitoring service. As an example, information on some monitoring services is shown below.

• Datadog’s OpenTelemetry (external site)
• Introduction to OpenTelemetry by New Relic (external site)
• Prometheus | HTTP API | OTLP Receiver(external site)

In this section, we will use the case of OTLP linking to Prometheus running on port 9090 of localhost as an example.

Adding Dependencies

<dependency>
  <groupId>io.micrometer</groupId>
  <artifactId>micrometer-registry-otlp</artifactId>
  <version>1.13.0</version>
</dependency>

Declare the Registry Factory

<component name="meterRegistry" class="nablarch.integration.micrometer.otlp.OtlpMeterRegistryFactory">
  <property name="meterBinderListProvider" ref="meterBinderListProvider" />
  <property name="applicationDisposer" ref="disposer" />
</component>

Write a configuration file

# Change Destination
nablarch.micrometer.otlp.url=http://localhost:9090/api/v1/otlp/v1/metrics

Configuring headers

nablarch.micrometer.otlp.headers=key1=value1,key2=value2

If you need header information such as API keys for authentication, you can set it with nablarch.micrometer.otlp.headers.

Disable the registry

nablarch.micrometer.otlp.enabled=false

You can disable the registry by setting nablarch.micrometer.otlp.enabled to false in micrometer.properties. You can override this configuration by environment variable. Therefor, you can enable the registry by setting true with environment variable only at production.

Examples of metrics for web applications¶

Processing time for HTTP requests

By measuring the processing time for each HTTP request, you can do the following.

• You can check how much traffic each URL
• You can check how long it takes to process the request

By measuring percentiles, you can also check how long it takes to process most of the requests.

See the following guide for more informations on how to collect these metrics.

• Handler to measure processing time
• Collect the percentiles

Processing time for SQL

By measuring the SQL processing time, you can do the following.

• You can check how long it takes for each SQL to be processed
• You can check for SQLs that are taking longer than expected

See the following guide for more informations on how to collect metrics.

• Measure SQL processing time

Output count per log level

By measuring the count of outputs per log level, you can do the following.

• You can check if the warning log is output an abnormal number of times (attack detection)
• You can detect error logs

See the following guide for more informations on how to collect metrics.

• Measure the output count per log level

Status of resources provided by application servers and libraries

By collecting metrics on the status of resources provided by application servers and libraries (thread pools, DB connection pools, etc.), you can use it as a source of information to identify the cause of system failures.

Many application servers expose the status of their resources through MBean in JMX. See the following guide for more informations on how to collect metrics.

• Measure the value obtained from any MBean as a metric

Examples of metrics for batch applications¶

Processing time for batch

By measuring the processing time of batches in normally, you can know the processing time under normal conditions. Therefore, you can quickly detect abnormalities when processing time deviates from normal.

You can get processing time of batch by process.uptime described in Metrics collected by the DefaultMeterBinderListProvider.

Processing time per transaction

By measuring the processing time per transaction, you can check whether each threads are distributed evenly in the multi-thread batch.

As with processing time for batch, you can quickly detect abnormalities when processing time deviates from normal.

See the following guide for more informations on how to collect metrics.

• Measure the processing time per transaction of a batch

Processed count with batch

By measuring the count that was processed by batch, you can do the following.

• You can check the progress of the batch
• You can check that the batch process is proceeding at the expected speed
• You can check that the count processed with batch is expected

See the following guide for more informations on how to collect metrics.

• Measure the count that was processed by batch

Processing time for SQL

By measuring the SQL processing time, you can do the following.

• You can check how long it takes for each SQL to be processed
• You can check for SQLs that are taking longer than expected

See the following guide for more informations on how to collect metrics.

• Measure SQL processing time

Output count per log level

By measuring the count of outputs per log level, you can detect warning logs and error logs.

See the following guide for more informations on how to collect metrics.

• Measure the output count per log level

Status of resources provided by libraries

By collecting metrics on the status of resources provided by libraries (DB connection pools, etc.), you can use it as a source of information to identify the cause of system failures.

Some libraries expose the status of the resource through MBean in JMX. See the following guide for more informations on how to collect metrics.

• Measure the value obtained from any MBean as a metric

Collect the percentiles¶

TimerMetricsHandler has the following properties to send percentiles to the monitoring services.

These properties are used as values to be set in Timer(external site) provided by Micrometer. For more details, see the Micrometer documentation (external site).

These properties are unset by default. Therefore, no percentile information is collected. You must configure these properties explicitly if you want collect percentiles. The following is an example for configuration.

<component class="nablarch.integration.micrometer.instrument.handler.TimerMetricsHandler">
  <property name="meterRegistry" ref="meterRegistry" />
  <property name="handlerMetricsMetaDataBuilder">
    <component class="nablarch.integration.micrometer.instrument.http.HttpRequestTimeMetricsMetaDataBuilder" />
  </property>

  <!-- Collect 98th, 90th, 50th percentiles -->
  <property name="percentiles">
    <list>
      <value>0.98</value>
      <value>0.90</value>
      <value>0.50</value>
    </list>
  </property>

  <!-- Send the histogram backets to the monitoring service  -->
  <property name="enablePercentileHistogram" value="true" />

  <!-- Set 1000ms and 1500ms as SLO -->
  <property name="serviceLevelObjectives">
    <list>
      <value>1000</value>
      <value>1500</value>
    </list>
  </property>

  <!-- Set the minimum bucket value to 500ms -->
  <property name="minimumExpectedValue" value="500" />
  <!-- Set the maximum bucket value to 3000ms -->
  <property name="maximumExpectedValue" value="3000" />
</component>

If you use the MeterRegistry that supports histogram buckets, the above configuration will allow you to collect the following metrics.

http_server_requests_seconds{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",quantile="0.98",} 1.475346432
http_server_requests_seconds{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",quantile="0.9",} 1.408237568
http_server_requests_seconds{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",quantile="0.5",} 0.737148928
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="0.5",} 9.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="0.536870911",} 9.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="0.626349396",} 12.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="0.715827881",} 16.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="0.805306366",} 16.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="0.894784851",} 17.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="0.984263336",} 17.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="1.0",} 18.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="1.073741824",} 20.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="1.431655765",} 29.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="1.5",} 32.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="1.789569706",} 32.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="2.147483647",} 32.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="2.505397588",} 32.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="2.863311529",} 32.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="3.0",} 32.0
http_server_requests_seconds_bucket{class="com.nablarch.example.app.web.action.MetricsAction",exception="None",httpMethod="GET",method="index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext",outcome="SUCCESS",status="200",le="+Inf",} 32.0

package example.micrometer.prometheus;

import io.micrometer.prometheusmetrics.PrometheusConfig;
import io.micrometer.prometheusmetrics.PrometheusMeterRegistry;
import nablarch.core.repository.di.DiContainer;
import nablarch.integration.micrometer.MeterRegistryFactory;
import nablarch.integration.micrometer.MicrometerConfiguration;
import nablarch.integration.micrometer.NablarchMeterRegistryConfig;

public class PrometheusMeterRegistryFactory extends MeterRegistryFactory<PrometheusMeterRegistry> {

    @Override
    protected PrometheusMeterRegistry createMeterRegistry(MicrometerConfiguration micrometerConfiguration) {
        return new PrometheusMeterRegistry(new Config(prefix, micrometerConfiguration));
    }

    @Override
    public PrometheusMeterRegistry createObject() {
        return doCreateObject();
    }

    static class Config extends NablarchMeterRegistryConfig implements PrometheusConfig {

        public Config(String prefix, DiContainer diContainer) {
            super(prefix, diContainer);
        }

        @Override
        protected String subPrefix() {
            return "prometheus";
        }
    }
}

The provided HandlerMetricsMetaDataBuilder implementation¶

In this section, we explain the implementation class of HandlerMetricsMetaDataBuilder, which is provided by Nablarch.

<!-- Handler queue -->
<component name="webFrontController"
           class="nablarch.fw.web.servlet.WebFrontController">
  <property name="handlerQueue">
    <list>
      <!-- Handler to collect metrics of processing time of HTTP requests -->
      <component class="nablarch.integration.micrometer.instrument.handler.TimerMetricsHandler">
        <!-- Set the MeterRegistry created by the registry factory to meterRegistry property -->
        <property name="meterRegistry" ref="meterRegistry" />

        <!-- Set the HttpRequestTimeMetricsMetaDataBuilder to handlerMetricsMetaDataBuilder property -->
        <property name="handlerMetricsMetaDataBuilder">
          <component class="nablarch.integration.micrometer.instrument.http.HttpRequestTimeMetricsMetaDataBuilder" />
        </property>
      </component>

      <component class="nablarch.fw.web.handler.HttpCharacterEncodingHandler"/>

      <!-- ... -->
   </list>
  </property>
</component>

2020-10-06 13:52:10.309 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: http.server.requests{class=com.nablarch.example.app.web.action.AuthenticationAction,exception=None,httpMethod=POST,method=login_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext,outcome=REDIRECTION,status=303} throughput=0.2/s mean=0.4617585s max=0.4617585s
2020-10-06 13:52:10.309 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: http.server.requests{class=com.nablarch.example.app.web.action.IndustryAction,exception=None,httpMethod=GET,method=find,outcome=SUCCESS,status=200} throughput=0.2/s mean=0.103277s max=0.103277s
2020-10-06 13:52:10.310 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: http.server.requests{class=com.nablarch.example.app.web.action.AuthenticationAction,exception=None,httpMethod=GET,method=index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext,outcome=SUCCESS,status=200} throughput=0.2/s mean=4.7409146s max=4.7409146s
2020-10-06 13:52:10.310 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: http.server.requests{class=com.nablarch.example.app.web.action.ProjectAction,exception=None,httpMethod=GET,method=index_nablarch.fw.web.HttpRequest_nablarch.fw.ExecutionContext,outcome=SUCCESS,status=200} throughput=0.2/s mean=0.5329547s max=0.5329547s

Configure LogPublisher¶

LogCountMetrics uses the LogPublisher mechanism to detect log output events.

Therefore, you need to configure LogPublisher at first to use LogCountMetrics. For LogPublisher settings, see How to use LogPublisher.

Create a custom DefaultMeterBinderListProvider¶

LogCountMetrics is provided as an implementation class of MeterBinder (external site). Therefore, you need create a class that inherits from DefaultMeterBinderListProvider and implement it to return a list of MeterBinders that contains LogCountMetrics.

The following is an example for a custom DefaultMeterBinderListProvider.

package example.micrometer.log;

import io.micrometer.core.instrument.binder.MeterBinder;
import nablarch.integration.micrometer.DefaultMeterBinderListProvider;
import nablarch.integration.micrometer.instrument.binder.logging.LogCountMetrics;

import java.util.ArrayList;
import java.util.List;

public class CustomMeterBinderListProvider extends DefaultMeterBinderListProvider {

    @Override
    protected List<MeterBinder> createMeterBinderList() {
        // Add LogCountMetrics to the default MeterBinder list.
        List<MeterBinder> meterBinderList = new ArrayList<>(super.createMeterBinderList());
        meterBinderList.add(new LogCountMetrics());
        return meterBinderList;
    }
}

Finally, set the custom DefaultMeterBinderListProvider that you created to the meterBinderListProvider property of the MeterRegistryFactory component. Now you can use the LogCountMetrics.

If you use LoggingMeterRegistry, you will get like the following metrics.

2020-12-22 14:25:36.978 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: log.count{level=WARN,logger=com.nablarch.example.app.web.action.MetricsAction} throughput=0.4/s
2020-12-22 14:25:41.978 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: log.count{level=ERROR,logger=com.nablarch.example.app.web.action.MetricsAction} throughput=1.4/s

Log level to be aggregated¶

By default, only log outputs above the warning log will be counted.

LogCountMetrics has a constructor that receives a LogLevel. You can change the threshold of the log level to be aggregated with the constructor. In the following implementation example, the threshold value is changed to INFO.

// ...
import nablarch.core.log.basic.LogLevel;

public class CustomMeterBinderListProvider extends DefaultMeterBinderListProvider {

    @Override
    protected List<MeterBinder> createMeterBinderList() {
        List<MeterBinder> meterBinderList = new ArrayList<>(super.createMeterBinderList());
        meterBinderList.add(new LogCountMetrics(LogLevel.INFO)); // Specify the threshold of log level.
        return meterBinderList;
    }
}

Obtain the status of the Tomcat thread pool¶

JmxGaugeMetrics implements MeterBinder (external site). Therefore, you need create a class that inherits from DefaultMeterBinderListProvider and implement it to return a list of MeterBinders that contains JmxGaugeMetrics.

The following is an example for a custom DefaultMeterBinderListProvider.

package example.micrometer;

import io.micrometer.core.instrument.binder.MeterBinder;
import nablarch.integration.micrometer.DefaultMeterBinderListProvider;
import nablarch.integration.micrometer.instrument.binder.MetricsMetaData;
import nablarch.integration.micrometer.instrument.binder.jmx.JmxGaugeMetrics;
import nablarch.integration.micrometer.instrument.binder.jmx.MBeanAttributeCondition;

import java.util.ArrayList;
import java.util.List;

public class CustomMeterBinderListProvider extends DefaultMeterBinderListProvider {

    @Override
    protected List<MeterBinder> createMeterBinderList() {
        List<MeterBinder> meterBinderList = new ArrayList<>(super.createMeterBinderList());
        meterBinderList.add(new JmxGaugeMetrics(
            // Name and description of metrics.
            new MetricsMetaData("thread.count.current", "Current thread count."),
            // The conditions to specify the attribute of MBean.
            new MBeanAttributeCondition("Catalina:type=ThreadPool,name=\"http-nio-8080\"", "currentThreadCount")
        ));
        return meterBinderList;
    }
}

You must pass following classes to the constructor of JmxGaugeMetrics.

• MetricsMetaData

  • Specify meta data such as the name, description, and tags of the metrics.

• MBeanAttributeCondition

  • Specify the object name and attribute name to identify the MBean.

JmxGaugeMetrics gets the MBean based on the information specified in MBeanAttributeCondition. Then, the JmxGaugeMetrics constructs metrics with the information specified in MetricsMetaData.

If you use LoggingMeterRegistry, you will get like the following metrics.

18-Feb-2021 13:17:38.168 INFO [logging-metrics-publisher] io.micrometer.core.instrument.logging.LoggingMeterRegistry.lambda$publish$3 thread.count.current{} value=10

Obtain the status of the HikariCP connection pool¶

HikariCP (external site) has a function to get status of the connection pool by MBean.

• MBean (JMX) Monitoring and Management (external site)

This function will allow JmxGaugeMetrics to collect connection pool status.

First, enable the function to publish status by MBean. You must set true to registerMbeans property of com.zaxxer.hikari.HikariDataSource.

<?xml version="1.0" encoding="UTF-8"?>
<component-configuration
        xmlns="http://tis.co.jp/nablarch/component-configuration"
        xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
        xsi:schemaLocation="http://tis.co.jp/nablarch/component-configuration https://nablarch.github.io/schema/component-configuration.xsd">
  <!-- ... -->

  <!-- Datasource configuration -->
  <component name="dataSource"
            class="com.zaxxer.hikari.HikariDataSource" autowireType="None">
    <property name="driverClassName" value="${nablarch.db.jdbcDriver}"/>
    <property name="jdbcUrl"         value="${nablarch.db.url}"/>
    <property name="username"        value="${nablarch.db.user}"/>
    <property name="password"        value="${nablarch.db.password}"/>
    <property name="maximumPoolSize" value="${nablarch.db.maxPoolSize}"/>
    <!-- Enable MBean to publish status. -->
    <property name="registerMbeans"  value="true"/>
  </component>

</component-configuration>

In the above configuration, we set true to the registerMbeans property in the component definition of HikariDataSource.

Next, configure the JmxGaugeMetrics with the object name and attribute name that you want to measure. The specifications of object names and attribute names are described in the HikariCP document mentioned above (external site).

The following is an example implementation of JmxGaugeMetrics for measuring the maximum count of connection pools and the count of active connections.

package com.nablarch.example.app.metrics;

import io.micrometer.core.instrument.binder.MeterBinder;
import nablarch.integration.micrometer.DefaultMeterBinderListProvider;
import nablarch.integration.micrometer.instrument.binder.MetricsMetaData;
import nablarch.integration.micrometer.instrument.binder.jmx.JmxGaugeMetrics;
import nablarch.integration.micrometer.instrument.binder.jmx.MBeanAttributeCondition;

import java.util.ArrayList;
import java.util.List;

public class CustomMeterBinderListProvider extends DefaultMeterBinderListProvider {

    @Override
    protected List<MeterBinder> createMeterBinderList() {
        List<MeterBinder> meterBinderList = new ArrayList<>(super.createMeterBinderList());
        // The maximum count.
        meterBinderList.add(new JmxGaugeMetrics(
            new MetricsMetaData("db.pool.total", "Total DB pool count."),
            new MBeanAttributeCondition("com.zaxxer.hikari:type=Pool (HikariPool-1)", "TotalConnections")
        ));
        // The active count.
        meterBinderList.add(new JmxGaugeMetrics(
            new MetricsMetaData("db.pool.active", "Active DB pool count."),
            new MBeanAttributeCondition("com.zaxxer.hikari:type=Pool (HikariPool-1)", "ActiveConnections")
        ));
        return meterBinderList;
    }
}

If you use LoggingMeterRegistry, you will get like the following metrics.

2020-12-24 16:37:57.143 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: db.pool.active{} value=0
2020-12-24 16:37:57.143 [INFO ]      i.m.c.i.l.LoggingMeterRegistry: db.pool.total{} value=5

18-Feb-2021 13:17:37.953 WARNING [logging-metrics-publisher] io.micrometer.core.util.internal.logging.WarnThenDebugLogger.log Failed to apply the value function for the gauge 'db.pool.active'. Note that subsequent logs will be logged at debug level.
        java.lang.RuntimeException: javax.management.InstanceNotFoundException: com.zaxxer.hikari:type=Pool (HikariPool-1)
                at nablarch.integration.micrometer.instrument.binder.jmx.JmxGaugeMetrics.obtainGaugeValue(JmxGaugeMetrics.java:59)
                at io.micrometer.core.instrument.Gauge.lambda$builder$0(Gauge.java:58)
                at io.micrometer.core.instrument.StrongReferenceGaugeFunction.applyAsDouble(StrongReferenceGaugeFunction.java:47)
                at io.micrometer.core.instrument.internal.DefaultGauge.value(DefaultGauge.java:54)
                at io.micrometer.core.instrument.logging.LoggingMeterRegistry.lambda$publish$3(LoggingMeterRegistry.java:98)
                at io.micrometer.core.instrument.Meter.use(Meter.java:158)
                at io.micrometer.core.instrument.logging.LoggingMeterRegistry.lambda$publish$12(LoggingMeterRegistry.java:97)
                at java.util.stream.ForEachOps$ForEachOp$OfRef.accept(ForEachOps.java:183)
                at java.util.stream.SortedOps$SizedRefSortingSink.end(SortedOps.java:357)
                at java.util.stream.AbstractPipeline.copyInto(AbstractPipeline.java:483)
                at java.util.stream.AbstractPipeline.wrapAndCopyInto(AbstractPipeline.java:472)
                at java.util.stream.ForEachOps$ForEachOp.evaluateSequential(ForEachOps.java:150)
                at java.util.stream.ForEachOps$ForEachOp$OfRef.evaluateSequential(ForEachOps.java:173)
                at java.util.stream.AbstractPipeline.evaluate(AbstractPipeline.java:234)
                at java.util.stream.ReferencePipeline.forEach(ReferencePipeline.java:485)
                at io.micrometer.core.instrument.logging.LoggingMeterRegistry.publish(LoggingMeterRegistry.java:95)
                at io.micrometer.core.instrument.push.PushMeterRegistry.publishSafely(PushMeterRegistry.java:52)
                at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
                at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
                at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
                at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
                at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
                at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
                at java.lang.Thread.run(Thread.java:748)
        Caused by: javax.management.InstanceNotFoundException: com.zaxxer.hikari:type=Pool (HikariPool-1)
                at com.sun.jmx.interceptor.DefaultMBeanServerInterceptor.getMBean(DefaultMBeanServerInterceptor.java:1095)
                at com.sun.jmx.interceptor.DefaultMBeanServerInterceptor.getAttribute(DefaultMBeanServerInterceptor.java:643)
                at com.sun.jmx.mbeanserver.JmxMBeanServer.getAttribute(JmxMBeanServer.java:678)
                at nablarch.integration.micrometer.instrument.binder.jmx.JmxGaugeMetrics.obtainGaugeValue(JmxGaugeMetrics.java:52)
                ... 23 more

18-Feb-2021 13:18:32.933 INFO [logging-metrics-publisher] io.micrometer.core.instrument.logging.LoggingMeterRegistry.lambda$publish$3 db.pool.active{} value=NaN
18-Feb-2021 13:18:32.933 INFO [logging-metrics-publisher] io.micrometer.core.instrument.logging.LoggingMeterRegistry.lambda$publish$3 db.pool.total{} value=NaN

package example.micrometer;

// ...
import nablarch.core.log.Logger;
import nablarch.core.log.LoggerManager;
import nablarch.core.repository.initialization.Initializable;
import java.sql.SQLException;
import javax.sql.DataSource;
import java.sql.Connection;

public class CustomMeterBinderListProvider extends DefaultMeterBinderListProvider implements Initializable {
    private static final Logger LOGGER = LoggerManager.get(CustomMeterBinderListProvider.class);

    private DataSource dataSource;

    @Override
    protected List<MeterBinder> createMeterBinderList() {
        // ...
    }

    public void setDataSource(DataSource dataSource) {
        this.dataSource = dataSource;
    }

    @Override
    public void initialize() {
        try (Connection con = dataSource.getConnection()) {
            // Preventing the warning log by establishing a connection during initialization.
        } catch (SQLException e) {
            LOGGER.logWarn("Failed initial connection.", e);
        }
    }
}

<component name="meterBinderListProvider"
           class="example.micrometer.CustomMeterBinderListProvider">
  <!-- Set the DataSource -->
  <property name="dataSource" ref="dataSource" />
</component>

<!-- The components that need initialization. -->
<component name="initializer"
           class="nablarch.core.repository.initialization.BasicApplicationInitializer">
  <property name="initializeList">
    <list>
      <!-- ... -->

      <!-- Add CustomMeterBinderListProvider for initialization. -->
      <component-ref name="meterBinderListProvider" />
    </list>
  </property>
</component>