The Normalizer service uses the Wizzie Metrics Library to build his metrics, by default it sends JVM metrics but you can register new metrics that will be exported too.

Properties

The metrics service has three properties to configure it:

Property	Description	Default Value
metric.enable	Enable or disable metrics service	false
metric.listeners	The listener to send the metrics.	[“io.wizzie.metrics.listeners.ConsoleMetricListener”]
metric.interval	The interval time to report metrics (milliseconds)	60000
metric.verbose.mode	Enable the verbose metric mode	false

The listeners are the process that listen the reported metrics and do something with them. You can have multiple listeners at the same time. Currently, the Normalizer service supports two listener metrics:

Listeners

ConsoleMetricListener

This listener io.wizzie.metrics.listeners.ConsoleMetricListener send the transform the metrics to JSON and prints them into the log file using the log4j. The metric format is:

{"timestamp":123456789, "monitor":"heap-memory", "value":12345}

KafkaMetricListener

This listener io.wizzie.metrics.listeners.KafkaMetricListener send the transform the metrics to JSON and sends them into the Kafka topic. The metric format is:

{"timestamp":123456789, "monitor":"heap-memory", "value":12345, "app_id":"MY_KAFKA_STREAMS_APP_ID"}

This listener adds a new property to specify the metrics Kafka topic metric.kafka.topic, by default is __normalizer_metrics

Custom Listeners

You can made new listeners to do this you need to implement the MetricListener Class.