One of crucial aspects of running production streaming processes is monitoring. In this section we'll explain how Nussknacker process running of Flink cluster gives rise to certain metrics, and how to process them and display in Grafana.

For each process following metrics are collected:

  • number of events consumed
  • number of events that passed the whole process
  • number of events filtered out
  • http services' invocation times, errors and throughput
  • event processing delays

Metrics technical details

We recommend using InfluxDB or Prometheus for storing metrics. In default (e.g. demo) setup we use InfluxDB.

Metric types

We use following standard metric types, which are reported according to configured metric reporter

  • gauge
  • histogram
  • counter
  • meter

In descriptions below we also use composite metrics, which translate to more than one Flink/Dropwizard metrics:

  • instantRate - gauge measuring instant rate (that is, without smoothing) TODO: add also 'normal' meter for this metric

  • instantRateWithCount - as above plus counter. TODO: after adding meter to instantRate this will become obsolete

    • instantRate
    • count - counter
  • espTimer - this type of metrics is used to track times of invocations with rate (e.g. how long service invocation took)

    • histogram
    • instantRate - gauge

Common metrics

Measurement Additional tags Metric type Notes
nodeCount nodeId counter used e.g. by count functionality
error.instantRate - instantRate
error.instantRateByNode nodeId instantRate nodeId is unknown if we fail to detect exact place
service.OK serviceName espTimer see below
service.FAIL serviceName espTimer see below

service metric is not added automatically. It can be used via GenericTimeMeasuringService to measure arbitrary code returning Future - it will be classified as OK or FAIL if it's successful or not.

Measurement Additional tags Metric type Description
source nodeId instantRateWithCount
eventtimedelay.histogram nodeId historgram only for sources with eventTime, measures delay from event time to system time
eventtimedelay.minimalDelay nodeId gauge time from last event (eventTime) to system time
end nodeId instantRateWithCount for sinks and end processors
dead_end nodeId instantRateWithCount for event filtered out on filters, switches etc.

Metrics in standalone mode

In standalone mode we use Dropwizard metrics. However, due to low traffic in this project we consider using Micrometer in the future.

Measurement Additional tags Metric type Description
invocation.success - espTimer
invocation.failure nodeId espTimer

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