Updated: March 18, 2024

The Nuxeo code is instrumented using Dropwizard Metrics.

This library enables to report different type of metrics:

  • Counters: a value that can increase (or decrease), for instance the number of created documents.
  • Gauges: this is an instantaneous measurement of a value. For example, the size of a cache.
  • Timers: it measures both the rate that a particular piece of code is called and the distribution of its duration. For example, it provides the min, max, average and percentiles for a request duration but also the number of requests per second, the total number of requests and, the total elapsed time.

Nuxeo metrics can be reported to various Monitoring systems.

To have a complete monitoring you should also monitor the operating system where Nuxeo is running as well as other services: databases, Elasticsearch, Redis or Kafka.

Supported Monitoring Systems

Nuxeo uses a MetricReporter interface to publish its metrics and provides multiple implementations, the system can be extended to support other monitoring systems.

By default, since Nuxeo 11, we have the following metric reporters:

  • JMX
  • Graphite
  • Datadog
  • Prometheus
  • GCP Metrics (previously known as Stackdriver)

It is possible to activate multiple reporters at the same time.

Depending on the chosen metric reporter, Nuxeo will push metrics or the metric system will poll Nuxeo for metrics. For instance, metrics are pushed to Graphite and Datadog while Prometheus is polling Nuxeo for metrics.

Monitoring systems are either hierarchical or dimensional:

  • Hierarchical Monitoring system uses a flat metric name, like a file system tree. Example of such system are: JMX, Graphite, StatsD, Ganglia, ...
  • Dimensional Monitoring system uses metric names enriched with tag key/value pairs. Example of such system are: Prometheus, Datadog, influxDB, ...

Since Nuxeo 11 the instrumentation of the code uses metric names with tags (dimensional metric). Hierarchical monitoring reporters flatten the tags into the metric name.

For instance, a gauge that measures the pending video conversions on a Nuxeo cluster is named and has the following tag: queue=videoConversion that express the work queue dimension, the metric name is translated into:

Monitoring system type metric
JMX hierarchical #mbean =,queue=videoConversion,type=gauges
Graphite hierarchical ${PREFIX}
Datadog dimensional queue:videoConversion host:nuxeo
Prometheus dimensional dropwizard5_nuxeo_works_global_queue_scheduled_gauge{instance="nuxeo:8888",job="nuxeo",queue="videoConversion"}
GCP Metrics (Stackdriver) dimensional queue:videoConversion

Note that the tag value (videoConversion in the above example) can be rewritten as a valid identifier, for instance a value of audit/writer will be translated into audit-writer

JMX Reporter

To activate the JMX reporting you need a nuxeo.conf with the following options:


Metrics are exposed in a metrics MBean domain.

Note that to access the JMX MBean you need to activate JMX using JAVA_OPTS:


You then have to manage security for this access, since there is no authentication by default.

Visit this page to see how to dump all metrics.

$ echo "get -b,queue=default,type=timers *" | java -jar /tmp/jmxterm-1.0.1-uber.jar -l localhost:1089 -n
Welcome to JMX terminal. Type "help" for available commands.
#mbean =,queue=default,type=timers:
50thPercentile = 0.0;
DurationUnit = microseconds;
Max = 76000.0;
75thPercentile = 0.0;
95thPercentile = 0.0;
98thPercentile = 0.0;
99thPercentile = 0.0;
999thPercentile = 24000.0;
Mean = 67.96712231400461;
StdDev = 1250.994358152994;
Min = 0.0;
Count = 60;
RateUnit = events/second;
Sum = 509000.0;
FifteenMinuteRate = 0.021929133134494853;
FiveMinuteRate = 0.011975928378019026;
MeanRate = 0.047353163048175675;
OneMinuteRate = 5.608847244891202E-4;

Graphite Reporter

Metrics are pushed to Graphite every pollInterval. Default reporting is done using TCP but if possible UDP should be chosen. If unspecified the default prefix is server.<HOSTNAME>.nuxeo.

The nuxeo.conf options are:



Datadog Reporter



The metrics.datadog.apiKey is required when publishing directly to Datadog, in this case host and port are not required.

When UDP is chosen, the and metrics.datadog.port must refer to a Datadog agent in charge of forwarding metrics into the cloud.

Additional tags can be added to all metrics using metrics.datadog.tags. Metrics are polled from Nuxeo and pushed to Datadog using the defined pollInterval.


Prometheus Reporter



Nuxeo is exposing a Prometheus endpoint on metrics.prometheus.port. You have to manage security for this access and make sure it is accessible from Prometheus in order to scrape the metrics.

Note that the Dropwizzard Metrics are exposed using Opencensus, they are automatically prefixed by dropwizard5_ and suffixed depending on metric types (_gauge, _count and _timer).


GCP Metrics (Stackdriver)

You need to provide a valid GCP project identifier.



The metrics will be prefixed by


Metrics Filtering

A counter or gauge instrumentation create a single metric, on the other hand a timer generates 16 metrics:

  • min: minimum measured time
  • max: maximum measured time
  • mean: average measured time
  • stddev: standard deviation
  • p50: median or percentile 50%
  • p75, p95, p98, p99, p999: percentiles
  • m1_rate: moving average on the last minute of the throughput
  • m5_rate, m15_rate: moving average on 5 and 15 minutes
  • mean_rate: average throughput
  • count: number of timer call
  • sum: total cumulative time

The number of metrics depends on the deployed repositories, directories, caches, work queues, computations, streams ... which can be a huge number. Fortunately it is possible to filter metrics.

Nuxeo comes with a default filter that:

  • Reduces timer metrics by removing some percentiles and rates
  • Accept only a few caches and directories metrics
  • Deny other caches and directories
  • Deny log4j metrics for the level below WARN

This filter can be found in common-base template in the metrics-config.xml file:

  <extension target="org.nuxeo.runtime.metrics.MetricsService" point="configuration">
    <configuration enabled="${metrics.enabled}">
          <!-- Timer expansion to remove -->

Note that the prefix value used in the allow/deny rules is the beginning of the flatten metric name.

Metrics Description

This section describes the main metrics available by categories.

You will find the metric name and its associates dimensions.

Nuxeo Cache

All the following metrics have a cache dimension with the name of the cache. Common caches are: default-cache or low level caches used by directories like: user-entry-cache or group-entry-cache.

  • nuxeo.cache.hit: Number of cache hits
  • nuxeo.cache.miss: Number of cache miss
  • nuxeo.cache.hit.ratio: Hit ratio of the cache
  • nuxeo.cache.invalidation: Number of cache invalidation
  • nuxeo.cache.size: Size of the cache
  • Number of cache get (miss + hit)
  • nuxeo.cache.write: Number of cache put

Nuxeo Directories

Directory metrics have a directory dimension with the name of the directory. Common directories are: userDirectory, groupDirectory

  • Number of active Sessions
  • Maximum number of Sessions used
  • Number of entry hits
  • Count hit on non-existing entries
  • Count invalidation
  • Number of cache miss
  • Cache size

Nuxeo Elasticsearch

Nuxeo Elasticsearch service use timers.

  • nuxeo.elasticsearch.service.timer: Timer on the service dimension below
    • service=search: Invoking an elasticsearch query
    • service=scroll: Invoking a next scroll query
    • service=index: Invoking indexation of a single document
    • service=bulkIndex: Invoking indexation of one or more documents
    • service=delete: Invoking a deletion query
    • service=fetch: Fetching documents from the repository to build the search response

Nuxeo Stream Importer

When using the nuxeo-platform-importer/nuxeo-importer-stream some metrics are reported to follow producers and consumers progress.

  • Timer on poducer hook
  • Number of producers
  • Number of consumers
  • Number of committed documents
  • Timer on batch transaction commit
  • Counter of batch failure

Nuxeo Instance UP

Each time a Nuxeo node is started it reports the following metrics that can be aggregated to count the number of Nuxeo nodes in the cluster.

  • nuxeo.instance-up: One if up

Nuxeo Repositories

Repository metrics have a repository dimension with the name of the repository.

  • nuxeo.repositories.repository.documents.create: Count the number of documents created since the node is up
  • nuxeo.repositories.repository.documents.delete: Count the number of documents deleted since the node is up
  • nuxeo.repositories.repository.documents.update: Count the number of documents updated since the node is up

  • nuxeo.repositories.repository.query: Timer on NXQL queries

  • Timer on session saves
  • nuxeo.repositories.sessions: Counter of active sessions

  • nuxeo.repositories.repository.connection.count: Number of connections used

  • nuxeo.repositories.repository.connection.idle: Number of connections idle
  • nuxeo.repositories.repository.connection.killed: Killed connections

Repository document cache stats:

  • nuxeo.repositories.repository.cache.eviction.count
  • nuxeo.repositories.repository.cache.hit.count
  • nuxeo.repositories.repository.cache.hit.ratio
  • nuxeo.repositories.repository.cache.miss.count
  • nuxeo.repositories.repository.cache.size

Repository children documents cache stats:

  • nuxeo.repositories.repository.childCache.eviction.count
  • nuxeo.repositories.repository.childCache.hit.count
  • nuxeo.repositories.repository.childCache.hit.ratio
  • nuxeo.repositories.repository.childCache.miss.count
  • nuxeo.repositories.repository.childCache.size

Nuxeo Streams

Nuxeo Stream Processor relies on a topology of computations. It is important to monitor failure because a manual intervention is required.

  • nuxeo.streams.failure: Total number of computation threads terminated because of failure for the node (all computations)

Each computation has the following metrics, the computation name being a dimension, for instance audit/writer, bulk/csvExport ...

  • nuxeo.streams.computation.failure: Count the number of computation threads terminated by a failure
  • nuxeo.streams.computation.skippedRecord: Count the number of record skipped after failure, the computation thread is not terminated
  • nuxeo.streams.computation.processRecord: Timer around processing of incoming record
  • nuxeo.streams.computation.processTimer: Timer around the computation timer processing
  • nuxeo.streams.computation.running: Number of active computation thread processing records or timers

All these metrics are local to each Nuxeo node.

The following metrics represent the lag and latencies of computations, these metrics are global to the Nuxeo cluster and have 2 dimensions:

  • stream obviously the stream name like audit/audit or bulk/command -group the name of the consumer group which the computation name like audit/writer or bulk/scroller

  • Number of records between the end of the stream and position of the consumer group

  • Offset of the consumer group on this stream
  • Offset of the last record in the stream
  • Latency of consumer group when there is a lag

Understanding the Lag and Latency Metrics

Given a producer that appends 3 records in a stream source:

  • record1 at time t1, offset 1
  • record2 at time t2, offset 2
  • record3 at time t3, offset 3

A processor is started with a computation C1 reading from the previous stream, until the first record of the stream has been processed there is no lag or latency reported.

Once the first record has been processed we have the following metrics for group: C1, stream: source:

  • pos: offset 1
  • end: offset 3
  • lag: 2 (which is end - pos)
  • latency: now() - t1

After processing the second record we have:

  • pos: offset 2
  • end: offset 3
  • lag: 1
  • latency: now() - t2

After the third and last record, there is no more lag or latency, the computation has caught up with the producer:

  • pos: offset 3
  • end: offset 3
  • lag: 0
  • latency: 0

Nuxeo Transactions

  • nuxeo.transactions.concurrency: Current number of concurrent transaction
  • nuxeo.transactions.concurrency.max: Maximum registered concurrent transactions
  • nuxeo.transactions.rollbacks: Number of transaction rollbacks
  • nuxeo.transactions.timer: Timer on all transactions

Nuxeo Web

Metrics reported by the Web NuxeoAuthenticationFilter:

  • nuxeo.web.authentication.logged-users: Number of users successfully logged and that didn't logout explicitly, the session timeout is not taken into account
  • nuxeo.web.authentication.requests.concurrency: Current concurrent requests in the filter
  • nuxeo.web.authentication.requests.concurrency.max: Registered maximum number of concurrency
  • nuxeo.web.authentication.requests.timer: Timer on the request web filter

Nuxeo WorkManager

The WorkManager service provides metrics by queue (default, fulltextUpdater ...)

Some are global to the Nuxeo cluster:

  • Number of scheduled Work
  • Number of completed Work
  • Number of running Work
  • number of canceled Work

Some are local to the node:

  • Number of Work in failure moved in the dead letter queue
  • Timer for Work execution


Can be disabled using:


Some metrics depends on the chosen garbage collector or the version of the JVM:

  • jvm.buffers.mapped.capacity
  • jvm.buffers.mapped.count
  • jvm.buffers.mapped.used
  • jvm.files
  • jvm.garbage.G1*
  • jvm.memory.heap.committed
  • jvm.memory.heap.init
  • jvm.memory.heap.max
  • jvm.memory.heap.usage
  • jvm.memory.heap.used
  • jvm.memory.non-heap.committed
  • jvm.memory.non-heap.init
  • jvm.memory.non-heap.max
  • jvm.memory.non-heap.usage
  • jvm.memory.non-heap.used
  • jvm.threads.blocked.count
  • jvm.threads.count
  • jvm.threads.daemon.count
  • jvm.threads.deadlock.count
  • jvm.threads.deadlocks
  • jvm.threads.runnable.count
  • jvm.threads.terminated.count
  • jvm.threads.timed_waiting.count
  • jvm.threads.waiting.count


Can be disabled using:

  • tomcat.activeSessions
  • tomcat.bytesReceived
  • tomcat.bytesSent
  • tomcat.currentThreadBusy
  • tomcat.currentThreadCount
  • tomcat.errorCount
  • tomcat.jdbc-numActive
  • tomcat.jdbc-numIdle
  • tomcat.processingTime
  • tomcat.requestCount


Can be disabled using:

  • org.apache.logging.log4j.core.Appender.all: Count number of log traced (all level)
  • org.apache.logging.log4j.core.Appender.warn: Count the number of log at level WARN
  • org.apache.logging.log4j.core.Appender.error: Count the number of log at level ERROR
  • org.apache.logging.log4j.core.Appender.fatal: Count the number of log at FATAL level

Monitoring Dashboard

The above metrics can be rendered in dashboards depending on the chosen monitoring systems.


Grafana can be used to render Graphite or Prometheus metrics.

The Nuxeo Stacks tool that generates dev and testing environment for Nuxeo provides a Grafana dashboard using a Graphite backend.

The JSON dashboard can be found in its sources.



The same dashboard can be build using Datadog.