Monitoring Kafka with JMX

Java Management Extensions (JMX) and Managed Beans (MBeans) are technologies for monitoring and managing Java applications, and they are enabled by default for Kafka and provide metrics for its components; brokers, controllers, producers, and consumers. The next sections describe how to configure JMX and verify that you have configured it correctly. You can also jump to searching for a metric.

Tip

Confluent offers some alternatives to using JMX monitoring.

• Health+: Consider monitoring and managing your environment with Confluent Health+. Ensure the health of your clusters and minimize business disruption with intelligent alerts, monitoring, and proactive support based on best practices created by the inventors of Kafka.
• Confluent Control Center: You can deploy Control Center for out-of-the-box Kafka cluster monitoring so you don’t have to build your own monitoring system. Control Center makes it easy to manage the entire Confluent Platform deployment. Control Center is a web-based application that allows you to manage your cluster and to alert on triggers. Additionally, Control Center measures how long messages take to be delivered, and determines the source of any issues in your cluster.

Configure JMX

You can use the following JVM environment variables to configure JMX monitoring when you start Kafka or use Java system properties to enable remote JMX programmatically.

JMX_PORT

The port that JMX listens on for incoming connections.

JMX_HOSTNAME

The hostname associated with locally created remote objects.

KAFKA_JMX_OPTS

JMX options. Use this variable to override the default JMX options such as whether authentication is enabled. The default options are set as follows: -Djava.rmi.server.hostname=127.0.0.1 -Dcom.sun.management.jmxremote=true -Dcom.sun.management.jmxremote.authenticate=false  -Dcom.sun.management.jmxremote.ssl=false

• server.hostname Specifies the host a JMX client connects to. The default is localhost (127.0.0.1)
• jmxremote=true Enables the JMX remote agent and enables the connector to listen through a specific port.
• jmxremote.authenticate=false Indicates that authentication is off by default.
• jmxremote.ssl=false- Indicates that TLS/SSL is off by default.

For example, to start Kafka, and specify a JMX port, you can use the following command:

JMX_PORT=2020 ./bin/kafka-server-start.sh ./etc/kafka/kraft/server.properties

For more on configuring JMX, see Monitoring and Management using JMX technology. For additional topics about monitoring, see the Related content section.

View MBeans with JConsole

To see JMX monitoring in action, you can start JConsole, a utility provided with Java.

To start JConsole, use the jconsole command, and connect to the Kafka process.

After JConsole starts, if Kafka is running locally, you will see it listed as a Local Process, and you can select it. Or if you are running Kafka remotely, such as in a Docker container, select Remote Process, enter the hostname and port you specified in your JMX configuration, and click Connect.

Enter a valid username and password, or if you have not configured authentication, you may be prompted to make an Insecure connection.

Once JConsole is running, you can select the MBeans tab and expand the folders to see the JMX events and attributes for those events.

You can also view JMX metrics with console tools such Jmxterm or export JMX metrics to other monitoring tools such as Prometheus. For a demo on how to use some popular monitoring tools with Confluent products, see JMX Monitoring Stacks on GitHub.

Configure security

Password authentication and TLS/SSL are disabled for JMX by default in Kafka, however in a production environment, you should enable authentication and TLS/SSL to prevent unauthorized users from accessing your brokers.

You override the default JMX settings to enable authentication and SSL.

To learn about how to secure JMX, follow the TLS/SSL and authentication sections in Monitoring and Management Using JMX Technology.

Configure other Confluent Platform components

Use the following environment variables to override the default JMX options such as authentication settings for other Confluent Platform components.

Component	Environment Variable
Confluent Control Center	CONTROL_CENTER_JMX_OPTS
REST Proxy	KAFKAREST_JMX_OPTS
ksqlDB	KSQL_JMX_OPTS
Rebalancer	REBALANCER_JMX_OPTS
Schema Registry	SCHEMA_REGISTRY_JMX_OPTS

Search for a metric

Broker metrics

There are many metrics reported at the broker and controller level that can be monitored and used to troubleshoot issues with your cluster. At minimum, you should monitor and set alerts on ActiveControllerCount, OfflinePartitionsCount, and UncleanLeaderElectionsPerSec.

clientSoftwareName/clientSoftwareVersion

Mbean: kafka.server:clientSoftwareName=(name),clientSoftwareVersion=(version),listener=(listener),networkProcessor=(processor-index),type=(type)

Name and version of client software in the brokers. For example, the Kafka 2.4 Java client produces the following MBean on the broker:

kafka.server:clientSoftwareName=apache-kafka-java,clientSoftwareVersion=2.4.0,listener=PLAINTEXT,networkProcessor=1,type=socket-server-metrics

RequestRateAndQueueTimeMs

MBean: kafka.controller:type=ControllerChannelManager,name=RequestRateAndQueueTimeMs,brokerId=([0-9]+)

The rate (requests per second) at which the controller takes requests from the queue of the given broker, and the time it takes for a request to stay in this queue before it is taken from the queue. ZooKeeper mode.

ElectionRateAndTimeMs

MBean: kafka.controller:type=ControllerStats,name=LeaderElectionRateAndTimeMs

Broker leader election rate and latency. This is non-zero when there are broker failures.

UncleanLeaderElectionsPerSec

MBean: kafka.controller:type=ControllerStats,name=UncleanLeaderElectionsPerSec

Unclean broker leader election rate. Should be 0.

MessageConversionsPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name={Produce|Fetch}MessageConversionsPerSec,topic=([-.\w]+)

Message format conversion rate, for Produce or Fetch requests, per topic. Omitting ‘topic={…}’ will yield the all-topic rate.

BytesInPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=BytesInPerSec,topic={topicName}

Byte incoming rate from the clients, per topic. Omitting ‘topic={…}’ will yield the all-topic rate.

BytesOutPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=BytesOutPerSec,topic={topicName}

Byte rate out to clients per topic. Omitting ‘topic={…}’ will yield the all-topic rate.

BytesRejectedPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=BytesRejectedPerSec,topic={topicName}

Rejected byte rate per topic, due to the record batch size being greater than max.message.bytes configuration. Omitting ‘topic={…}’ will yield the all-topic rate.

FailedFetchRequestsPerSec

Mbean: kafka.server:type=BrokerTopicMetrics,name=FailedFetchRequestsPerSec

Fetch request rate for requests that failed.

FailedProduceRequestsPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=FailedProduceRequestsPerSec

Produce request rate for requests that failed.

InvalidMagicNumberRecordsPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=InvalidMagicNumberRecordsPerSec

Message validation failure rate due to an invalid magic number. This should be 0.

InvalidMessageCrcRecordsPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=InvalidMessageCrcRecordsPerSec

Message validation failure rate due to incorrect Crc checksum

InvalidOffsetOrSequenceRecordsPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=InvalidOffsetOrSequenceRecordsPerSec

Message validation failure rate due to non-continuous offset or sequence number in batch. Normally this should be 0.

MessagesInPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=MessagesInPerSec,topic={topicName}

Incoming message rate per topic. Omitting ‘topic={…}’ will yield the all-topic rate.

NoKeyCompactedTopicRecordsPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=NoKeyCompactedTopicRecordsPerSec

Message validation failure rate due to no key specified for compacted topic. This should be 0.

ReassignmentBytesInPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=ReassignmentBytesInPerSec

Incoming byte rate of reassignment traffic.

ReassignmentBytesOutPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=ReassignmentBytesOutPerSec

Outgoing byte rate of reassignment traffic.

RemoteFetchBytesPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=RemoteFetchBytesPerSec,topic={topicName}

Rate of bytes read from remote storage per topic. Omitting ‘topic={…}’ will yield the all-topic rate.

RemoteFetchErrorsPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=RemoteFetchErrorsPerSec,topic={topicName}

Rate of read errors from remote storage per topic. Omitting ‘topic={…}’ will yield the all-topic rate.

RemoteFetchRequestsPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=RemoteFetchRequestsPerSec,topic={topicName}

Rate of read requests from remote storage per topic. Omitting ‘topic={…}’ will yield the all-topic rate.

ReplicationBytesInPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=ReplicationBytesInPerSec,topic={topicName}

Byte-in rate from other brokers per topic. Omitting ‘topic={…}’ will yield the all-topic rate.

ReplicationBytesOutPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=ReplicationBytesOutPerSec

Byte-out rate to other brokers.

TotalFetchRequestsPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=TotalFetchRequestsPerSec

Fetch request rate.

TotalProduceRequestsPerSec

MBean: kafka.server:type=BrokerTopicMetrics,name=TotalProduceRequestsPerSec

Produce request rate.

consumer-lag-offsets

MBean: kafka.server:type=consumer-lag-emitter,name=consumer-lag-offsets,consumer-group={groupName},client-id={clientID},
 member={memberID},group-instance-id={groupID},topic={topicName},partition={partitionID}

   The difference between the last offset stored by the broker and the last committed offset for a specific consumer group name, client ID, member ID, group instance ID, topic name, and partition ID. This metric provides the consumer lag in offsets only and does not report latency.

PurgatorySize (produce)

MBean: kafka.server:type=DelayedOperationPurgatory,delayedOperation=Produce,name=PurgatorySize

Number of requests waiting in the producer purgatory. This should be non-zero when acks=all is used on the producer.

PurgatorySize (fetch)

MBean: kafka.server:type=DelayedOperationPurgatory,delayedOperation=Fetch,name=PurgatorySize

Number of requests waiting in the fetch purgatory. This is high if consumers use a large value for fetch.wait.max.ms

ConsumerLag

Mbean: kafka.server:type=FetcherLagMetrics,name=ConsumerLag,clientId=([-.\w]+),topic={topicName},partition=([0-9]+)

Lag in number of messages per follower replica. This is useful to know if the replica is slow or has stopped replicating from the leader and if the associated brokers need to be removed from the In-Sync Replicas list.

linux-disk-read-bytes

Mbean: kafka.server:type=KafkaServer,name=linux-disk-read-bytes

The total number of bytes read by the broker process, including reads from all disks. The total doesn’t include reads from page cache. Available only on Linux-based systems.

linux-disk-write-bytes

Mbean: kafka.server:type=KafkaServer,name=linux-disk-write-bytes

The total number of bytes written by the broker process, including writes from all disks. Available only on Linux-based systems.

UnderMinIsrPartitionCount

Mbean: kafka.server:type=ReplicaManager,name=UnderMinIsrPartitionCount

Number of partitions whose in-sync replicas count is less than minIsr.

UnderReplicatedPartitions

Mbean: kafka.server:type=ReplicaManager,name=UnderReplicatedPartitions

Number of under-replicated partitions (| ISR | < | current replicas |). Replicas that are added as part of a reassignment will not count toward this value. Alert if the value is greater than 0.

ReassigningPartitions

Mbean: kafka.server:type=ReplicaManager,name=ReassigningPartitions

Number of reassigning partitions.

UnderMinIsr

MBean: kafka.cluster:type=Partition,topic={topic},name=UnderMinIsr,partition={partition}

Number of partitions whose in-sync replicas count is less than minIsr. These partitions will be unavailable to producers who use acks=all.

InSyncReplicasCount

MBean: kafka.cluster:type=Partition,topic={topic},name=InSyncReplicasCount,partition={partition}

A gauge metric that indicates the in-sync replica count per topic partition leader.

AtMinIsr

MBean: kafka.cluster:type=Partition,topic={topic}name=AtMinIsr,partition={partition}

Number of partitions whose in-sync replicas count is equal to the minIsr value.

ReplicasCount

MBean: kafka.cluster:type=Partition,topic={topic}:name=ReplicasCount,partition={partition}

A gauge metric that indicates the replica count per topic partition leader.

UnderReplicated

MBean: kafka.cluster:type=Partition,topic={topic}::name=UnderReplicated,partition={partition}

Number of partitions that are under replicated meaning the number of in-sync replicas is less than the replica count.

PartitionCount

MBean: kafka.server:type=ReplicaManager,name=PartitionCount

Number of partitions on this broker. This should be mostly even across all brokers.

LeaderCount

MBean: kafka.server:type=ReplicaManager,name=LeaderCount

Number of leaders on this broker. This should be mostly even across all brokers. If not, set auto.leader.rebalance.enable to true on all brokers in the cluster.

RequestHandlerAvgIdlePercent

MBean: kafka.server:type=KafkaRequestHandlerPool,name=RequestHandlerAvgIdlePercent

Average fraction of time the request handler threads are idle. Values are between 0 meaning all resources are used and 1 meaning all resources are available.

IsrShrinksPerSec

MBean: kafka.server:type=ReplicaManager,name=IsrShrinksPerSec

Measures the reduction of in-sync replicas per second. If a broker goes down, ISR for some of the partitions will shrink. When that broker is up again, ISR will be expanded once the replicas are fully caught up. Other than that, the expected value for both ISR shrink rate and expansion rate is 0.

IsrExpandsPerSec

MBean: kafka.server:type=ReplicaManager,name=IsrExpandsPerSec

Measures the expansion of in-sync replicas per second. When a broker is brought up after a failure, it starts catching up by reading from the leader. Once it is caught up, it gets added back to the ISR.

DelayQueueSize

MBean: kafka.server:type=Produce,name=DelayQueueSize

Number of producer clients currently being throttled. The value can be any number greater than or equal to 0.

Important

For monitoring quota applications and throttled clients, use the Bandwidth quota, and Request quota metrics.

Bandwidth quota

MBean: kafka.server:type={Produce|Fetch},user={userName},client-id={clientId}

Use the attributes of this metric to measure the bandwidth quota. This metric has the following attributes:

• throttle-time: the amount of time in milliseconds the client was throttled. Ideally = 0.
• byte-rate: the data produce/consume rate of the client in bytes/sec.
  • For (user, client-id) quotas, specify both user and client-id.
  • If a per-client-id quota is applied to the client, do not specify user.
  • If a per-user quota is applied, do not specify client-id.

Request quota

MBean: kafka.server:type=Request,user={userName},client-id={clientId}

Use the attributes of this metric to measure request quota. This metric has the following attributes:

• throttle-time: the amount of time in milliseconds the client was throttled. Ideally = 0.
• request-time: the percentage of time spent in broker network and I/O threads to process requests from client group.
  • For (user, client-id) quotas, specify both user and client-id.
  • If a per-client-id quota is applied to the client, do not specify user.
  • If a per-user quota is applied, do not specify client-id.

connection-count

MBean: kafka.server:type=socket-server-metrics,listener={listener_name},networkProcessor={#},name=connection-count

Number of currently open connections to the broker.

connection-creation-rate

MBean: kafka.server:type=socket-server-metrics,listener={listener_name},networkProcessor={#},name=connection-creation-rate

Number of new connections established per second.

KRaft broker metrics

These metrics are only produced for a broker when running in KRaft mode.

last-applied-record-offset

MBean: kafka.server:type=broker-metadata-metrics,name=last-applied-record-offset

The offset of the last record from the cluster metadata partition that was applied by the broker.

last-applied-record-timestamp

MBean: kafka.server:type=broker-metadata-metrics,name=last-applied-record-timestamp

The timestamp of the last record from the cluster metadata partition that was applied by the broker.

last-applied-record-lag-ms

MBean: kafka.server:type=broker-metadata-metrics,name=last-applied-record-lag-ms

The difference between now and the timestamp of the last record from the cluster metadata partition that was applied by the broker.

metadata-load-error-count

MBean: kafka.server:type=broker-metadata-metrics,name=metadata-load-error-count

The number of errors encountered by the BrokerMetadataListener while loading the metadata log and generating a new MetadataDelta based on it.

metadata-apply-error-count

MBean: kafka.server:type=broker-metadata-metrics,name=metadata-apply-error-count

The number of errors encountered by the BrokerMetadataPublisher while applying a new MetadataImage based on the latest MetadataDelta.

KRaft Quorum metrics

These metrics are reported on both controllers and brokers in a KRaft cluster.

current-state

MBean: kafka.server:type=raft-metrics,name=current-state

The current state of this member; possible values are leader, candidate, voted, follower, unattached, observer.

current-leader

Mbean: kafka.server:type=raft-metrics,name=current-leader

The current quorum leader’s id; -1 indicates unknown.

current-vote

Mbean: kafka.server:type=raft-metrics,name=current-vote

The current voted leader’s id; -1 indicates not voted for anyone.

current-epoch

Mbean: kafka.server:type=raft-metrics,name=current-epoch

The current quorum epoch.

high-watermark

Mbean: kafka.server:type=raft-metrics,name=high-watermark

The high watermark maintained on this member; -1 if it is unknown.

log-end-offset

Mbean: kafka.server:type=raft-metrics,name=log-end-offset

The current raft log end offset.

number-unknown-voter-connections

Mbean: kafka.server:type=raft-metrics,name=number-unknown-voter-connections

Number of unknown voters whose connection information is not cached. This value of this metric is always 0.

commit-latency-avg

Mbean: kafka.server:type=raft-metrics,name=commit-latency-avg

The average time in milliseconds to commit an entry in the raft log.

commit-latency-max

Mbean: kafka.server:type=raft-metrics,name=commit-latency-max

The maximum time in milliseconds to commit an entry in the raft log.

election-latency-avg

Mbean: kafka.server:type=raft-metrics,name=election-latency-avg

The average time in milliseconds spent on electing a new leader.

election-latency-max

Mbean: kafka.server:type=raft-metrics,name=election-latency-max

The maximum time in milliseconds spent on electing a new leader.

fetch-records-rate

Mbean: kafka.server:type=raft-metrics,name=fetch-records-rate

The average number of records fetched from the leader of the raft quorum.

append-records-rate

Mbean: kafka.server:type=raft-metrics,name=append-records-rate

The average number of records appended per sec by the leader of the raft quorum.

poll-idle-ratio-avg

Mbean: kafka.server:type=raft-metrics,name=poll-idle-ratio-avg

The average fraction of time the client’s poll() is idle as opposed to waiting for the user code to process records.

Controller metrics

The following metrics are exposed by a controller, which can be a broker controller in ZooKeeper mode or a KRaft controller in KRaft mode. For more about monitoring KRaft, see Monitor KRaft.

EventQueueProcessingTimeMs

MBean: kafka.controller:type=ControllerEventManager,name=EventQueueProcessingTimeMs

A Histogram of the time in milliseconds that requests spent being processed in the Controller Event Queue.

EventQueueSize

MBean: kafka.controller:type=ControllerEventManager,name=EventQueueSize

Size of the controller’s event queue.

EventQueueTimeMs

MBean: kafka.controller:type=ControllerEventManager,name=EventQueueTimeMs

Time that takes for any event (except the Idle event) to wait in the controller event queue before being processed.

ActiveBrokerCount

Mbean: kafka.controller:type=KafkaController,name=ActiveBrokerCount

The number of active brokers as observed by this controller. This metric is produced for both ZooKeeper and KRaft mode.

ActiveControllerCount

MBean: kafka.controller:type=KafkaController,name=ActiveControllerCount

For KRaft, the number of active controllers in the cluster. Valid values are ‘0’ or ‘1’. For ZooKeeper, indicates whether the broker is the controller broker. Alert if the aggregated sum across all brokers in the cluster is anything other than 1 because there should be exactly one controller per cluster.

FencedBrokerCount

MBean: kafka.controller:type=KafkaController,name=FencedBrokerCount

In KRaft mode, the number of fenced, but registered brokers as observed by this controller. This metric is always 0 in ZooKeeper mode.

GlobalPartitionCount

MBean: kafka.controller:type=KafkaController,name=GlobalPartitionCount

Number of partitions across all topics in the cluster.

GlobalTopicCount

MBean: kafka.controller:type=KafkaController,name=GlobalTopicCount

The number of global partitions as observed by this Controller.

LastAppliedRecordLagMs

MBean: kafka.controller:type=KafkaController,name=LastAppliedRecordLagMs

The difference between now and the timestamp of the last record from the cluster metadata partition that was applied by the controller. For active controllers the value of this lag is always zero.

LastAppliedRecordOffset

MBean: kafka.controller:type=KafkaController,name=LastAppliedRecordOffset

The offset of the last record from the cluster metadata partition that was applied by the Controller.

LastAppliedRecordTimestamp

MBean: kafka.controller:type=KafkaController,name=LastAppliedRecordTimestamp

The timestamp of the last record from the cluster metadata partition that was applied by the controller.

LastCommittedRecordOffset

MBean: kafka.controller:type=KafkaController,name=LastCommittedRecordOffset

The offset of the last record committed to this Controller.

MetadataErrorCount

MBean: kafka.controller:type=KafkaController,name=MetadataErrorCount

The number of times this controller node has encountered an error during metadata log processing.

OfflinePartitionsCount

MBean: kafka.controller:type=KafkaController,name=OfflinePartitionsCount,partition={partition}

Number of partitions that don’t have an active leader and are therefore not writable or readable. Alert if value is greater than 0.

PreferredReplicaImbalanceCount

Mbean: kafka.controller:type=KafkaController,name=PreferredReplicaImbalanceCount

The count of topic partitions for which the leader is not the preferred leader.

ReplicasIneligibleToDeleteCount

MBean: kafka.controller:type=KafkaController,name=ReplicasIneligibleToDeleteCount

Number of ineligible pending replica deletes.

ReplicasToDeleteCount

MBean: kafka.controller:type=KafkaController,name=ReplicasToDeleteCount

Pending replica deletes.

TopicsIneligibleToDeleteCount

MBean: kafka.controller:type=KafkaController,name=TopicsIneligibleToDeleteCount

Ineligible pending topic deletes.

TopicsToDeleteCount

MBean: kafka.controller:type=KafkaController,name=TopicsToDeleteCount

Pending topic deletes.

Log metrics

The following section contains metrics for logs, log cleaners, and log cleaner managers. A log directory is a directory on disk that contains one or more Kafka log segments. When a Kafka broker starts up, it registers all of the log directories that it finds on its local disk with the log manager. The log manager is responsible for managing the creation, deletion, and cleaning of log segments across all registered log directories.

LogEndOffset

MBean: kafka.log:type=Log,name=LogEndOffset

The offset of the last message in a partition. Use with LogStartOffset to calculate the current message count for a topic.

LogStartOffset

MBean: kafka.log:type=Log,name=LogStartOffset

The offset of the first message in a partition. Use with LogEndOffset to calculate the current message count for a topic.

NumLogSegments

MBean: kafka.log:type=Log:name=NumLogSegments

The number of log segments that currently exist for a given partition.

Size

MBean: kafka.log:type=Log,name=Size

A metric for the total size in bytes of all log segments that belong to a given partition.

DeadThreadCount

MBean: kafka.log:type=LogCleaner,name=DeadThreadCount

Provides the number of dead threads for the process.

cleaner-recopy-percent

MBean: kafka.log:type=LogCleaner,name=cleaner-recopy-percent

A metric to track the recopy rate of each thread’s last cleaning

max-buffer-utilization-percent

MBean: kafka.log:type=LogCleaner,name=max-buffer-utilization-percent

A metric to track the maximum utilization of any thread’s buffer in the last cleaning.

max-clean-time-secs

MBean: kafka.log:type=LogCleaner,name=max-clean-time-secs

A metric to track the maximum cleaning time for the last cleaning from each thread.

max-compaction-delay-secs

MBean: kafka.log:type=LogCleaner,name=max-compaction-delay-secs

A metric that provides the maximum delay, in seconds, that the log cleaner will wait before compacting a log segment.

compacted-partition-bytes

MBean: kafka.log:type=LogCleanerManager,name=compacted-partition-bytes

A gauge metric that provides compacted data in each partition.

compacted-partition-local-bytes

MBean: kafka.log:type=LogCleanerManager,name=compacted-partition-local-bytes

A gauge metric that provides local compacted data in each partition. Confluent Server only.

compacted-partition-tiered-bytes

MBean: kafka.log:type=LogCleanerManager,name=compacted-partition-tiered-bytes

A gauge metric that provides compacted data in each partition when using tiered storage. Confluent Server only.

max-dirty-percent

MBean: kafka.log:type=LogCleanerManager,name=max-dirty-percent

A gauge metric that provides the maximum percentage of the log segment that can contain dirty messages before the log cleaner will begin cleaning it.

time-since-last-run-ms

MBean: kafka.log:type=LogCleanerManager,name=time-since-last-run-ms

A gauge metric that provides the time, in milliseconds, since the log cleaner last ran.

OfflineLogDirectoryCount

MBean: kafka.log:type=LogManager,name=OfflineLogDirectoryCount

A metric that describes the number of log directories that are registered with the log manager, but are currently offline.

LogFlushRateAndTimeMs

MBean: kafka.log:type=LogFlushStats,name=LogFlushRateAndTimeMs

Log flush rate and time.

uncleanable-bytes

MBean: kafka.log:logDirectory="{/log-directory}":type=LogCleanerManager:name=uncleanable-bytes

A metric that provides information about the total number of bytes in log segments for a specified log directory that cannot be cleaned by the log cleaner due to retention policy or other configuration settings.

uncleanable-partitions-count

MBean: kafka.log:logDirectory="{/log-directory}":type=LogCleanerManager:name=uncleanable-partitions-count

A gauge metric that tracks the number of partitions marked as uncleanable for each log directory.

LogDirectoryOffline

MBean: kafka.log:logDirectory="{/log-directory}":type=LogManager,name=LogDirectoryOffline

A metric that provides the number of log directories that are currently offline and not available for use by the Kafka broker.

SegmentAppendTimeMs

MBean: kafka.log:type=SegmentStats,name=SegmentAppendTimeMs

The time in milliseconds to append a record to the log segment. Available on Confluent Server only.

OffsetIndexAppendTimeMs

MBean: kafka.log:type=SegmentStats,name=OffsetIndexAppendTimeMs

The time in milliseconds to append an entry to the log segment offset index. The offset index maps from logical offsets to physical file positions. Available on Confluent Server only.

TimestampIndexAppendTimeMs

MBean: kafka.log:type=SegmentStats,name=TimestampIndexAppendTimeMs

The time in milliseconds to append an entry to the log segment timestamp index. Available on Confluent Server only.

Network metrics

Kafka brokers can generate a lot of network traffic because they collect and distribute data for processing. You can use the following metrics to help evaluate whether your Kafka deployment is communicating efficiently.

RequestQueueSize

MBean: kafka.network:type=RequestChannel,name=RequestQueueSize

Size of the request queue. A congested request queue will not be able to process incoming or outgoing requests.

ResponseQueueSize

MBean: kafka.network:type=RequestChannel,name=ResponseQueueSize

Size of the response queue. The response queue is unbounded. A congested response queue can result in delayed response times and memory pressure on the broker.

ErrorsPerSec

MBean: kafka.network:type=RequestMetrics,name=ErrorsPerSec,request={requestType},error={error-code}

Indicates the number of errors in responses counted per-request-type, per-error-code. If a response contains multiple errors, all are counted. error=NONE indicates successful responses.

LocalTimeMs

MBean: kafka.network:type=RequestMetrics,name=LocalTimeMs,request={Produce|FetchConsumer|FetchFollower}

Time in milliseconds the request is processed at the leader.

MessageConversionsTimeMs

MBean: kafka.network:type=RequestMetrics,name=MessageConversionsTimeMs,request={Produce|Fetch}

Time in milliseconds spent on message format conversions.

RemoteTimeMs

MBean: kafka.network:type=RequestMetrics,name=RemoteTimeMs,request={Produce|FetchConsumer|FetchFollower}

Time in milliseconds the request waits for the follower. This is non-zero for produce requests when ack=-1 or acks=all.

RequestBytes

MBean: kafka.network:type=RequestMetrics,name=RequestBytes,request={requestType}

Request size in bytes.

RequestQueueTimeMs

MBean: kafka.network:type=RequestMetrics,name=RequestQueueTimeMs,request={Produce|FetchConsumer|FetchFollower}

Time the request waits in the request queue.

RequestsPerSec

MBean: kafka.network:type=RequestMetrics,name=RequestsPerSec,request={Produce|FetchConsumer|FetchFollower},version=([0-9]+

The request rate. version refers to the API version of the request type. To get the total count for a specific request type, make sure that JMX monitoring tools aggregate across different versions.

ResponseSendTimeMs

MBean: kafka.network:type=RequestMetrics,name=ResponseSendTimeMs,request={Produce|FetchConsumer|FetchFollower}

Time to send the response.

TemporaryMemoryBytes

MBean: kafka.network:type=RequestMetrics,name=TemporaryMemoryBytes,request={Produce|Fetch}

Temporary memory, in bytes, used for message format conversions and decompression.

TotalTimeMs

MBean: kafka.network:type=RequestMetrics,name=TotalTimeMs,request={Produce|FetchConsumer|FetchFollower}

Total time in milliseconds to serve the specified request. - Produce: requests from producers to send data - FetchConsumer: requests from consumers to get data - FetchFollower: requests from follower brokers that are the followers of a partition to get new data

ExpiredConnectionsKilledCount

MBean: kafka.network:type=SocketServer,name=ExpiredConnectionsKilledCount

The total number of connections disconnected, across all processors, due to a client not re-authenticating and then using the connection beyond its expiration time for anything other than re-authentication. Ideally 0 when re-authentication is enabled, implying there are no longer any older, pre-2.2.0 clients connecting to this broker

NetworkProcessorAvgIdlePercent

MBean: kafka.network:type=SocketServer,name=NetworkProcessorAvgIdlePercent

Average fraction of time the network processor threads are idle. Values are between 0 (all resources are used) and 1 (all resources are available).Ideally this is less than 0.3.

ZooKeeper metrics

Important

As of Confluent Platform 7.5, ZooKeeper is deprecated for new deployments. Confluent recommends KRaft mode for new deployments. For more information, see KRaft Overview.

ZooKeeper state transition counts are exposed as metrics, which can help to spot problems with your cluster. For example, such as broker connections to ZooKeeper. The metrics show the transitions rate per second for each one of the possible states. Here is the list of the counters we expose, one for each possible ZooKeeper client state.

ZooKeeperDisconnectsPerSec

MBean: kafka.server:type=SessionExpireListener,name=ZooKeeperDisconnectsPerSec

The ZooKeeper client is currently disconnected from the ensemble. The client lost its previous connection to a server and it is currently trying to reconnect. The session is not necessarily expired. Note that this metric tells you if the broker is disconnecting, but not if ZooKeeper is down. If you are checking system health, ZooKeeperExpiresPerSec is a better metric to help you determine this.

ZooKeeperExpiresPerSec

MBean: kafka.server:type=SessionExpireListener,name=ZooKeeperExpiresPerSec

The ZooKeeper session has expired. Note that when a session expires it could result in leader changes or possibly a new controller. You should monitor the number of these events across a Kafka cluster and if the overall number is high, you can do the following:

1. Check the health of your network
2. Check for garbage collection issues and tune it accordingly
3. If necessary, increase the session time out by setting the value of zookeeper.session.timeout.ms.

Following are additional ZooKeeper metrics you can optionally observe on a Kafka broker.

ZooKeeperSyncConnectsPerSec

MBean: kafka.server:type=SessionExpireListener,name=ZooKeeperSyncConnectsPerSec

ZooKeeper client is connected to the ensemble and ready to execute operations.

ZooKeeperAuthFailuresPerSec

MBean: kafka.server:type=SessionExpireListener,name=ZooKeeperAuthFailuresPerSec

An attempt to connect to the ensemble failed because the client has not provided correct credentials.

ZooKeeperReadOnlyConnectsPerSec

MBean: kafka.server:type=SessionExpireListener,name=ZooKeeperReadOnlyConnectsPerSec

The server the client is connected to is currently LOOKING, which means that it is neither FOLLOWING nor LEADING. Consequently, the client can only read the ZooKeeper state, but not make any changes (create, delete, or set the data of znodes).

ZooKeeperSaslAuthenticationsPerSec

MBean: kafka.server:type=SessionExpireListener,name=ZooKeeperSaslAuthenticationsPerSec

Client has successfully authenticated.

SessionState

MBean: kafka.server:type=SessionExpireListener,name=SessionState

Connection status of broker’s ZooKeeper session. Expected value is CONNECTED.

Producer metrics

The following metrics are available on a producer instance. These metrics are attributes on the associated MBean.

batch-size-avg

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average number of bytes sent per partition per-request. Global request metric.

batch-size-max

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The max number of bytes sent per partition per-request. Global request metric.

batch-split-rate

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average number of batch splits per second. Global request metric.

batch-split-total

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The total number of batch splits. Global request metric.

compression-rate-avg

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average compression rate of record batches, defined as the average ratio of the compressed batch size over the uncompressed size. Global request metric.

incoming-byte-rate

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average number of incoming bytes received per second from all servers. Global request metric.

metadata-age

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The age, in seconds, of the current producer metadata being used. Global request metric.

outgoing-byte-rate

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average number of bytes sent per second to all servers. Global request metric.

produce-throttle-time-avg

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average time in milliseconds a request was throttled by a broker. Global request metric.

produce-throttle-time-max

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The maximum time in milliseconds a request was throttled by a broker. Global request metric.

record-error-rate

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average per-second number of record sends that resulted in errors. Global request metric.

record-error-total

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The total number of record sends that resulted in errors. Global request metric.

record-queue-time-avg

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average time in milliseconds record batches spent in the send buffer. Global request metric.

record-queue-time-max

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The maximum time in milliseconds record batches spent in the send buffer. Global request metric.

record-retry-rate

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average per-second number of retried record sends. Global request metric.

record-retry-total

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The total number of retried record sends. Global request metric.

record-send-rate

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average number of records sent per second. Global request metric.

record-send-total

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The total number of records sent. Global request metric.

record-size-avg

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average record size. Global request metric.

record-size-max

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The maximum record size. Global request metric.

records-per-request-avg

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average number of records per request. Global request metric.

request-rate

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average number of requests sent per second. Global request metric.

requests-in-flight

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The current number of in-flight requests awaiting a response. Global request metric.

bufferpool-wait-time-ns-total

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The total time in nanoseconds a producer waits for space allocation. Global connection metric.

connection-close-rate

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

Connections closed per second in the window. Global connection metric.

connection-count

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The current number of active connections. Global connection metric.

connection-creation-rate

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

New connections established per second in the window. Global connection metric.

io-ratio

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The fraction of time the I/O thread spent doing I/O. Global connection metric.

io-time-ns-avg

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average length of time for I/O per select call in nanoseconds. Global connection metric.

io-time-ns-total

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The total time the I/O thread spent doing I/O in nanoseconds. Global connection metric.

io-wait-ratio

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The fraction of time the I/O thread spent waiting. Global connection metric.

io-wait-time-ns-avg

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The average length of time the I/O thread spent waiting for a socket ready for reads or writes in nanoseconds. Global connection metric.

io-wait-time-ns-total

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

The total length of time the I/O thread spent waiting for a socket ready for reads or writes in nanoseconds. Global connection metric.

select-rate

MBean: kafka.producer:type=producer-metrics,client-id={clientId}

Number of times the I/O layer checked for new I/O to perform per second. Global connection metric.

Besides the producer global request metrics, the following metrics are also available per broker:

incoming-byte-rate

MBean: kafka.producer:type=producer-node-metrics,client-id={clientId},node-id=([0-9]+)

The average number of bytes received per second from the broker.

outgoing-byte-rate

MBean: kafka.producer:type=producer-node-metrics,client-id={clientId},node-id=([0-9]+)

The average number of bytes sent per second to the broker.

request-size-avg

MBean: kafka.producer:type=producer-node-metrics,client-id={clientId},node-id=([0-9]+)

The average size of all requests in the window for a broker.

request-size-max

MBean: kafka.producer:type=producer-node-metrics,client-id={clientId},node-id=([0-9]+)

The maximum size of any request sent in the window for a broker.

request-rate

MBean: kafka.producer:type=producer-node-metrics,client-id={clientId},node-id=([0-9]+)

The average number of requests sent per second to the broker.

response-rate

MBean: kafka.producer:type=producer-node-metrics,client-id={clientId},node-id=([0-9]+)

The average number of responses received per second from the broker.

In addition to the producer global request metrics, the following metric attributes are available per topic:

byte-rate

MBean: kafka.producer:type=producer-topic-metrics,client-id="{client-id}",topic="{topic}

The average number of bytes sent per second for a topic.

byte-total

MBean: kafka.producer:type=producer-topic-metrics,client-id="{client-id}",topic="{topic}

The total number of bytes sent for a topic.

compression-rate

MBean: kafka.producer:type=producer-topic-metrics,client-id="{client-id}",topic="{topic}

The average compression rate of record batches for a topic. This is computed by averaging the compression ratios of the record batches. The compression ratio is computed by dividing the compressed batch size by the uncompressed size.

record-error-rate

MBean: kafka.producer:type=producer-topic-metrics,client-id="{client-id}",topic="{topic}

The average per-second number of record sends that resulted in errors for a topic.

record-error-total

MBean: kafka.producer:type=producer-topic-metrics,client-id="{client-id}",topic="{topic}

The total number of record sends that resulted in errors for a topic.

record-retry-rate

MBean: kafka.producer:type=producer-topic-metrics,client-id="{client-id}",topic="{topic}

The average per-second number of retried record sends for a topic.

record-retry-total

MBean: kafka.producer:type=producer-topic-metrics,client-id="{client-id}",topic="{topic}

The total number of retried record sends for a topic.

record-send-rate

MBean: kafka.producer:type=producer-topic-metrics,client-id="{client-id}",topic="{topic}

The average number of records sent per second for a topic.

record-send-total

MBean: kafka.producer:type=producer-topic-metrics,client-id="{client-id}",topic="{topic}

The total number of records sent for a topic.

Consumer metrics

A consumer instance exposes the following metrics. These metrics are attributes on the listed MBean.

bytes-consumed-rate

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The average number of bytes consumed per second.

bytes-consumed-total

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The total number of bytes consumed.

fetch-latency-avg

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The average time taken for a fetch request.

fetch-latency-max

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The max time taken for a fetch request.

fetch-rate

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The number of fetch requests per second.

fetch-size-avg

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The average number of bytes fetched per request.

fetch-size-max

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The maximum number of bytes fetched per request.

fetch-throttle-time-avg

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The average throttle time in ms. When quotas are enabled, the broker may delay fetch requests in order to throttle a consumer which has exceeded its limit. This metric indicates how throttling time has been added to fetch requests on average.

fetch-throttle-time-max

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The maximum throttle time in ms.

fetch-total

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The total number of fetch requests.

records-consumed-rate

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The average number of records consumed per second.

records-consumed-total

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The total number of records consumed.

records-lag-max

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The maximum lag in terms of number of records for any partition in this window. An increasing value over time is your best indication that the consumer group is not keeping up with the producers.

records-lead-min

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The minimum lead in terms of number of records for any partition in this window.

records-per-request-avg

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}"

The average number of records in each request.

bytes-consumed-rate

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}",topic="{topic}"

The average number of bytes consumed per second for a specific topic.

bytes-consumed-total

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}",topic="{topic}"

The total number of bytes consumed for a specific topic.

fetch-size-avg

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}",topic="{topic}"

The average number of bytes fetched per request for a specific topic.

fetch-size-max

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}",topic="{topic}"

The maximum number of bytes fetched per request for a specific topic.

records-consumed-rate

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}",topic="{topic}"

The average number of records consumed per second for a specific topic.

records-consumed-total

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}",topic="{topic}"

The total number of records consumed for a specific topic.

records-per-request-avg

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{client-id}",topic="{topic}"

The average number of records in each request for a specific topic.

preferred-read-replica

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,partition="{partition}",topic="{topic}",client-id="{client-id}

The current read replica for the partition, or -1 if reading from leader.

records-lag

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,partition="{partition}",topic="{topic}",client-id="{client-id}

The latest lag of the specified partition.

records-lag-avg

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,partition="{partition}",topic="{topic}",client-id="{client-id}

The average lag of the specified partition.

records-lag-max

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,partition="{partition}",topic="{topic}",client-id="{client-id}

The max lag of the specified partition.

records-lead

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,partition="{partition}",topic="{topic}",client-id="{client-id}

The latest lead of the specified partition.

records-lead-avg

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,partition="{partition}",topic="{topic}",client-id="{client-id}

The average lead of the specified partition.

records-lead-min

MBean: kafka.consumer:type=consumer-fetch-manager-metrics,partition="{partition}",topic="{topic}",client-id="{client-id}

The min lead of the specified partition.

incoming-byte-rate

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

The average number of incoming bytes received per second from all servers. Global request metric.

outgoing-byte-rate

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

The average number of outgoing bytes sent per second to all servers. Global request metric.

request-latency-avg

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

The average request latency in ms. Global request metric.

request-latency-max

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

The maximum request latency in ms. Global request metric.

request-rate

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

The average number of requests sent per second. Global request metric.

response-rate

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

The average number of responses received per second. Global request metric.

connection-count

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

The current number of active connections. Consumer global connection metric.

connection-creation-rate

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

New connections established per second in the window. Consumer global connection metric.

connection-close-rate

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

Connections closed per second in the window. Consumer global connection metric.

io-ratio

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

The fraction of time the I/O thread spent doing I/O. Consumer global connection metric.

io-time-ns-avg

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

The average length of time for I/O per select call in nanoseconds. Consumer global connection metric.

io-wait-ratio

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

The fraction of time the I/O thread spent waiting. Consumer global connection metric.

io-wait-time-ns-avg

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

The average length of time the I/O thread spent waiting for a socket ready for reads or writes in nanoseconds. Consumer global connection metric.

select-rate

MBean: kafka.consumer:type=consumer-metrics,client-id={clientId}

Number of times the I/O layer checked for new I/O to perform per second. Consumer global connection metric.

incoming-byte-rate

MBean: kafka.consumer:type=consumer-node-metrics,client-id={clientId},node-id=([0-9]+)

The average number of bytes received per second from the specified broker.

outgoing-byte-rate

MBean: kafka.consumer:type=consumer-node-metrics,client-id={clientId},node-id=([0-9]+)

The average number of bytes sent per second to the specified broker.

request-size-avg

MBean: kafka.consumer:type=consumer-node-metrics,client-id={clientId},node-id=([0-9]+)

The average size of all requests in the window for a specified broker.

request-size-max

MBean: kafka.consumer:type=consumer-node-metrics,client-id={clientId},node-id=([0-9]+)

The maximum size of any request sent in the window for a specified broker.

request-rate

MBean: kafka.consumer:type=consumer-node-metrics,client-id={clientId},node-id=([0-9]+)

The average number of requests sent per second to the specified broker.

response-rate

MBean: kafka.consumer:type=consumer-node-metrics,client-id={clientId},node-id=([0-9]+)

The average number of responses received per second from the specified broker.

Consumer group metrics

A consumer group exposes the following metrics. These metrics are attributes on the listed MBean.

assigned-partitions

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The number of partitions currently assigned to this consumer.

commit-latency-avg

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The average time taken for a commit request.

commit-latency-max

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The max time taken for a commit request.

commit-rate

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The number of commit calls per second.

commit-total

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The total number of commit calls.

failed-rebalance-rate-per-hour

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The number of failed group rebalance event per hour.

failed-rebalance-total

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The total number of failed group rebalances.

heartbeat-rate

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The average number of heartbeats per second. After a rebalance, the consumer sends heartbeats to the coordinator to keep itself active in the group. You can control this using the heartbeat.interval.ms setting for the consumer. You may see a lower rate than configured if the processing loop is taking more time to handle message batches. Usually this is OK as long as you see no increase in the join rate.

heartbeat-response-time-max

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The max time taken to receive a response to a heartbeat request.

heartbeat-total

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The total number of heartbeats.

join-rate

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The number of group joins per second. Group joining is the first phase of the rebalance protocol. A large value indicates that the consumer group is unstable and will likely be coupled with increased lag.

join-time-avg

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The average time taken for a group rejoin. This value can get as high as the configured session timeout for the consumer, but should usually be lower.

join-time-max

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The max time taken for a group rejoin. This value should not get much higher than the configured session timeout for the consumer.

join-total

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The total number of group joins.

last-heartbeat-seconds-ago

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The number of seconds since the last controller heartbeat.

last-rebalance-seconds-ago

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The number of seconds since the last rebalance event.

partitions-assigned-latency-avg

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The average time taken by the on-partitions-assigned rebalance listener callback.

partitions-assigned-latency-max

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The max time taken by the on-partitions-assigned rebalance listener callback.

partitions-lost-latency-avg

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The average time taken by the on-partitions-lost rebalance listener callback.

partitions-lost-latency-max

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The max time taken by the on-partitions-lost rebalance listener callback.

partitions-revoked-latency-avg

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The average time taken by the on-partitions-revoked rebalance listener callback.

partitions-revoked-latency-max

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The max time taken by the on-partitions-revoked rebalance listener callback.

rebalance-latency-avg

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The average time taken for a group rebalance.

rebalance-latency-max

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The max time taken for a group rebalance.

rebalance-latency-total

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The total time taken for group rebalances so far.

rebalance-rate-per-hour

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The number of group rebalance participated per hour.

rebalance-total

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The total number of group rebalances participated.

sync-rate

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The number of group syncs per second. Group synchronization is the second and last phase of the rebalance protocol. Similar to join-rate, a large value indicates group instability.

sync-time-avg

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The average time taken for a group sync.

sync-time-max

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The max time taken for a group sync.

sync-total

MBean: kafka.consumer:type=consumer-coordinator-metrics,client-id={clientId}

The total number of group syncs.

Audit metrics

These audit metrics are specific Confluent Enterprise. For information about how audit logging works, see Audit Log Concepts.

audit-log-rate-per-minute

MBean: confluent-audit-metrics:name=audit-log-rate-per-minute

The number of audit log entries created per minute. This metric is useful in cases where you need to know the number of audit logs created.

audit-log-fallback-rate-per-minute

MBean: confluent-audit-metrics:name=audit-log-fallback-rate-per-minute

The rate of audit log fallback entries per minute. If the audit logging mechanism tries to write to the Kafka topic and doesn’t succeed for any reason, it writes the JSON audit log message to log4j instead. This metric is useful in cases where you need to know the fallback rate of your audit logs.

authentication-audit-log-rate

MBean: confluent-audit-metrics:name=authentication-audit-log-rate

The number authentication audit log entries created per second.

authentication-audit-log-failure-rate

MBean: confluent-audit-metrics:name=authentication-audit-log-rate

The number of authentication failure entries per second.

authorization-audit-log-rate

MBean: confluent-audit-metrics:name=authentication-audit-log-failure-rate

The number of authorization audit log entries created per second.

authorization-audit-log-failure-rate

MBean: confluent-audit-metrics:name=authorization-audit-log-failure-rate

The number of authorization audit log failure entries per second.

kafka-request-event-audit-log-rate

MBean: confluent-audit-metrics:name=kafka-request-event-audit-log-rate

The number of Kafka request event audit log entries per second.

kafka-request-event-audit-log-failure-rate

MBean: confluent-audit-metrics:name=kafka-request-event-audit-log-failure-rate

The number of Kafka request event audit log failure entries per second.

Authorizer metrics

The following metrics are exposed by Confluent Enterprise. For more about Confluent Server Authorizer, see Configure Confluent Server Authorizer.

authorization-request-rate-per-minute

MBean: confluent-authorizer-metrics:name=authorization-request-rate-per-minute

The number of authorization requests per minute. This metric is useful in cases where you need to know the exact number of authorization requests per minute.

authorization-allowed-rate-per-minute

MBean: confluent-authorizer-metrics:name=authorization-allowed-rate-per-minute

The number of authorizations allowed per minute. This metric is useful in cases where you need to know the rate of authorizations allowed per minute.

authorization-denied-rate-per-minute

MBean: confluent-authorizer-metrics:name=authorization-denied-rate-per-minute

The number of authorizations denied per minute. This metric is useful in cases where you need to know the rate of authorizations denied per minute.

RBAC and LDAP metrics

The following metrics are exposed when you use RBAC and LDAP.

failure-start-seconds-ago

MBean: confluent.metadata:type=LdapGroupManager,name=failure-start-seconds-ago

The number of seconds since the last failed attempt to process metadata from the LDAP server. This is reset to zero on the next successful metadata refresh. This metric is available on brokers in the metadata cluster if LDAP group-based authorization is enabled. Alert if value is greater than zero.

writer-failure-start-seconds-ago

MBean: confluent.metadata:type=KafkaAuthStore,name=writer-failure-start-seconds-ago

The number of seconds since the last failure in the writer that updates authentication or authorization metadata on topics in the metadata cluster. This is reset to zero after the next successful metadata update. This metric is available on brokers in the metadata cluster. Alert if value is greater than zero.

reader-failure-start-seconds-ago

MBean: confluent.metadata:type=KafkaAuthStore,name=reader-failure-start-seconds-ago

The number of seconds since the last failure in the consumer that processes authentication or authorization metadata from the topics in the metadata cluster. This is reset to zero after the next successful metadata refresh. This metric is available on all brokers configured to use RBAC. Alert if value is greater than zero.

remote-failure-start-seconds-ago

Mbean: confluent.metadata:type=KafkaAuthStore,name=remote-failure-start-seconds-ago

The number of seconds since the last failure in the metadata service, for example, due to LDAP refresh failures for a long duration. This is reset to zero when notification of successful refresh from the metadata service is processed. This metric is available on all brokers configured to use RBAC. Alert if value is greater than zero.

active-writer-count

MBean: confluent.metadata:type=KafkaAuthStore,name=active-writer-count

Number of active writers in the metadata cluster. Alert if the sum is any number other than one because there should be exactly one writer in the metadata cluster.

metadata-status

MBean: confluent.metadata:type=KafkaAuthStore,name=metadata-status,topic=([-.\w]+),partition=([0-9]+)

Current status of metadata on each metadata topic partition. Value may be UNKNOWN, INITIALIZING, INITIALIZED or FAILED.

record-send-rate

MBean: confluent.metadata:type=KafkaAuthStore,name=record-send-rate,topic=([-.\w]+),partition=([0-9]+)

The average number of records sent per second to the metadata topic partitions.

record-error-rate

MBean: confluent.metadata:type=KafkaAuthStore,name=record-error-rate,topic=([-.\w]+),partition=([0-9]+)

The average number of record send attempts per second to the metadata topic partitions that failed.

rbac-role-bindings

MBean: confluent-auth-store-metrics:name=rbac-role-bindings-count

The number of role bindings defined. This metric is useful in cases where you need to know the exact number of role bindings that exist.

rbac-access-rules-count

MBean: confluent-auth-store-metrics:name=rbac-access-rules-count

The number of RBAC access rules defined. This metric is useful in cases where you need to know the exact number of RBAC access rules that exist. Access rules allow or deny access to specific resources within a specific scope, unlike role bindings, which assign an RBAC role for a specific resource to a specific principal.

acl-access-rules-count

MBean: confluent-auth-store-metrics:name=acl-access-rules-count

The number of ACL access rules defined. This metric is useful in cases where you need to know the exact number of ACLs that exist.

Related content

• Use JMX to Monitor Connect
• What are the top 5 Broker JMX metrics you should be watching (Confluent Support)
• Kafka Broker Performance Diagnostics (Confluent Support)
• For Confluent Platform with Docker, see Kafka Monitoring and Metrics Using JMX with Docker
• For details on configuring JMX with Connect, see Monitor Kafka Connect and Connectors
• For Confluent Platform: For a practical guide to optimizing your Kafka deployment for various service goals including throughput, latency, durability and availability, and useful metrics to monitor for performance and cluster health for on-prem Kafka clusters, see the Optimizing Your Apache Kafka Deployment whitepaper.
• For examples of JMX monitoring stacks that you can use to monitor Confluent Platform, see the jmx-monitoring-stacks repo
• For an example that showcases how to monitor Kafka client application and Confluent Cloud metrics, and steps through various failure scenarios to see how they are reflected in the provided metrics, see the Observability for Apache Kafka Clients to Confluent Cloud demo
• For Confluent Cloud: For a practical guide to configuring, monitoring, and optimizing your Kafka client applications, see Developing Client Applications on Confluent Cloud