The average number of bytes fetched per request. The average number of records consumed per second. The average number of records sent per second. Enabling SASL SCRAM authentication, 6.2.2. client APIs, the API documentation (and ultimately the source code) provides a more detailed Running Kafka Connect in standalone mode, 8.2.1. The average compression rate of record batches for a topic. The average time in milliseconds taken by this task to commit offsets. The average time in ms record batches spent in the send buffer. The total number of bytes sent for a topic. Specify the Bootstrap servers from which you want The total number of restore calls for this store. In the example below, the call to myDataProcess.doStuff(records) can cause The fraction of time an appender waits for space allocation. The total number of process operations called. Enabling Server-to-server authentication using DIGEST-MD5, 3.4.3. The total number of punctuate calls across all tasks. The average per-second number of records read from Kafka for this task belonging to the named sink connector in this worker. MBeans matching kafka.connect:type=sink-task-metrics,connector=*,task=*, 7.8.8. Configuring Kafka brokers to use the new inter-broker protocol version, 11.6. The average number of requests sent per second. The maximum execution time in ms for committing across all running tasks of this thread. These are metrics at the consumer level about connection to each broker. kafka.server:type=ReplicaManager,name=LeaderCount. The maximum amount of buffer memory the client can use (whether or not it is currently used). These are metrics at the topic level about topics the producer is sending messages to. MBeans matching kafka.connect:type=connect-worker-metrics, 7.8.4. Copyright 2021, Axual B.V. All other trademarks, servicemarks, and copyrights are the property of their The JConsole tool is distributed with the Java Development Kit (JDK). The total number of commit calls across all tasks.

The average per-second number of records output from the transformations and written to Kafka for this task belonging to the named source connector in this worker. In addition to the recommendations presented here, it is highly recommended that you also The average number of requests sent per second for a node. where multiple, subscribed members have access. The number of record processing errors in this task. The average request latency in ms for a node. Kafka Streams MBeans", Expand section "8.1. They assume you have sufficient Review the following collection of code snippets and recommendations regarding the use Zookeeper, the Kafka broker, Kafka Connect, and the Kafka clients all expose management information using Java Management Extensions (JMX). The total number of connector starts that failed. The average per-second number of retried record sends. The total number of offset commit completions that were completed successfully. clients. MBeans matching kafka.producer:type=producer-metrics,client-id=*,node-id=*, 7.6.3. The scripts provided with AMQ Streams (bin/kafka-server-start.sh and bin/connect-distributed.sh, and so on) use the KAFKA_JMX_OPTS environment variable to set these system properties. For information on Hadoop clusters, see Set up the Pentaho Server to connect to a Hadoop cluster. The average number of create operations per second. Specify the Hadoop cluster been any changes to how the APIs are used (setup, read, The average percentage of this workers connectors starts that failed. This is insecure because it allows JMX tools to connect from anywhere, with no authentication. Zookeeper request latency in milliseconds, kafka.server:type=ZooKeeperClientMetrics,name=ZooKeeperRequestLatencyMs. Data storage considerations", Collapse section "2.4. The maximum restore execution time in ns. MBeans matching kafka.producer:type=producer-metrics,client-id=*, 7.6.2. The following procedure explains how to disable the JMX agent for a Kafka broker. MBeans matching kafka.consumer:type=consumer-metrics,client-id=*,node-id=*, 7.7.3. The total number of records consumed for a topic. The average number of bytes sent per partition per-request. The average number of newly created tasks per second. The average number of records consumed per second for a topic. This metric is useful to monitor if the broker is a leader for a group of partitions. The average number of process operations per second. JMX works at the level of the JVM (Java Virtual Machine). The total number of destroy operations called. The total number of retried record sends. The average number of punctuates per second. The average time in milliseconds taken by this task to poll for a batch of source records. programming . called within a loop. Configuring Kafka Connect in distributed mode, 8.2.2. kafka.network:type=RequestMetrics,name=TemporaryMemoryBytes,request={Produce|Fetch}. Multiple servers can be specified if these are part of the same The total number of poll calls across all tasks. The number of offline log directories (for example, after a hardware failure). The unique Client identifier, used to identify and set up a durable connection Scaling Kafka clusters", Expand section "6.2. The average size of all requests in the window for a node. The number of attempted writes to the dead letter queue. You can use JConsole to connect to a local or remote JVM and discover and display management information from Java applications. Connections that were successfully authenticated using SASL or SSL. The average percentage of this tasks offset commit attempts that failed. to receive the Kafka streaming data. The maximum time taken by this task to put a batch of sinks records. The version of the connector class, as reported by the connector. The maximum lag in terms of number of records that the sink task is behind the consumers position for any topic partitions. In order to create a very basic producer application using mTLS, you need create the configuration for the Kafka Producer. behavior in many cases. It is recommended that you configure authentication and SSL to ensure that the remote JMX connection is secure.

The following MBeans will exist in Kafka consumer applications, including Kafka Streams applications and Kafka Connect with sink connectors. The name of the class containing the main method for the application. poll() method throws several exceptions. Similarly, it is recommended that you use one consumer and/or producer object per thread. kafka.network:type=RequestMetrics,name=RequestsPerSec,request={Produce|FetchConsumer|FetchFollower}. The category to which records are published. described below. Generating reassignment JSON files, 6.2.3. If the catch statements The total number of put-if-absent calls for this store. Reviewing the latest information could help avoid upgrade-related The minimum lead in terms of number of records for any partition in this window. Producer step publishes a stream of records to one Kafka new client id every time a new connection is established, which can severely increase MBeans matching kafka.consumer:type=consumer-fetch-manager-metrics,client-id=*,topic=*, 7.7.6. The total number of records output from the transformations and sent/put to this task belonging to the named sink connector in this worker, since the task was last restarted. Hitachi Vantara Corporation LLC 2022. further information on these input names, see the Apache Kafka documentation site: https://kafka.apache.org/documentation/. For more information about the system properties needed to do this, see the JMX documentation. Engage with our Red Hat Product Security team, access security updates, and ensure your environments are not exposed to any known security vulnerabilities. The total number of task starts that failed. Kafka Connect in standalone mode", Expand section "8.2. The total number of requests made for the request type per second. Most of this management information is in the form of metrics that are useful for monitoring the condition and performance of your Kafka cluster. The average time taken by this task to put a batch of sinks records. In addition, Cloudera recommends to set and use a fixed client ID for producers and topic. The time in milliseconds since this worker completed the most recent rebalance. MBeans matching kafka.connect:type=connector-task-metrics,connector=*,task=*, 7.8.7. kafka.server:type=BrokerTopicMetrics,name=MessagesInPerSec. MBeans matching kafka.connect:type=connect-metrics,client-id=*,node-id=*, 7.8.3. A Red Hat training course is available for Red Hat AMQ. The Produce, FetchConsumer, and FetchFollower request types each have their own MBeans. The max time taken for any fetch request. The number of failed writes to the dead letter queue.

Whether this worker is currently rebalancing. The average number of records in each request. Separate MBeans for all available request types are listed under the RemoteTimeMs node. Many other tools and monitoring products can be used to fetch the metrics using JMX and provide monitoring and alerting based on those metrics. The status of the connector task. configuration from which you want to retrieve the Kafka streaming data. can also cause various session timeouts to occur. MBeans matching kafka.connect:type=connect-metrics,client-id=*, 7.8.2. can cause performance issues. Like other Java applications, Kafka provides this management information through various managed beans, or MBeans. These are metrics at the topic level about the consumer's fetcher. The maximum number of records that have been produced by this task but not yet completely written to Kafka. With above configurations, instantiate a Kafka Producer and start sending records. The average execution time in ms for polling, across all running tasks of this thread. components. Monitoring your cluster using JMX", Expand section "7.5. This could be due to a kafka.server:type=BrokerTopicMetrics,name=BytesInPerSec. This recommendation is for the Java client only. The system properties for configuring JMX are the same, even though Kafka producer, consumer, and streams applications typically start the JVM in different ways.

The total number of retried record sends for a topic. The following table shows a selection of metrics that report information about the controller of the cluster. The average restore execution time in ns. Configuring connectors in distributed Kafka Connect, 9.1. These are metrics at the producer level about connection to each broker. combination of reasons: In such cases, consider having another thread or process doing the actual work and making You can prevent local JMX tools from connecting to the JVM (for example, for compliance reasons) by disabling the JMX agent for an AMQ Streams component. After reviewing the basic examples of a producer and consumer, prototyping your own designs Zookeeper authorization", Expand section "4.8. features a Kafka connection setup tab and a configuration property options tab. kafka.server:type=DelayedOperationPurgatory,name=PurgatorySize,delayedOperation=Fetch. These are metrics at the consumer level about the consumer group. The maximum number of bytes fetched per request. improve on scalability, debuggability, robustness, and maintainability. The average execution time in ms for processing, across all running tasks of this thread. For , enter the name of the port on which you want the Kafka broker to listen for JMX connections. In a MBeans matching kafka.consumer:type=consumer-metrics,client-id=*, 7.7.2. The rate at which data is fetched and read from the broker by consumers. Time, in milliseconds, spent on converting message formats. The rate at which new leader replicas are elected. The maximum punctuate execution time in ns. In the next step you will create a Java consumer application to use the data you just produced. The average number of bytes consumed per second for a topic. infrequent polling. The average percentage of this tasks offset commit attempts that succeeded. Creating more objects opens multiple ports per broker connection. MBeans matching kafka.producer:type=producer-topic-metrics,client-id=*,topic=*, 7.7.1. The length of time, in milliseconds, that the request waits in the response queue. kafka.server:type=SessionExpireListener,name=SessionState. Values of fields tenant, instance can be found in the on-boarding information, environment value is example in this Getting Started. maximum poll interval is reached. The average number of commit calls per second. The average time taken for a commit request. Metrics that express a rate or unit of time are provided as Yammer metrics. A lower value indicates that the workload of the broker is high. Zookeeper authorization", Collapse section "4.7. MBeans matching kafka.streams:type=stream-[store-scope]-metrics,client-id=*,task-id=*,[store-scope]-id=*, 7.9.5. Kafka Connect will contain the producer MBeans for source connectors and consumer MBeans for sink connectors in addition to those documented here. The documentation for the latest upstream release of Apache Kafka indicates if there have MBeans matching kafka.streams:type=stream-metrics,client-id=*, 7.9.2. The average number of bytes sent per second for a topic. One indicates that the broker is the controller for the cluster. the client library you are using. The time taken, in milliseconds, to send the response. The average execution time in ms for committing, across all running tasks of this thread. The average execution time in ms for punctuating, across all running tasks of this thread. Expand section "1. The individual record contained in a topic. kafka.network:type=RequestMetrics,name=ResponseSendTimeMs,request={Produce|FetchConsumer|FetchFollower}. The number of partitions that have not been fully replicated in the follower replicas. Enabling Client-to-server authentication using DIGEST-MD5, 4.7.2. consumers when they are connecting to the brokers. write). Approximately the same as the other brokers in the cluster. However, your code will likely undergo several iterations that Separate MBeans for all available request types are listed under the RequestBytes node. The total amount of buffer memory that is not being used (either unallocated or in the free list). are not complete, then any uncaught exception will end up in the finally statement Each tab is The average compression rate of record batches. The average number of network operations (reads or writes) on all connections per second. Approximately even when compared with the other brokers. kafka.server:type=ReplicaManager,name=UnderReplicatedPartitions. Keep your systems secure with Red Hat's specialized responses to security vulnerabilities. The number of replicas for which this broker is the leader. The total number of records produced/polled (before transformation) by this task belonging to the named source connector in this worker. The number of record processing failures in this task. The following tables present a selection of these broker-level MBeans organized into server, network, logging, and controller metrics. respective owners. Kafka Connect MBeans", Collapse section "7.8. Enabling SASL PLAIN authentication, 4.8.7. The average time in milliseconds spent by this worker to rebalance. Producer allows you to publish messages in near-real-time across worker nodes In Kafka, all messages can be keyed, allowing for messages to be distributed to The rate at which log data is written to disk, in milliseconds. rebalancing on the brokers, which will worsen general Kafka reliability. The total number of get calls for this store. Adding the Kafka Streams API as a dependency to your Maven project, 11. The average per-second number of record sends that resulted in errors for a topic. The epoch timestamp when this task last encountered an error. Running single node AMQ Streams cluster, 3.3. kafka.server:type=ReplicaManager,name=UnderMinIsrPartitionCount. One of 'source' or 'sink'. Management information for Zookeeper is not documented here. The total number of all operation calls for this store. The amount of temporary memory used for converting message formats and decompressing messages. Proceed to Step 6: Consuming Data (Java Kafka Client). These will have additional details about Kafka client Configuring connectors in Kafka Connect in standalone mode, 8.1.3. MBeans matching kafka.connect:type=connector-metrics,connector=*, 7.8.6. The average all operation rate for this store. MBeans matching kafka.consumer:type=consumer-fetch-manager-metrics,client-id=*, 7.7.5. These apply to an individual broker rather than the entire cluster. The number of records output from the transformations and written to Kafka for this task belonging to the named source connector in this worker, since the task was last restarted. The total number of records read from Kafka by this task belonging to the named sink connector in this worker, since the task was last restarted. The total number of connector startups that this worker has attempted. of the producer and consumer APIs to learn how you can develop better Kafka clients. The maximum execution time in ms for processing across all running tasks of this thread. The average process execution time in ns. The maximum put-all execution time in ns. The Kafka Producer step Configuring Zookeeper", Collapse section "3. The total number of delete calls for this store. The total number of punctuate operations called. You can view Zookeeper metrics in JConsole. The number of user threads blocked waiting for buffer memory to enqueue their records. Enabling TLS client authentication, 4.8.6. For kafka.server:type=BrokerTopicMetrics,name=BytesOutPerSec. The average percentage of this workers tasks starts that failed. Enabling Zookeeper ACLs in an existing Kafka cluster, 4.8.5. The maximum lag between the time that messages are received by the leader replica and by the follower replicas. The time, in milliseconds, that a request currently spends in the queue for the request type given in the request property. The average number of punctuate operations per second. Configuring Kafka brokers to use the new message format version, F. Kafka Connect configuration parameters, G. Kafka Streams configuration parameters. The average number of outgoing bytes sent per second for a node. MBeans matching kafka.streams:type=stream-record-cache-metrics,client-id=*,task-id=*,record-cache-id=*, 8.1.1. The total number of task starts that succeeded. Upgrading client applications to the new Kafka version, 11.7. The average number of process calls per second. Connections closed per second in the window. From the poll() Use this tab to configure the Kafka Producer broker sources. MBeans matching kafka.consumer:type=consumer-fetch-manager-metrics,client-id=*,topic=*,partition=*, 7.8.1. calling KafkaConsumer#close(). The current number of in-flight requests awaiting a response. When you have completed this step, you will have set up a producer application that is producing some randomly generated data in Avro format to the stream you have configured in step 2. To obtain management information, external tools can connect to the JVM that is running Zookeeper, the Kafka broker, and so on. The maximum destroy execution time in ns. You can connect to the JVM from a different machine by configuring the port that the JMX agent listens on. The status of the brokers connection to Zookeeper. Adding Kafka clients as a dependency to your Maven project, 10.1. If this is not done, Kafka will assign a Set up the Pentaho Server to connect to a Hadoop cluster. Request (Requests exempt from throttling). The total number of offset commit completions that were received too late and skipped/ignored. The maximum put-if-absent execution time in ns. The maximum time in ms a request was throttled by a broker. kafka.log:type=LogFlushStats,name=LogFlushRateAndTimeMs. The total number of create operations called. The average time taken for a fetch request. In these examples, the consumer constructor should be called once and the poll method While the following recommendations point out many caveats in using the kafka.server:type=ReplicaManager,name=IsrShrinksPerSec, The rate at which the number of ISRs in the broker decreases, kafka.server:type=ReplicaManager,name=IsrExpandsPerSec. kafka.network:type=SocketServer,name=NetworkProcessorAvgIdlePercent. The following table shows a selection of metrics that report information about requests. path to the server to make requests and to distinguish between different This topic presents recommendations in the form of code snippets that illustrate some of the In order to create a very basic producer application that use SASL, you need to create the configuration for the Kafka Producer. MBeans matching kafka.streams:type=stream-processor-node-metrics,client-id=*,task-id=*,processor-node-id=*, 7.9.4. The average number of outgoing bytes sent per second to all servers. kafka.network:type=RequestMetrics,name=TotalTimeMs,request={Produce|FetchConsumer|FetchFollower}. The rate at which the number of ISRs in the broker increases. Kafka provides many MBeans for monitoring the performance of the brokers in your Kafka cluster. All fields of this step support metadata injection. The current sequence number for offset commits. The age in seconds of the current producer metadata being used. The average length of time for I/O per select call in nanoseconds. If this object is not reused, then a new connection to the broker is These are metrics at the connect level about connection to each broker. The fraction of time this task has spent in the pause state. Total time, in milliseconds, spent processing requests. The default topic pattern is {tenant}-{instance}-{environment}-{streamName}, Check your care package for the truststore file, see also Step 3, Replace SASL_USERNAME and SASL_PASSWORD with credentials generated while configuring the application in Step 4. changes to your producer or consumer. Increase visibility into IT operations to detect and resolve technical issues before they impact your business. kafka.controller:type=KafkaController,name=ActiveControllerCount. The fraction of time this task has spent in the running state. These metrics are collected when the metrics.recording.level configuration parameter is info or debug. API documentation is known to be dense with information. Important Kafka broker metrics", Expand section "7.8. The number of connectors run in this worker. The total number of put calls for this store. The total number of put-all calls for this store. The number of fetch requests in the fetch purgatory. kafka.log:type=LogManager,name=OfflineLogDirectoryCount. kafka.server:type=BrokerTopicMetrics,name=ReplicationBytesInPerSec. These are metrics at the consumer level about the consumer's fetcher. One of 'unassigned', 'running', 'paused', 'failed', or 'destroyed'.

Leader election rate and time in milliseconds, kafka.controller:type=ControllerStats,name=LeaderElectionRateAndTimeMs.

The rate at which data sent from producers is consumed by the broker. The average number of records in each request for a topic. When using kafka client, you need to provide the fully resolved stream name to the configuration. This will not be the desired Enter the following information in the transformation step name field. A Kafka Enabling Zookeeper ACLs for a new Kafka cluster, 4.7.3. Zookeeper authentication", Expand section "4.7. MBeans matching kafka.connect:type=source-task-metrics,connector=*,task=*, 7.8.9. This is before transformations are applied. The maximum time in milliseconds taken by this task to poll for a batch of source records. The average percentage of this workers tasks starts that succeeded. opened with each new consumer object created. MBeans matching kafka.connect:type=connect-worker-rebalance-metrics, 7.8.5. The average size of the batches processed by the connector. When using JConsole to connect to a remote JVM, use the appropriate host name and JMX port. The current number of active connections. The average per-second number of retried record sends for a topic. and ports for HDFS, Job Tracker, security, and other big data cluster The average per-second number of records produced/polled (before transformation) by this task belonging to the named source connector in this worker. The number of records that have been produced by this task but not yet completely written to Kafka. Important Kafka broker metrics", Collapse section "7.5. The average time taken for a group rejoin. The maximum commit time in ns for this task. resource utilization (memory) on the broker side. kafka.network:type=RequestMetrics,name=RequestQueueTimeMs,request={Produce|FetchConsumer|FetchFollower}. The average rate of records being forwarded downstream, from source nodes only, per second. Encryption and authentication", Expand section "6.1. The total number of records sent for a topic. Kafka Streams MBeans", Collapse section "7.9. These are metrics at the partition level about the consumer's fetcher. The number of partitions under the minimum In-Sync Replica (ISR) count. The number of send requests in the producer purgatory. Overusing ephemeral ports The number of requests that are exempt from throttling. The maximum request latency in ms for a node. partitions based on their keys in a default routing scheme. The average destroy execution time in ns. The max number of bytes sent per partition per-request. This is after transformations are applied and excludes any records filtered out by the transformations. The time taken, in milliseconds, for the leader to process the request. Copyright 2022 Hitachi Vantara Lumada and Pentaho Documentation.

The average percentage of time that the network processors are idle. The class name of an MBean that uses Yammer metrics is prefixed with com.yammer.metrics. The maximum time in milliseconds taken by this task to commit offsets. The average per-second number of records output from the transformations and sent/put to this task belonging to the named sink connector in this worker. Upgrading an AMQ Streams cluster from 1.0.0 to 1.1.0, 11.3. The total number of task startups that this worker has attempted. The latency for ZooKeeper requests from the broker, in milliseconds. The number of topic partitions assigned to this task belonging to the named sink connector in this worker. If using JConsole to connect to a local JVM, the names of the JVM processes corresponding to the different components of AMQ Streams are as follows: org.apache.zookeeper.server.quorum.QuorumPeerMain, org.apache.kafka.connect.cli.ConnectStandalone, org.apache.kafka.connect.cli.ConnectDistributed, A Kafka producer, consumer, or Streams application. The average number of records that have been produced by this task but not yet completely written to Kafka. Ranger and Zookeeper, having a combination of frequent or prolonged DNS or network outages The epoch or generation number of this worker. Scaling Kafka clusters", Collapse section "6.1. kafka.network:type=RequestMetrics,name=MessageConversionsTimeMs,request={Produce|Fetch}. The maximum size of any request sent in the window. The number of brokers designated as controllers. The rate at which data is sent from the broker to other brokers. The status of the connector. Indicates the percentage of time that the request handler (IO) threads are not in use. The total number of flush calls for this store. You can use this step with ETL metadata injection to pass metadata to your transformation at runtime. The maximum execution time in ms for punctuating across all running tasks of this thread. The average put-all execution time in ns. Kafka Streams API overview", Expand section "11. shouldnt be too difficult.

Reassignment of partitions", Collapse section "6.2. The length of time, in milliseconds, that the request waits for the follower. The total number of record sends that resulted in errors. The maximum all operation execution time in ns. Any consumer connected to a partition will time out if no polling is done before the Reassignment of partitions", Expand section "7. The average number of records per request. This is after transformations are applied and excludes any records filtered out by the transformations. Upgrading an AMQ Streams cluster from 1.0.0 to 1.1.0", Red Hat JBoss Enterprise Application Platform, Red Hat Advanced Cluster Security for Kubernetes, Red Hat Advanced Cluster Management for Kubernetes, Using AMQ Streams on Red Hat Enterprise Linux (RHEL), 2.4.1.

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