Messages are produced to Kafka using a Producer object. If you select a codec of plain, Logstash will encode your messages with not only the message but also with a timestamp and hostname. xml file to monitor all these components. Complete example. Take a look at the departmental KPI examples below to learn more about the one you should be. Kafka Connector metrics. Create an instance using the supplied producer factory and autoFlush setting. Azure Sample: Basic example of using Java to create a producer and consumer that work with Kafka on HDInsight. Producer Example for an SSL-Enabled Cluster. Along with that, we are going to learn about how to set up configurations and how to use group and offset concepts in Kafka. We are are using metricbeats with the kafka module turned on. In order to publish messages to an Apache Kafka topic, we use Kafka Producer. These factory methods are part of the Producer API Producer API. The tables below may help you to find the producer best suited for your use-case. Kafka is a 1991 French-American mystery thriller film directed by Steven Soderbergh. I can only reach around 1k/s after give 8 cores to Spark executors while other post said they car r. In this, we will learn the concept of how to Monitor Apache Kafka. Net Core Central. You will learn about the important Kafka metrics to be aware of in part 3 of this Monitoring Kafka series. transaction. Let’s take a look at a Kafka Nodejs example with Producers and Consumers. \w]+),topic=([-. Take a look at the departmental KPI examples below to learn more about the one you should be. This course will bring you through all those configurations and more, allowing you to discover brokers, consumers, producers, and topics. Thanks @ MatthiasJSax for managing this release. Take table backup - just in case. We sent records with the Kafka Producer using async and sync send methods. Prerequisites. producer are available only via the kafka_consumer and kafka_producer monitors of SignalFx Agent. You’ll be able to follow the example no matter what you use to run Kafka or Spark. # Properties for akka. We create a Message Producer which is able to send messages to a Kafka topic. Unit Testing Your Producer. Kafka Producers: Writing Messages to Kafka. If you choose a metric from the list, you will see something. uberAgent natively supports Kafka via the Confluent REST proxy. 0 Monitor types and attributes Kafka Producer Metrics (KFK_PRODUCER_METRICS) The Kafka Producer Metrics monitor type serves as a container for all the Kafka Producer Component Metrics instances. Kafka is run as a cluster on one, or across multiple servers, each of which is a broker. 9+), but is backwards-compatible with older versions (to 0. I’m building out a data pipeline that is using Kafka as its central integration point: shipping logs from hosts via Beats, and metrics via. For example, the production Kafka cluster at New Relic processes more than 15 million messages per second for an aggregate data rate approaching 1 Tbps. It's worth to note, that the Producer, the Kafka Connect framework and the Kafka Streams library exposes metrics via JMX as well. Kafka Tutorial. At a high level I think there are three ap. In this part we will going to see how to configure producers and consumers to use them. A Kafka client that publishes records to the Kafka cluster. In this post I am just doing the Consumer and using built in Producer. Kafka Streams is a Java library for building real-time, highly scalable, fault tolerant, distributed applications. The value_serializer attribute is just for the purpose of JSON serialization of JSON Values encountered. This link is the official tutorial but brand new users may find it hard to run it as the tutorial is not complete and the code has some bugs. You can use this pool setup to precisely control the number of Kafka producer instances that are being made available to your streaming application (if in doubt, use fewer). With that in mind, here is our very own checklist of best practices, including key Kafka metrics and alerts we monitor with Server Density. 10 and your version of Spark:. A record is a key-value pair. Since being created and open sourced by LinkedIn in 2011, Kafka has quickly evolved from messaging queue to a full-fledged streaming platform. The reason it appears as "unknown" is tied to the way we build it (outside of a repository). The field being unknown does not affect the Kafka. Applications that aggregate metrics and counters, for example, are good examples of how VoltDB makes data more meaningful and actionable. Below class determines the partitioning in the topic where the message needs to be sent. Send simple string messages to a topic: kafka-console-producer --broker-list localhost:9092 --topic test here is a message here is another message ^D (each new line is a new message, type ctrl+D or ctrl+C to stop) Send messages with keys:. The consumers export all metrics starting from Kafka version 0. Also a demonstration of the streaming api. Successes to true. 10:9092]buffer. This topic describes how to create a Hadoop cluster and Kafka cluster by using E-MapReduce (EMR) and run a Spark Streaming job to consume Kafka data. Note that in order for the Successes channel to be populated, you have to set config. While doing so, I want to capture the producer metrics in the below way: I am aware about JMX port for kafka & I did try setting the Kafka JMX port to 9999. Consumers can subscribe to topics and receive messages. Flink's Kafka connectors provide some metrics through Flink's metrics system to analyze the behavior of the connector. Kafka provides metrics via logs. One of the first ones was logging and metrics aggregation. Zabbix history table gets really big, and if you are in a situation where you want to clean it up. Covers Kafka Architecture with some small examples from the command line. Confluent provides a nice (and mostly correct) overview of the available metrics in the more recent Kafka versions. Start the producer with the JMX parameters enabled: JMX_PORT=10102 bin/kafka-console-producer. We will also take a look into. Use the Kafka broker tab to keep an eye out for such problems. This check fetches the highwater offsets from the Kafka brokers, consumer offsets that are stored in kafka or zookeeper (for old-style consumers), and the calculated consumer lag (which is the difference between the broker offset. When configuring Metrics Reporter on a secure Kafka broker, the embedded producer (that sends metrics data to _confluent-metrics topic) in Metrics Reporter needs to have the correct client security configurations prefixed with confluent. And how to move all of this data becomes nearly as important - Selection from Kafka: The Definitive Guide [Book]. commits, no. In this tutorial, we will be developing a sample apache kafka java application using maven. protoc -o metrics. While doing so, I want to capture the producer metrics in the below way: I am aware about JMX port for kafka & I did try setting the Kafka JMX port to 9999. 10 with Spark 2. Kafka Tutorial. export KAFKA_PRDCR_HOST=127. This section describes how to use E-MapReduce to collect metrics from a Kafka client to conduct effective performance monitoring. As and when I'm ready to deploy the code to a 'real' execution environment (for example EMR), then I can start to worry about that. hortonworks. If you choose a metric from the list, you will see something. This Confluence has been LDAP enabled, if you are an ASF Committer, please use your LDAP Credentials to login. Welcome, Habr! At one time, we were the first to introduce the topic of Kafka to the Russian market and continue to follow its development. Partitioning an Apache Kafka application. This script requires protobuf and kafka-python modules. Logging and metrics aggregation. Kafka topics are divided into a number of partitions. Kafka’s producer explained. It helped me to configure producer and consumer by using xml configuration files. Send simple string messages to a topic: kafka-console-producer --broker-list localhost:9092 --topic test here is a message here is another message ^D (each new line is a new message, type ctrl+D or ctrl+C to stop) Send messages with keys:. Kafak Sample producer that sends Json messages. Both consumers and producers can be written in any language that has a Kafka client written for it. This includes metrics, logs, custom events, and so on. Should producers fail, consumers will be left without new messages. Micronaut applications built with Kafka can be deployed with or without the presence of an HTTP server. Kafka Console Producer and Consumer Example – In this Kafka Tutorial, we shall learn to create a Kafka Producer and Kafka Consumer using console interface of Kafka. topics: null. Below are some of the most useful producer metrics to monitor to ensure a steady stream of incoming data. To take advantage of this, the client will keep a buffer of messages in the background and batch them. MQTT is the protocol optimized for sensor networks and M2M. A producer is an application that generates data but only to provide it to some other application. For example, if we assign the replication factor = 2 for one topic, so Kafka will create two identical replicas for each partition and locate it in the cluster. This post gives an overview of Apache Kafka and using an example use-case, shows how to get up and running with it quickly and easily. This is different from other metrics like yammer, where each metric has its own MBean with multiple attributes. Both consumers and producers can be written in any language that has a Kafka client written for it. 0 just got released , so it is a good time to review the basics of using Kafka. desc metrics. In this tutorial, we shall learn Kafka Producer with the help of Example Kafka Producer in Java. NET producer and consumer, I have set up a test Kafka environment on a Wwindows machine. Kafka and IBM QRadar Integration queries ?? Hi Experts - I have a scenario wherein I have to forward and filter network and OS syslogs/security events/performance metrics from Cloudera Data Lake to IBM QRadar for further visualizations in QRadar. Kafka’s producer explained. A consumer pulls messages off of a Kafka topic while producers push messages into a Kafka topic. The following example assumes that you are using the local Kafka configuration described in Running Kafka in Development >. The Producer class in Listing 2 (below) is very similar to our simple producer from Kafka Producer And Consumer Example, with two changes: We set a config property with a key equal to the value of ProducerConfig. Also, when native encoding and decoding is used, the headerMode=embeddedHeaders property is ignored and headers are not embedded in the message. It's worth to note, that the Producer, the Kafka Connect framework and the Kafka Streams library exposes metrics via JMX as well. My objective here is to show how Spring Kafka provides an abstraction to raw Kafka Producer and Consumer API's that is easy to use and is familiar to someone with a Spring background. Short title. MockProducer producer; @Before public void setUp() { producer = new MockProducer( true, new StringSerializer(), new StringSerializer()); }. Here’s the example dashboard for the system and Kafka monitoring:. Default null (no transactions) spring. It is horizontally scalable. This is a use case in which the ability to have multiple applications producing the same type of message shines. This client class contains logic to read user input from the console and send that input as a message to the Kafka server. Kafka Component. Net Core Central. Enable remote connections Allow remote JMX connections to monitor DataStax Apache Kafka Connector activity. 2018-08-01. As a result, we'll see the system, Kafka Broker, Kafka Consumer, and Kafka Producer metrics on our dashboard on Grafana side. Questions: I have Kafka running in a remote server and I am using spring framework (java) to produce and consume messages. When transactions are enabled, individual producer properties are ignored and all producers use the spring. Moreover, we will cover all possible/reasonable Kafka metrics that can help at the time of troubleshooting or Kafka Monitor. Similarly, producers and consumers can also expose metrics via JMX that can be visualized by repeating the exact same process show above. producer:type=producer-topic-metrics,client-id=([-. If you haven’t already, check out my previous tutorial on how to setup Kafka in docker. Creating a Simple Kafka Producer in Java Apache Kafka is a fault tolerant publish-subscribe streaming platform that lets you process streams of records as they occur. For more information, see High availability with Apache Kafka on HDInsight. Creating a producer with security Given below isa asample configuration that creates a producer with security:. The Consumer API allows an application to subscribe to one or more topics and process the stream of records produced to them. This example shows how to use the producer with separate goroutines reading from the Successes and Errors channels. Since Mirror Maker has one or more consumers and a single producer, most consumer or metrics should be usable with this query. Kafka is starting to get more producer implementations but, again, there were no existing implementations that could stream the audio data of interest. Intro to Apache Kafka - [Instructor] Okay finally another big use case for Kafka. Moreover, we will cover all possible/reasonable Kafka metrics that can help at the time of troubleshooting or Kafka Monitor. Hi, I use such metrics as: - the position in google search - the number of releases, the current release number, no. Unknown Kafka producer or consumer properties provided through this configuration are filtered out and not allowed to propagate. Kafka Tutorial. This means I don’t have to manage infrastructure, Azure does it for me. I’m running my Kafka and Spark on Azure using services like Azure Databricks and HDInsight. For every event in the Kafka, a function is triggered - which is a Consumer function. Questions: I have Kafka running in a remote server and I am using spring framework (java) to produce and consume messages. To integrate with other applications, systems, we need to write producers to feed data into Kafka and write the consumer to consume the data. Kafka Use Cases. Using these tools, operations is able manage partitions and topics, check consumer offset position, and use the HA and FT capabilities that Apache Zookeeper provides for Kafka. The bootstrap_servers attribute informs about the host & port for the Kafka server. Use cases for Apache Kafka. consumer:type=consumer-fetch-manager-metrics,client-id=id' attribute='records-lag-max' where the id is typically a number assigned to the worker by the Kafka Connect. Over time we came to realize many of the limitations of these APIs. In this blog, we will show how Structured Streaming can be leveraged to consume and transform complex data streams from Apache Kafka. 10 and as the adoption of Kafka booms, so does Kafka Streams. Moreover, we will cover all possible/reasonable Kafka metrics that can help at the time of troubleshooting or Kafka Monitor. transaction. The following example assumes that you are using the local Kafka configuration described in Running Kafka in Development >. If you haven't installed Kafka yet, see our Kafka Quickstart Tutorial to get up and running quickly. 1 Basic Kafka Operations This section will review the most common operations you will perform on your Kafka cluster. Apache Kafka - Example of Producer/Consumer in Java If you are searching for how you can write simple Kafka producer and consumer in Java, I think you reached to the right blog. Note that the metrics prefixed by kafka. This means I don’t have to manage infrastructure, Azure does it for me. Pulsar provides an easy option for applications that are currently written using the Apache Kafka Java client API. Here is a simple example of using the producer to send records with strings containing sequential numbers as the key/value pairs. Successes to true. The Kafka producer collects messages into a batch, compresses the batch, then sends it to a broker. Micronaut features dedicated support for defining both Kafka Producer and Consumer instances. Sample Code. If the key is null, Kafka uses random partitioning for message assignment. Moreover, we will see KafkaProducer API and Producer API. 1 Basic Kafka Operations This section will review the most common operations you will perform on your Kafka cluster. Kafka Home metrics descriptions; Row Metrics Description; BYTES IN & OUT / MESSAGES IN: Bytes In & Bytes Out /sec: Rate at which bytes are produced into the Kafka cluster and the rate at which bytes are being consumed from the Kafka cluster. bin/kafka-console-producer. We have also expanded on the Kafka design section and added references. SASL is used to provide authentication and SSL for encryption. Title XVIII—Government purchase and travel cards Sec. In an existing application, change the regular Kafka client dependency and replace it with the Pulsar Kafka wrapper. Welcome, Habr! At one time, we were the first to introduce the topic of Kafka to the Russian market and continue to follow its development. This post is about combining Dropwizard metrics with Kafka to create self instrumenting applications producing durable streams of application metrics, which can be processed (and re-processed) in many ways. SELECT kafka_partitions, kafka_under_replicated_partitions WHERE hostname=host1. We recommend to use DirectMQ instead of Kafka as message queue,because it is simpler to use and tailored to the needs of ArangoDB devel 3. BMC PATROL for Apache Kafka 1. I am using apache camel kafka as client for producing message, what I observed is kafka producer taking 1 ms to push a message, if I merge message into batch by using camel aggregation then it is taking 100ms to push a single message. Business examples of topics might be account, customer, product, order, sale, etc. Consumer Lag & 100+ Metrics. MockProducer producer; @Before public void setUp() { producer = new MockProducer( true, new StringSerializer(), new StringSerializer()); }. We will have a separate consumer and producer defined in java that will produce message to the topic and also consume message from it. kafka-metrics-producer-topkrabbensteam Kafka-metrics-producer-topkrabbensteam. After a year of running a commercial service, SignalFx has grown its own internal Kafka cluster to 27 brokers, 1000 active partitions, and 20 active topics serving more than 70 billion messages per day (and growing). Using these tools, operations is able manage partitions and topics, check consumer offset position, and use the HA and FT capabilities that Apache Zookeeper provides for Kafka. Monitoring end-to-end performance requires tracking metrics from brokers, consumer, and producers, in addition to monitoring ZooKeeper, which Kafka uses for coordination among consumers. Use the Kafka broker tab to keep an eye out for such problems. This significantly increased the throughput of the publisher. In this, we will learn the concept of how to Monitor Apache Kafka. Use cases for Apache Kafka. Sample scenario The sample scenario is a simple one, I have a system which produces a message and another which processes it. ConsoleProducer) will use the new producer instead of the old producer be default, and users have to specify 'old-producer' to use the old producer. 10 and your version of Spark:. For example, we had a "high-level" consumer API which supported consumer groups and handled failover, but didn't support many of the more. You create a new replicated Kafka topic called my. For example, the following metric names may be valid for Kafka Broker: alerts_rate_across_clusters; total_alerts_rate_across_clusters; Some metrics, such as alerts_rate, apply to nearly every metric context. That message is queued. It will automatically gather all metrics for the Kafka Broker, Kafka Consumer (Java only) and Kafka Producers (Java only) across your environment with a single plugin. Logging and metrics aggregation. Code for reference : k8s-hpa-custom-autoscaling-kafka-metrics/go-kafka. \bin\windows\kafka-console-producer. kafka-python is best used with newer brokers (0. Apache Kafka – Java Producer Example with Multibroker & Partition In this post I will be demonstrating about how you can implement Java producer which can connect to multiple brokers and how you can produce messages to different partitions in a topic. Additionally, Kafka connects to external systems (for data import/export) via Kafka Connect and provides Kafka Streams, a Java stream processing library. Spark Streaming + Kafka Integration Guide. Let's start by creating a Producer. Background. Messages can be sent in various formats such as tuple, string, blob, or a custom format provided by the end user. In this module, you will learn about large scale data storage technologies and frameworks. Sample scenario The sample scenario is a simple one, I have a system which produces a message and another which processes it. Take informed troubleshooting decisions by keeping track of critical metrics like connection count, incoming and outgoing bytes rate and lot more. Kafka Connect standardises integration of other data systems with Apache Kafka, simplifying connector development, deployment, and management. 0 Monitor types and attributes Kafka Producer Metrics (KFK_PRODUCER_METRICS) The Kafka Producer Metrics monitor type serves as a container for all the Kafka Producer Component Metrics instances. An example of a producer application could be a web server that produces “page hits” that tell when a web page was accessed, from which IP address, what the page was and how long it took. Apache Kafka is a distributed streaming platform designed for high volume publish-subscribe messages and streams. System metrics from hosts in the cluster are written as [heroku-kafka. Instructor Stephane Maarek includes practical use cases and examples, such as consuming data from sources like Twitter and ElasticSearch, that feature real-world architecture and production deployments. Since Kafka has multiple components (Kafka broker, producer, consumer) which expose the JMX metrics. The examples shown here can be run against a live Kafka cluster. Apache Kafka - Example of Producer/Consumer in Java If you are searching for how you can write simple Kafka producer and consumer in Java, I think you reached to the right blog. codec: none: This parameter allows you to specify the compression codec for all data generated by this producer. This tool lets you produce messages from the command-line. 9, simplifies the integration between Apache Kafka and other systems. Apache Kafka 1. To view these metrics, create a custom dashboard: Go to the New Relic metric explorer. Last released: Oct 23, 2018. We'll call processes that publish messages to a Kafka topic producers. Then we can do so, using the below steps. TestEndToEndLatency can't find the class. I am new to kafka. To take advantage of this, the client will keep a buffer of messages in the background and batch them. xml : < dependency > < groupId > org. We sent records with the Kafka Producer using async and sync send methods. Hey guys, I wanted to kick off a quick discussion of metrics with respect to the new producer and consumer (and potentially the server). Kafka Producer. Apache Kafka Performance with Dell EMC Isilon F800 All-Flash NAS Kafka Introduction A Kafka cluster consists of Producers that send records to the cluster, the cluster stores these records and makes them available to Consumers. For testing on my local machine, I am just producing 1 event. Clusters and Brokers Kafka cluster includes brokers — servers or nodes and each broker can be located in a different machine and allows subscribers to pick messages. Following is the C# producer code. This uses the Kafka Producer API to write messages to a topic on the broker. We will have a separate consumer and producer defined in java that will produce message to the topic and also consume message from it. We will also take a look into. Together, you can use Apache Spark and Kafka to transform and augment real-time data read from Apache Kafka and integrate data read from Kafka with information stored in other systems. Zabbix history table gets really big, and if you are in a situation where you want to clean it up. In this tutorial, we are going to create a simple Java example that creates a Kafka producer. produce you are performing no external I/O. We will be creating a kafka producer and consumer in Nodejs. For us Under Replicated Partitions and. On this section, we will learn the internals that compose a Kafka producer, responsible for sending messages to Kafka topics. Download and install Apache Kafka. Response rate: the rate at which the producer receives responses from brokers. So, when you call producer. Clusters and Brokers Kafka cluster includes brokers — servers or nodes and each broker can be located in a different machine and allows subscribers to pick messages. Select Kafka process and click on the Connect button and then select the MBeans tab. Initially conceived as a messaging queue, Kafka is based on an abstraction of a distributed commit log. Each Kafka server instance is called a broker. The Kafka distribution provides a producer performance tool that can be invoked with the script bin/kafka-producer-perf-test. For more information, see High availability with Apache Kafka on HDInsight. Partitioning an Apache Kafka application. For example: michael,1 andrew,2 ralph,3 sandhya,4. Conclusion Kafka Producer example. But Kafka can get complex at scale. This post gives an overview of Apache Kafka and using an example use-case, shows how to get up and running with it quickly and easily. Lastly, we added some simple Java client examples for a Kafka Producer and a Kafka Consumer. Hello everyone, welcome back to. An example of a producer application could be a web server that produces “page hits” that tell when a web page was accessed, from which IP address, what the page was and how long it took. The following are code examples for showing how to use kafka. Also, when native encoding and decoding is used, the headerMode=embeddedHeaders property is ignored and headers are not embedded in the message. These factory methods are part of the Producer API Producer API. Apache Kafka Simple Producer Example in Apache Kafka - Apache Kafka Simple Producer Example in Apache Kafka courses with reference manuals and examples pdf. consumer and kafka. Together, you can use Apache Spark and Kafka to transform and augment real-time data read from Apache Kafka and integrate data read from Kafka with information stored in other systems. Monitoring end-to-end performance requires tracking metrics from brokers, consumer, and producers, in addition to monitoring ZooKeeper, which Kafka uses for coordination among consumers. sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic matstream Create a file named myfile that consists of comma-separated data. Example of a Kafka Producer that is using Snappy Compression. This link is the official tutorial but brand new users may find it hard to run it as the tutorial is not complete and the code has some bugs. In particular, we found the topic of interaction between Kafka and Kubernetes interesting. sh and kafka-console-consumer. The examples shown here can be run against a live Kafka cluster. Business examples of topics might be account, customer, product, order, sale, etc. Setting Env Vars. KPI Examples. Agenda The goal of producer performance tuning Understand the Kafka Producer Producer performance tuning ProducerPerformance tool Quantitative analysis using producer metrics Play with a toy example Some real world examples Latency when acks=-1 Produce when RTT is long Q & A 6. Below are some of the most useful producer metrics to monitor to ensure a steady stream of incoming data. I have downloaded kafka 2. Example: processing streams of events from multiple sources with Apache Kafka and Spark. It visualizes key metrics like under-replicated and offline partitions in a very intuitive way. This Confluence has been LDAP enabled, if you are an ASF Committer, please use your LDAP Credentials to login. Ostensibly a biopic , based on the life of Franz Kafka , the film blurs the lines between fact and Kafka's fiction (most notably The Castle and The Trial ), creating a Kafkaesque atmosphere. KafkaProducer¶ class kafka. I assume that you have Python 3 installed on your system and virtualenv installed as well. In this example we provide only the required properties for the producer. When working with the producer, we create ProducerRecords, that we send to Kafka by using the producer. Performance Test Tool for Apache Kafka. Kafka makes it possible to distribute uberAgent’s metrics in a highly scalable manner, supporting hundreds of thousands of endpoints (data producers) and thousands of consumers. That message is queued. In this tutorial, you learn how to. This example also assumes that the offsets are stored in Kafka. Create a temporary table. Code for reference : k8s-hpa-custom-autoscaling-kafka-metrics/go-kafka. Producer Metrics 236 Consumer Metrics 239 Kafka Streams by Example 264 Word Count 265. The thread is started right when KafkaProducer is created. I successfully created a topic and sent a message. We will implement a simple example to send a message to Apache Kafka using Spring Boot Spring Boot + Apache Kafka Hello World Example In this post we will integrate Spring Boot and Apache Kafka instance. Today, we will see Kafka Monitoring. Below is a simple example that creates a Kafka consumer that joins consumer group mygroup and reads messages from its assigned partitions until Ctrl-C is pressed: A number of configuration parameters are worth noting: bootstrap. Apache Kafka 77 usages. See the integration documentation for more information. Brief description of installation 3 kafka clusther 16Core 32GB RAM. In this article, we'll cover Spring support for Kafka and the level of abstractions it provides over native Kafka Java client APIs. Net Core Streaming Application Using Kafka – Part 1. Would it be possible for somebody in the know to mark the metrics Grokbase › Groups › Kafka › users › July 2013. The consumers export all metrics starting from Kafka version 0. Library that can be used to produce metrics to Kafka using Apache Avro schemas Installation: pip install kafka-metrics-producer-topkrabbensteam Usage:. This check fetches the highwater offsets from the Kafka brokers, consumer offsets that are stored in kafka or zookeeper (for old-style consumers), and the calculated consumer lag (which is the difference between the broker offset. The following are code examples for showing how to use kafka. # Properties for akka. Note that in order for the Successes channel to be populated, you have to set config. In this scenario, the light sensor needs to talk to the LED, which is an example of M2M communication. Below are some of the most useful producer metrics to monitor to ensure a steady stream of incoming data. Kafka's speed comes from the ability to batch many message together. commits, no. Well, it could be a messaging system, it could be used for activity tracking or to gather metrics from many different locations, (mumbles) your examples or your IoT devices. Sample scenario The sample scenario is a simple one, I have a system which produces a message and another which processes it. Apache Kafka 77 usages. BasicProducerExample.