Kafka

Figure 1. Kafdrop Topic Viewer In the ever-expanding world of data streaming and event-driven architecture, Apache Kafka has emerged as a cornerstone for reliable and scalable data processing. However, managing and monitoring Kafka clusters can often present its own set of challenges. This is where Kafdrop, a web-based Kafka consumer group and topic viewer, comes to the rescue. With its intuitive interface and insightful visualizations, Kafdrop offers developers and operators an efficient way to gain valuable insights into Kafka clusters. ...

The AWS shapes are included in the PlantUML stdlib .. simply include them as shown here: example.puml @startuml !include <awslib/AWSCommon> !include <awslib/Analytics/ManagedStreamingforKafka> !include <awslib/Database/RDS> !include <awslib/General/Users> !include <awslib/General/InternetGateway> !include <kubernetes/k8s-sprites-labeled-25pct> skinparam linetype ortho title "AWS Context Diagram" package "EKS Kubernetes Cluster" as eks_cluster { component "<$pod>\napp1" as pod1 component "<$pod>\napp2" as pod2 } ManagedStreamingforKafka(kafka_pod, "Amazon MSK", "Apache Kafka") RDS(pg_rds, "PostgreSQL", "Sample Schema") Users(users, "AppUsers","editors, admins") InternetGateway(igw1, "Customer Gateway", "Customer access to internal services") users -> igw1 igw1 --> pod1 igw1 --> pod2 pod1 --> pg_rds pod1 --> kafka_pod pod2 --> pg_rds pod2 --> kafka_pod @enduml ...

Let’s say we would like to increase the limit t 10MB …​ Broker Configuration Apply the new limit either by modifying the server.properties like this…​ max.message.bytes=10485760 or apply it to a specific topic using kafka-configs.sh --bootstrap-server localhost:9092 \ --entity-type topics \ --entity-name thetopic \ --alter \ --add-config max.message.bytes=10485760 Producer Configuration for Spring Boot We simply need to add the following line to our application.properties: spring.kafka.producer.properties.max.request.size=spring.kafka.producer.properties.max.request.size The following proof-of-concept demonstrates that without the property, sending a large message fails, with the property it succeeds: ...

Sometimes it is nice to set up an embedded Kafka broker for testing without the need to have Docker installed (e.g. for using testcontainers-lib). The following snippet shows, how to set up an embedded Kafka instance for testing for a Spring Boot project. Setup Using Maven, this is our Spring Boot project with dependencies needed: pom.xml <?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> <modelVersion>4.0.0</modelVersion> <parent> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-parent</artifactId>(1) <version>2.6.4</version> <relativePath/> <!-- lookup parent from repository --> </parent> <groupId>com.hascode.tutorial</groupId> <artifactId>kafka-testing</artifactId> <version>1.0.0-SNAPSHOT</version> <properties> <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding> <project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding> <java.version>17</java.version> <maven.compiler.source>${java.version}</maven.compiler.source> <maven.compiler.target>${java.version}</maven.compiler.target> <kafka.version>3.1.0</kafka.version>(2) </properties> <dependencies> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter</artifactId> </dependency> <dependency> <groupId>org.springframework.kafka</groupId> <artifactId>spring-kafka</artifactId>(3) </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-test</artifactId> <scope>test</scope> </dependency> <dependency> <groupId>org.springframework.kafka</groupId> <artifactId>spring-kafka-test</artifactId>(4) <scope>test</scope> </dependency> <dependency>(5) <groupId>org.junit.jupiter</groupId> <artifactId>junit-jupiter-api</artifactId> <scope>test</scope> </dependency> <dependency> <groupId>org.junit.jupiter</groupId> <artifactId>junit-jupiter-engine</artifactId> <scope>test</scope> </dependency> <dependency> <groupId>org.junit.platform</groupId> <artifactId>junit-platform-launcher</artifactId> <scope>test</scope> </dependency> [..] </project> ...

Goals Setup Kafka and Zookeeper with Docker and docker-compose Create a message consumer and producer in Java Kafka Setup We’re using docker-compose to set up our message broker, zookeper and other stuff using confluent-platform. This is our docker-compose.yaml config file from Confluent’s following GitHub repository. docker-compose.yaml --- version: '2' services: zookeeper: image: confluentinc/cp-zookeeper:7.0.1 hostname: zookeeper container_name: zookeeper ports: - "2181:2181" environment: ZOOKEEPER_CLIENT_PORT: 2181 ZOOKEEPER_TICK_TIME: 2000 broker: image: confluentinc/cp-kafka:7.0.1 hostname: broker container_name: broker depends_on: - zookeeper ports: - "29092:29092" - "9092:9092" - "9101:9101" environment: KAFKA_BROKER_ID: 1 KAFKA_ZOOKEEPER_CONNECT: 'zookeeper:2181' KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: PLAINTEXT:PLAINTEXT,PLAINTEXT_HOST:PLAINTEXT KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://broker:29092,PLAINTEXT_HOST://localhost:9092 KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1 KAFKA_TRANSACTION_STATE_LOG_MIN_ISR: 1 KAFKA_TRANSACTION_STATE_LOG_REPLICATION_FACTOR: 1 KAFKA_GROUP_INITIAL_REBALANCE_DELAY_MS: 0 KAFKA_JMX_PORT: 9101 KAFKA_JMX_HOSTNAME: localhost schema-registry: image: confluentinc/cp-schema-registry:7.0.1 hostname: schema-registry container_name: schema-registry depends_on: - broker ports: - "8081:8081" environment: SCHEMA_REGISTRY_HOST_NAME: schema-registry SCHEMA_REGISTRY_KAFKASTORE_BOOTSTRAP_SERVERS: 'broker:29092' SCHEMA_REGISTRY_LISTENERS: http://0.0.0.0:8081 connect: image: cnfldemos/kafka-connect-datagen:0.5.0-6.2.0 hostname: connect container_name: connect depends_on: - broker - schema-registry ports: - "8083:8083" environment: CONNECT_BOOTSTRAP_SERVERS: 'broker:29092' CONNECT_REST_ADVERTISED_HOST_NAME: connect CONNECT_GROUP_ID: compose-connect-group CONNECT_CONFIG_STORAGE_TOPIC: docker-connect-configs CONNECT_CONFIG_STORAGE_REPLICATION_FACTOR: 1 CONNECT_OFFSET_FLUSH_INTERVAL_MS: 10000 CONNECT_OFFSET_STORAGE_TOPIC: docker-connect-offsets CONNECT_OFFSET_STORAGE_REPLICATION_FACTOR: 1 CONNECT_STATUS_STORAGE_TOPIC: docker-connect-status CONNECT_STATUS_STORAGE_REPLICATION_FACTOR: 1 CONNECT_KEY_CONVERTER: org.apache.kafka.connect.storage.StringConverter CONNECT_VALUE_CONVERTER: io.confluent.connect.avro.AvroConverter CONNECT_VALUE_CONVERTER_SCHEMA_REGISTRY_URL: http://schema-registry:8081 CONNECT_PLUGIN_PATH: "/usr/share/java,/usr/share/confluent-hub-components" CONNECT_LOG4J_LOGGERS: org.apache.zookeeper=ERROR,org.I0Itec.zkclient=ERROR,org.reflections=ERROR ksqldb-server: image: confluentinc/cp-ksqldb-server:7.0.1 hostname: ksqldb-server container_name: ksqldb-server depends_on: - broker - connect ports: - "8088:8088" environment: KSQL_CONFIG_DIR: "/etc/ksql" KSQL_BOOTSTRAP_SERVERS: "broker:29092" KSQL_HOST_NAME: ksqldb-server KSQL_LISTENERS: "http://0.0.0.0:8088" KSQL_CACHE_MAX_BYTES_BUFFERING: 0 KSQL_KSQL_SCHEMA_REGISTRY_URL: "http://schema-registry:8081" KSQL_PRODUCER_INTERCEPTOR_CLASSES: "io.confluent.monitoring.clients.interceptor.MonitoringProducerInterceptor" KSQL_CONSUMER_INTERCEPTOR_CLASSES: "io.confluent.monitoring.clients.interceptor.MonitoringConsumerInterceptor" KSQL_KSQL_CONNECT_URL: "http://connect:8083" KSQL_KSQL_LOGGING_PROCESSING_TOPIC_REPLICATION_FACTOR: 1 KSQL_KSQL_LOGGING_PROCESSING_TOPIC_AUTO_CREATE: 'true' KSQL_KSQL_LOGGING_PROCESSING_STREAM_AUTO_CREATE: 'true' ksqldb-cli: image: confluentinc/cp-ksqldb-cli:7.0.1 container_name: ksqldb-cli depends_on: - broker - connect - ksqldb-server entrypoint: /bin/sh tty: true ksql-datagen: image: confluentinc/ksqldb-examples:7.0.1 hostname: ksql-datagen container_name: ksql-datagen depends_on: - ksqldb-server - broker - schema-registry - connect command: "bash -c 'echo Waiting for Kafka to be ready... && \ cub kafka-ready -b broker:29092 1 40 && \ echo Waiting for Confluent Schema Registry to be ready... && \ cub sr-ready schema-registry 8081 40 && \ echo Waiting a few seconds for topic creation to finish... && \ sleep 11 && \ tail -f /dev/null'" environment: KSQL_CONFIG_DIR: "/etc/ksql" STREAMS_BOOTSTRAP_SERVERS: broker:29092 STREAMS_SCHEMA_REGISTRY_HOST: schema-registry STREAMS_SCHEMA_REGISTRY_PORT: 8081 rest-proxy: image: confluentinc/cp-kafka-rest:7.0.1 depends_on: - broker - schema-registry ports: - 8082:8082 hostname: rest-proxy container_name: rest-proxy environment: KAFKA_REST_HOST_NAME: rest-proxy KAFKA_REST_BOOTSTRAP_SERVERS: 'broker:29092' KAFKA_REST_LISTENERS: "http://0.0.0.0:8082" KAFKA_REST_SCHEMA_REGISTRY_URL: 'http://schema-registry:8081' ...

A lot of boilerplate code is written when developers need to test their applications with different connected systems like databases, stream platforms and other collaborators. Docker allows to handle those dependencies but there is still some glue code required to bind the container’s lifecycle and the configuration to the concrete integration test. Testcontainers is a testing library that offers lightweight throwaway instances of anything able to run in a Docker container, with bindings to configure the specific containers and also provides wrappers to manage our own custom containers. ...

When writing test for applications that interact with Kafka brokers we often need to setup a decent environment including an instance of Kafka and ZooKeeper. Though Kafka ships with some classes for testing, setting up a simple testing environment is quite easier with the kafka-unit library that offers JUnit test rule support or a fast programmatic setup within no time. In the following short example, I’d like to show how create a simple setup using Maven, Surefire and kafka-unit. [more-1484]# ...

Start an Image with kcat / kafka-cat for Debugging kubectl -n NAMESPACE run "$(whoami)-debug" -it --rm \ --image=confluentinc/cp-kafkacat:6.1.9 \ --restart=Never \ -- bash Dockerfile for Kafka Analysis Container with different Tools With jq, kafka console tools, schema registry tools and kafkacat installed …​. Dockerfile FROM confluentinc/cp-kafka:6.2.1 as cp-kafka FROM confluentinc/cp-schema-registry:6.2.1 as cp-schema-registry FROM debian:10-slim ARG DEBIAN_FRONTEND=noninteractive # Install necessary tools RUN apt-get update && apt-get install -y \ curl \ jq \ yq \ && rm -rf /var/lib/apt/lists/* # Install kafkacat binary RUN apt-get update && apt-get install -y kafkacat && rm -rf /var/lib/apt/lists/* # Copy Kafka binaries COPY --from=cp-kafka /usr/bin/kafka-* /usr/bin/ COPY --from=cp-schema-registry /usr/bin/schema-registry* /usr/bin/ # Copy entrypoint script COPY entrypoint.sh /usr/bin/entrypoint.sh RUN chmod +x /usr/bin/entrypoint.sh ENTRYPOINT ["/usr/bin/entrypoint.sh"] ...

Rerun existing completed Job Caution kubectl replace deletes the old job, if there is any error, your job definition is lost, don’t forget to save it first! Replace an existing Job with itself kubectl get job JOBNAME -o yaml | kubectl replace --force -f - Tip Sometimes there are errors importing the job template due to auto-generated labels or selectors .. a quick and dirty hack is to filter them out using jq ...