我正在尝试使用 docker-compose 启动 kafka 服务。我使用卡夫来摆脱动物园管理员。我正在做的只是为了发展和未来的目的。 Kraft 应该能够在 docker 内部和外部访问。 KRaft 应该在我本地机器上的容器中运行，我只想从我的本地机器或 docker 镜像本身访问它。我在 KRaft 部分遵循了 enter link description here 这个例子。 我的 docker-compose.yml 是：

---
version: '2'
services:

  broker:
    image: confluentinc/cp-kafka:6.2.0
    hostname: broker
    container_name: broker
    ports:
      - "9092:9092"
      - "9101:9101"
    environment:
      KAFKA_BROKER_ID: 1
      KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: 'CONTROLLER:PLAINTEXT,PLAINTEXT:PLAINTEXT,PLAINTEXT_HOST:PLAINTEXT'
      KAFKA_ADVERTISED_LISTENERS: 'PLAINTEXT://broker:29092,PLAINTEXT_HOST://localhost:9092'
      KAFKA_OFFSETS_TOPIC_REPLICATION_FactOR: 1
      KAFKA_GROUP_INITIAL_REBAlance_DELAY_MS: 0
      KAFKA_TRANSactION_STATE_LOG_MIN_ISR: 1
      KAFKA_TRANSactION_STATE_LOG_REPLICATION_FactOR: 1
      KAFKA_JMX_PORT: 9101
      KAFKA_JMX_HOSTNAME: localhost
      KAFKA_PROCESS_ROLES: 'broker,controller'
      KAFKA_NODE_ID: 1
      KAFKA_CONTROLLER_QUORUM_VOTERS: '1@broker:29093'
      KAFKA_LISTENERS: 'PLAINTEXT://broker:29092,CONTROLLER://broker:29093,PLAINTEXT_HOST://localhost:9092'
      KAFKA_INTER_BROKER_LISTENER_NAME: 'PLAINTEXT'
      KAFKA_CONTROLLER_LISTENER_NAMES: 'CONTROLLER'
      KAFKA_LOG_DIRS: '/tmp/kraft-combined-logs'
    volumes:
      - ./update_run.sh:/tmp/update_run.sh
    command: "bash -c 'if [ ! -f /tmp/update_run.sh ]; then echo \"ERROR: Did you forget the update_run.sh file that came with this docker-compose.yml file?\" && exit 1 ; else /tmp/update_run.sh && /etc/confluent/docker/run ; fi'"

  schema-registry:
    image: confluentinc/cp-schema-registry:6.2.0
    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_REST_PORT: 8083
      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

  rest-proxy:
    image: confluentinc/cp-kafka-rest:6.2.0
    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'

然后，当我尝试在 docker 映像中启动 kafka-console-consumer 时，一切正常。但是，如果我使用以下命令在 Windows 计算机上启动 kafka-console-consumer，则会断开连接。

kafka-console-consumer 命令：

.\bin\windows\kafka-console-consumer.bat --bootstrap-server localhost:9092 --topic kraft-test

输出：

WARN [Consumer clientId=consumer-console-consumer-42932-1,groupId=console-consumer-42932] Bootstrap broker localhost:9092 (id: -1 rack: null) disconnected (org.apache.kafka.clients.NetworkClient)

我尝试在这两个网站的帮助下自己修复它，但没有任何效果。 enter link description here 和 enter link description here

对我来说一切看起来都不错，但也许我已经被这个问题困住了。