Kafka加密采集监控解决方案

Kafka加密采集监控解决方案,第1张

Kafka加密采集监控解决方案 环境准备

配置SASL/PLAINTEXT MECHANISM为SCRAM-SHA512

Kafka加密 配置SASL+ACL 一、 SASL配置 1. 修改zoo.cfg配置文件,开启zk的SASL认证

requireClientAuthScheme=sasl

2. 创建kafka-broker-jaas.conf文件,为kafka添加认证信息

kafksServer 中的username和password是broker之间通信

Client 是客户端的username和password,除了配置文件方式,也可以通过命令创建(后面会讲)

KafkaServer {
org.apache.kafka.common.security.scram.ScramLoginModule required
username="admin"
password="admin1234";
};
Client {
org.apache.zookeeper.server.auth.DigestLoginModule required
username="kafka"
password="kafka1234";
};
3. 在kafka的sasl_server.properties配置文件中开启SASL认证
 #设置本例中admin为超级用户
super.users=User:admin;User:kafka
 #启用SCRAM机制,采用SCRAM-SHA-512算法
sasl.enabled.mechanisms=SCRAM-SHA-512
#为broker间通讯开启SCRAM机制,采用SCRAM-SHA-512算法
sasl.mechanism.inter.broker.protocol=SCRAM-SHA-512
 #broker间通讯使用PLAINTEXT,本例中不演示SSL配置
security.inter.broker.protocol=SASL_PLAINTEXT
 #配置listeners使用SASL_PLAINTEXT
listeners=SASL_PLAINTEXT://192.168.1.88:9092
 #配置advertised.listeners
advertised.listeners=SASL_PLAINTEXT://192.168.1.88:9092
 security.protocol=SASL_SSL 
4. 修改kafka启动脚本,加载指定的properties文件 及 读取认证配置文件,这一行代码 放在zkEnv.sh脚本的最前面

export KAFKA_OPTS="-Djava.security.auth.login.config=/home/impdatahd/kafka_2.12-2.4.0/config/kafka-broker-jaas.conf"

5.sh kafka-start.sh 启动kafka server,并验证启动成功 二、 ACL配置 1. 修改zoo.cfg配置文件,开启zk的ACL认证

authProvider.1=org.apache.zookeeper.server.auth.SASLAuthenticationProvider

2. 在kafka的sasl_server.properties配置文件中开启ACL认证
# 启用ACL
authorizer.class.name=kafka.security.authorizer.AclAuthorizer
3. ACL动态创建用户、分配用户组 及 topic读、写赋权命令

创建账号:

sh kafka-configs.sh --zookeeper localhost:2181/kafka240 --alter --add-config 'SCRAM-SHA-512=[password=sasl_user_1_pwd]' 	--entity-type users --entity-name sasl_user_1

添加账号写权限:

sh kafka-acls.sh --authorizer kafka.security.auth.SimpleAclAuthorizer --authorizer-properties 	zookeeper.connect=localhost:2181/kafka240 --add --allow-principal User:sasl_user_1 --operation Write --topic kafka_sasl_2

添加账号读权限:

sh kafka-acls.sh --authorizer kafka.security.auth.SimpleAclAuthorizer --authorizer-properties 	zookeeper.connect=localhost:2181/kafka240 --add --allow-principal User:test3read --operation Read --topic kafka_sasl_6

创建Group:

sh kafka-acls.sh --authorizer kafka.security.auth.SimpleAclAuthorizer --authorizer-properties 	zookeeper.connect=localhost:2181/kafka240 --add --allow-principal User:sasl_user_1  --group kafka-acls-group
4. 验证步骤3是否正确,通过kafka自带的producer、consumer命令测试

4.1 创建生产者配置文件 producer.properties

security.protocol=SASL_PLAINTEXT
sasl.mechanism=SCRAM-SHA-512
sasl.jaas.config=org.apache.kafka.common.security.scram.ScramLoginModule required username="kafka" password="kafka1234";

4.2 创建消费者配置文件 consumer.properties

bootstrap.servers=localhost:9092
group.id=kafka-acls-group
security.protocol=SASL_PLAINTEXT
sasl.mechanism=SCRAM-SHA-512
sasl.jaas.config=org.apache.kafka.common.security.scram.ScramLoginModule required username="test3read" password="test3read1234";

4.3 生产 和 消费命令
生产:kafka-console-producer.sh --broker-list loyx01:9092 --topic sasl_test_one --producer.config /home/impdatahd/kafka_2.12-2.4.0/config/p_sasl.properties
消费:kafka-console-consumer.sh --bootstrap-server loyx01:9092 --topic behavior_log_andr_test --consumer.config /home/impdatahd/kafka_2.12-2.4.0/config/c_sasl.properties
三、 常见问题

    kafka启动时报错: ERROR SASL authentication failed using login context ‘Client’ with exception: {}
    解决:
    使用windows拖拽的方式会导致有无法看见的结束符,不识别conf文件而造成失败。启动时没有加载zookeeper_sasl.conf文件报错
采集

利用flume进行采集需要做以下修改。
1)创建jaas文件
需要和kafka配置保持一致!

KafkaServer {
    org.apache.kafka.common.security.scram.ScramLoginModule required
    username="youradminusername"
    password="youradminpwd";
};
Client {
    org.apache.zookeeper.server.auth.DigestLoginModule required
    username="yourusername"
    password="yourpwd";
};

2)修改flume-env.sh
JAVA_OPTS="$JAVA_OPTS -Djava.security.auth.login.config=/home/impdatahd/flume-1.9.0/conf/kafka-broker-jaas.conf"
3)编写flume脚本

# 命名每个组件 a1代表agent的名称
#a1.sources代表a1中配置的source,多个使用空格间隔
#a1.sinks代表a1中配置的sink,多个使用空格间隔
#a1.channels代表a1中配置的channel,多个使用空格间隔
a1.sources = r1
a1.sinks = k1
a1.channels = c1
#source
a1.sources.r1.type = org.apache.flume.source.kafka.KafkaSource
a1.sources.r1.batchSize = 1000
a1.sources.r1.batchDurationMillis = 1000
a1.sources.r1.kafka.bootstrap.servers = 192.168.1.88:9092,192.168.1.89:9092,192.168.1.90:9092
a1.sources.r1.kafka.topics = kafka_sasl_1
a1.sources.r1.kafka.consumer.group.id = kafka-acls-group
a1.sources.r1.kafka.consumer.security.protocol = SASL_PLAINTEXT
a1.sources.r1.kafka.consumer.sasl.mechanism = SCRAM-SHA-512
a1.sources.r1.kafka.consumer.sasl.jaas.config =org.apache.kafka.common.security.scram.ScramLoginModule required username="yourusername" password="yourpwd";
a1.sources.r1.kafka.consumer.auto.offset.reset = earliest
#channel
a1.channels.c1.type = memory
a1.channels.c1.capacity = 100000
a1.channels.c1.transactionCapacity = 10000
a1.channels.c1.byteCapacityBufferPercentage = 20
a1.channels.c1.byteCapacity = 6912212
# 配置sink
a1.sinks.k1.type = hdfs
a1.sinks.k1.hdfs.path=/origin_data/test/sasl_test/%Y-%m-%d
#上传文件的前缀
a1.sinks.k1.hdfs.filePrefix = sasl-
a1.sinks.k1.hdfs.batchSize= 7500
a1.sinks.k1.hdfs.minBlockReplicas=1
#配置文件滚动
# 30MIN
a1.sinks.k1.hdfs.rollInterval = 1800
#128M after codec
a1.sinks.k1.hdfs.rollSize = 1580484745
a1.sinks.k1.hdfs.rollCount = 0
a1.sinks.k1.hdfs.fileType=DataStream
# 绑定和连接组件
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

启动flume即可!
采集后如图所示

监控

1)exporter
利用github开源项目做数据收集,分布式部署到kafka所在节点。
exporter开源项目 采用版本v.1.13.1
将源文件编译后得到其脚本文件,给予可执行权限后运行以下语句开启监控。

grafana面板地址
ID:10736
下面是启停命令。

# --kafka.server=kafka_broker_address
# --kafka.version=kafka_version
# --log.leve=日志等级
nohup ./kafka_exporter 
	--kafka.server=192.168.1.88:9092 
	--kafka.server=192.168.1.89:9092 
	--kafka.server=192.168.1.90:9092 
	--kafka.version=2.4.0 
	--sasl.enabled 
	--sasl.mechanism=scram-sha512 
	--sasl.username=admin 
	--sasl.password=admin1234 
	--tls.insecure-skip-tls-verify 
	--log.level=info > kafka_exporter.log  
	--web.listen-address=:29092 &
	
ps -ef | grep kafka_exporter| grep -v grep |  awk '{print $2}'| xargs kill

2)promethus
需要对promethus做相关配置。

global:
  scrape_interval: 60s
  evaluation_interval: 60s
scrape_configs:
   - job_name: 'prometheus'
     static_configs:
       - targets: ['localhost:9090']
         labels:
           instance: prometheus
   - job_name: 'linux'
     metrics_path: "/metrics"
     static_configs:
       - targets: ['192.168.1.88:9100','192.168.1.89:9100','192.168.1.90:9100','192.168.1.91:9100']
   - job_name: 'kafka_exporter'
     metrics_path: "/metrics"
     scrape_interval: 5s
     static_configs:
       - targets: ['192.168.1.88:29092','192.168.1.89:29092','192.168.1.90:29092']
   - job_name: 'flume_exporter'
     metrics_path: "/metrics"
     scrape_interval: 5s
     static_configs:
       - targets: ['192.168.1.89:9360','192.168.1.90:9360
测试 javademo关键代码 application.yml
server:
  port: 9000
spring:
  kafka:
    consumer:    
      bootstrap-servers: 192.168.1.88:9092
      group-id: kafka_test
      auto-offset-reset: earliest
      key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
      value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
    producer:    
      bootstrap-servers: 192.168.1.88:9092      
      key-serializer: org.apache.kafka.common.serialization.StringSerializer
      value-serializer: org.apache.kafka.common.serialization.StringSerializer
      acks: 1
      retries: 3
      buffer-memory: 33554432
      batch-size: 16384
    properties:
      security.protocol: SASL_PLAINTEXT
      sasl.mechanism: SCRAM-SHA-512
      ssl.endpoint.identification.algorithm: ""
      sasl.jaas.config: org.apache.kafka.common.security.scram.ScramLoginModule required username='kafka' password='kafka1234';
Controller
package com.imprexion.test;



import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;


@RestController
@RequestMapping(value = "/kafka")
public class KafkaController {

    private final Producer producer;

    @Autowired
    KafkaController(Producer producer) {
        this.producer = producer;
    }

    @PostMapping(value = "/publish")
    public void sendMessageToKafkaTopic(@RequestParam("message") String message) {
        this.producer.sendMessage(message);
    }
}


Producer
package com.imprexion.test;

import javafx.scene.input.DataFormat;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.stereotype.Service;

import java.sql.Timestamp;
import java.text.SimpleDateFormat;
import java.util.Date;


@Service
public class Producer {

    private static final Logger logger = LoggerFactory.getLogger(Producer.class);
    private static final String TOPIC = "kafka_sasl_1";

    @Autowired
    private KafkaTemplate kafkaTemplate;

    public void sendMessage(String message) {
        logger.info(String.format("#### -> Producing message -> %s", message));
        for (int i = 0; i < 10000; i++) {
            SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
            String format = simpleDateFormat.format(new Date());
            long time = System.currentTimeMillis();
            message = "{ "a": " " + format + ""," +
                    "  "app_version": "4.2.1"," +
                    "  "device_id": "1f43f912c2"," +
                    "  "e": "faceID_launch"," +
                    "  "faceImage": ""," +
                    "  "p": {" +
                    "    "package": "com.imprexion.member"," +
                    "    "page": "com.Orbbec.MagicSalad2"" +
                    "    "valume": "" + i + "," +
                    "  }," +
                    "  "package_name": "com.imprexion.service.facerecognition"," +
                    "  "pre_login_id": "1f43f912c2_1626330120074"," +
                    "  "source_channel": "com.imprexion.aibar"," +
                    "  "t": "" + time + "," +
                    "  "uid": -1," +
                    "  "v": 1," +
                    "  "st":"" + time + 
                    "}";
            this.kafkaTemplate.send(TOPIC, message);

        }

    }
}
Consumer
package com.imprexion.test;


import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Service;

import java.io.IOException;


@Service
public class Consumer {
    private final Logger logger = LoggerFactory.getLogger(Producer.class);

    @KafkaListener(topics = "kafka_sasl_1", groupId = "kafka-acls-group")
    public void consume(String message) throws IOException {
        logger.info(String.format("#### -> Consumed message -> %s", message));
    }
}

Application
package com.imprexion.sendmsg;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.ComponentScan;

@SpringBootApplication
@ComponentScan(basePackages = {"com.imprexion.test"})
public class SendmsgApplication {


    public static void main(String[] args) {
        SpringApplication.run(SendmsgApplication.class, args);
    }

}

访问地址
http://localhost:9000/kafka/publish?message=hello
监控图表展示
数据生产前

数据生产后

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原文地址: http://outofmemory.cn/zaji/5707555.html

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