本文已经收录在 Prometheus 合集 Prometheus 都可以采集那些指标？-- 常用 Exporter 合集 中。
Kafka 是一种分布式的，基于发布 / 订阅的消息系统。原本开发自 LinkedIn，用作 LinkedIn 的活动流（Activity Stream）和运营数据处理管道（Pipeline）的基础。现在很多公司在都在使用 Kafka ，所以我找了一个 Kafka 的 Exporter 来采集 Kafka 的指标。
这个 Kafka Exporter 的地址是 https://github.com/danielqsj/kafka_exporter ，之前作者 2 年没有更新项目，今年突然更新了。本来以为这个工具已经没人维护被弃用了，现在发现还可以继续使用。当前最新版本是 v1.4.2 ，发布于 2021.09.16 。
这个 Kafka Exporter 支持 Apache Kafka 最低版本为 v0.10.1.0 版本。
安装
Kafka Exporter 可以直接用二进制运行，也可以用 Docker 来运行。
二进制下载地址为 https://github.com/danielqsj/kafka_exporter/releases
Docker image 下载地址为 https://hub.docker.com/r/danielqsj/kafka-exporter/tags ，看到标签为 latest 的镜像是 17 天前推送的，也就是大约 11 月初的样子，比稳定版 v1.4.2 要晚很多，可能年底还会有一次版本更新。
启动 二进制的 命令为
kafka_exporter --kafka.server=kafka:9092 [--kafka.server=another-server ...]
注意这里是要 Cluster 的 IP 地址。
启动 Docker image 的命令为
docker run -ti --rm -p 9308:9308 danielqsj/kafka-exporter:v1.4.2 --kafka.server=kafka:9092 [--kafka.server=another-server ...]
我打印了 Kafka Exporter 的帮助信息，里边有很多的参数可以使用。
[Erdong@kafka01 kafka_exporter-1.4.2.linux-amd64]$ ./kafka_exporter --helpusage: kafka_exporter [<flags>]
Flags: -h, --help Show context-sensitive help (also try --help-long and --help-man). --web.listen-address=":9308" Address to listen on for web interface and telemetry. --web.telemetry-path="/metrics" Path under which to expose metrics. --topic.filter=".*" Regex that determines which topics to collect. --group.filter=".*" Regex that determines which consumer groups to collect. --log.enable-sarama Turn on Sarama logging. --kafka.server=kafka:9092 ... Address (host:port) of Kafka server. --sasl.enabled Connect using SASL/PLAIN. --sasl.handshake Only set this to false if using a non-Kafka SASL proxy. --sasl.username="" SASL user name. --sasl.password="" SASL user password. --sasl.mechanism="" The SASL SCRAM SHA algorithm sha256 or sha512 or gssapi as mechanism --sasl.service-name="" Service name when using kerberos Auth --sasl.kerberos-config-path="" Kerberos config path --sasl.realm="" Kerberos realm --sasl.kerberos-auth-type="" Kerberos auth type. Either 'keytabAuth' or 'userAuth' --sasl.keytab-path="" Kerberos keytab file path --tls.enabled Connect to Kafka using TLS. --tls.server-name="" Used to verify the hostname on the returned certificates unless tls.insecure-skip-tls-verify is given. The kafka server's name should be given. --tls.ca-file="" The optional certificate authority file for Kafka TLS client authentication. --tls.cert-file="" The optional certificate file for Kafka client authentication. --tls.key-file="" The optional key file for Kafka client authentication. --server.tls.enabled Enable TLS for web server. --server.tls.mutual-auth-enabled Enable TLS client mutual authentication. --server.tls.ca-file="" The certificate authority file for the web server. --server.tls.cert-file="" The certificate file for the web server. --server.tls.key-file="" The key file for the web server. --tls.insecure-skip-tls-verify If true, the server's certificate will not be checked for validity. This will make your HTTPS connections insecure. --kafka.version="2.0.0" Kafka broker version --use.consumelag.zookeeper if you need to use a group from zookeeper --zookeeper.server=localhost:2181 ... Address (hosts) of zookeeper server. --kafka.labels="" Kafka cluster name --refresh.metadata="30s" Metadata refresh interval --offset.show-all Whether show the offset/lag for all consumer group, otherwise, only show connected consumer groups --concurrent.enable If true, all scrapes will trigger kafka operations otherwise, they will share results. WARN: This should be disabled on large clusters --topic.workers=100 Number of topic workers --verbosity=0 Verbosity log level --log.level=info Only log messages with the given severity or above. One of: [debug, info, warn, error] --log.format=logfmt Output format of log messages. One of: [logfmt, json] --version Show application version.
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指标
使用 这个 Exporter 可以采集以下这些类型，比如 Brokers、Topics、Consumer Groups、
关于 Brokers 主要是 Kafka 的数量。
# HELP kafka_brokers Number of Brokers in the Kafka Cluster.# TYPE kafka_brokers gaugekafka_brokers 3
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关于 Topics 的指标就多了，
kafka_topic_partitions Number of partitions for this Topic
kafka_topic_partition_current_offset Current Offset of a Broker at Topic/Partition
kafka_topic_partition_oldest_offset Oldest Offset of a Broker at Topic/Partition
kafka_topic_partition_in_sync_replica Number of In-Sync Replicas for this Topic/Partition
kafka_topic_partition_leader Leader Broker ID of this Topic/Partition
kafka_topic_partition_leader_is_preferred 1 if Topic/Partition is using the Preferred Broker
kafka_topic_partition_replicas Number of Replicas for this Topic/Partition
kafka_topic_partition_under_replicated_partition 1 if Topic/Partition is under Replicated
这些指标的输出样例如下：
# HELP kafka_topic_partitions Number of partitions for this Topic# TYPE kafka_topic_partitions gaugekafka_topic_partitions{topic="__consumer_offsets"} 50
# HELP kafka_topic_partition_current_offset Current Offset of a Broker at Topic/Partition# TYPE kafka_topic_partition_current_offset gaugekafka_topic_partition_current_offset{partition="0",topic="__consumer_offsets"} 0
# HELP kafka_topic_partition_oldest_offset Oldest Offset of a Broker at Topic/Partition# TYPE kafka_topic_partition_oldest_offset gaugekafka_topic_partition_oldest_offset{partition="0",topic="__consumer_offsets"} 0
# HELP kafka_topic_partition_in_sync_replica Number of In-Sync Replicas for this Topic/Partition# TYPE kafka_topic_partition_in_sync_replica gaugekafka_topic_partition_in_sync_replica{partition="0",topic="__consumer_offsets"} 3
# HELP kafka_topic_partition_leader Leader Broker ID of this Topic/Partition# TYPE kafka_topic_partition_leader gaugekafka_topic_partition_leader{partition="0",topic="__consumer_offsets"} 0
# HELP kafka_topic_partition_leader_is_preferred 1 if Topic/Partition is using the Preferred Broker# TYPE kafka_topic_partition_leader_is_preferred gaugekafka_topic_partition_leader_is_preferred{partition="0",topic="__consumer_offsets"} 1
# HELP kafka_topic_partition_replicas Number of Replicas for this Topic/Partition# TYPE kafka_topic_partition_replicas gaugekafka_topic_partition_replicas{partition="0",topic="__consumer_offsets"} 3
# HELP kafka_topic_partition_under_replicated_partition 1 if Topic/Partition is under Replicated# TYPE kafka_topic_partition_under_replicated_partition gaugekafka_topic_partition_under_replicated_partition{partition="0",topic="__consumer_offsets"} 0
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对于 Consumer Groups 有 2 个指标，
这两个指标的样例如下：
# HELP kafka_consumergroup_current_offset Current Offset of a ConsumerGroup at Topic/Partition# TYPE kafka_consumergroup_current_offset gaugekafka_consumergroup_current_offset{consumergroup="KMOffsetCache-kafka-manager-3806276532-ml44w",partition="0",topic="__consumer_offsets"} -1
# HELP kafka_consumergroup_lag Current Approximate Lag of a ConsumerGroup at Topic/Partition# TYPE kafka_consumergroup_lag gaugekafka_consumergroup_lag{consumergroup="KMOffsetCache-kafka-manager-3806276532-ml44w",partition="0",topic="__consumer_offsets"} 1
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关于这些指标的 Grafana 展示，作者在三年前上传了一个到 Grafana Dashboards 里，我感觉已经过期了，有时间自己画一个吧。
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