Tag: puppet

  • Install Kafka Manager with Puppet

    Hi,

    I will continue on this line with the install of a management tool called Kafka manager using same old Puppet.

    The main source of the project is here:

    https://github.com/yahoo/kafka-manager

    If you scroll down at packaging you will see that you have the possibility to create a .deb package for Ubuntu or Debian setup or a rpm. To do this just clone the project, go into it and run the command

    sbt debian:packageBin
    

    It will take some time but eventually it will create the required package. Now, since you have the package, you can easily ask a friend to upload it to your pipeline apt repo (this is what i did, i don’t have yet the experience on how to do that) and install and configure it via puppet. In order to do that, i “wrote” the following manifest:

    kafkamanager.pp

    class profiles::kafkamanager {
    	
    	$zookeeper_connect = hiera('kafkamanager::zookeeperconnect')
    	package {'kafka-manager':
    		ensure => installed,
    	}
    	group { 'kafka-manager':
    		ensure => 'present',	
    	}
    	user { 'kafka-manager':
    		ensure => 'present',
    		groups => 'kafka-manager'
    	}
    	
    	Group['kafka-manager'] -> User['kafka-manager']
    	
    	file { '/usr/share/kafka-manager' :
        		ensure    => directory,
        		owner     => 'kafka-manager',
        		group      => 'kafka-manager',
        		require     => [ User['kafka-manager'], Group['kafka-manager'], ],
        		recurse    => true,
    	}
    
    	file_line { 'config_zookeeper':
    	    path => '/etc/kafka-manager/application.conf',
    	    match => 'kafka-manager.zkhosts=\"kafka-manager-zookeeper:2181\"',
    	    line => "kafka-manager.zkhosts=\"${zookeeper_connect}\"",
    	    replace => true,
    	}
        
        file_line { 'enable_auth':
            path => '/etc/kafka-manager/application.conf',
            match => 'basicAuthentication.enabled=false',
            line => 'basicAuthentication.enabled=true',
            replace => true,
            }
    	service { 'kafka-manager':
    		ensure => 'running',
    		enable => true,
    		require => [ File['/usr/share/kafka-manager'], File_line['config_zookeeper'] ],	
    	}
    }

    This should be all, you are now free to login with the user and pass that you find in the application.conf file and start mapping Kafka clusters.

    Cheers!

  • Integrate Kafka with Datadog monitoring using puppet

    Hi,

    Since i was in debt with an article on how to integate Kafka monitoring using Datadog, let me tell you a couple of things about this topic. First of all, we are taking the same config of Kafka with Jolokia that was describe in following article. From the install of the brokers on our infrastructure, JMX data is published on port 9990 (this will be needed in the datadog config).

    The files you need to create for this task are as follows:

    datadogagent.pp

    class profiles::datadogagent {
      $_check_api_key = hiera('datadog_agent::api_key')
    
      contain 'datadog_agent'
      contain 'profiles::datadogagent_config_kafka'
      contain 'datadog_agent::integrations::zk'
    
      Class['datadog_agent'] -> Class['profiles::datadog_agent_config_kafka']
      Class['datadog_agent'] -> Class['datadog_agent::integrations::zk']
    }

    datadogagent_config_kafka.pp

    class profiles::datadogagent_config_kafka (
    $servers = [{'host' => 'localhost', 'port' => '9990'}]
    ) inherits datadog_agent::params {
      include datadog_agent
    
      validate_array($servers)
    
      file { "${datadog_agent::params::conf_dir}/kafka.yaml":
        ensure  => file,
        owner   => $datadog_agent::params::dd_user,
        group   => $datadog_agent::params::dd_group,
        mode    => '0600',
        content => template("${module_name}/kafka.yaml.erb"),
        require => Package[$datadog_agent::params::package_name],
        notify  => Service[$datadog_agent::params::service_name],
      }
    }
    

    And since, there isn’t yet an integration by default for the kafka on the datadog module which you can find it here:

    https://github.com/DataDog/puppet-datadog-agent

    i created in the templates directory the following file:

    kafka.yaml.erb (as you can see from the header this is actually the template given by datadog for kafka integration with specific host and port)

    ##########
    # WARNING
    ##########
    # This sample works only for Kafka >= 0.8.2.
    # If you are running a version older than that, you can refer to agent 5.2.x released
    # sample files, https://raw.githubusercontent.com/DataDog/dd-agent/5.2.1/conf.d/kafka.yaml.example
    
    instances:
    <% @servers.each do |server| -%>
      - host: <%= server['host'] %>
        port: <%= server['port'] %> # This is the JMX port on which Kafka exposes its metrics (usually 9999)
        tags:
          kafka: broker
    
    init_config:
      is_jmx: true
    
      # Metrics collected by this check. You should not have to modify this.
      conf:
        # v0.8.2.x Producers
        - include:
            domain: 'kafka.producer'
            bean_regex: 'kafka\.producer:type=ProducerRequestMetrics,name=ProducerRequestRateAndTimeMs,clientId=.*'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.producer.request_rate
        - include:
            domain: 'kafka.producer'
            bean_regex: 'kafka\.producer:type=ProducerRequestMetrics,name=ProducerRequestRateAndTimeMs,clientId=.*'
            attribute:
              Mean:
                metric_type: gauge
                alias: kafka.producer.request_latency_avg
        - include:
            domain: 'kafka.producer'
            bean_regex: 'kafka\.producer:type=ProducerTopicMetrics,name=BytesPerSec,clientId=.*'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.producer.bytes_out
        - include:
            domain: 'kafka.producer'
            bean_regex: 'kafka\.producer:type=ProducerTopicMetrics,name=MessagesPerSec,clientId=.*'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.producer.message_rate
        # v0.8.2.x Consumers
        - include:
            domain: 'kafka.consumer'
            bean_regex: 'kafka\.consumer:type=ConsumerFetcherManager,name=MaxLag,clientId=.*'
            attribute:
              Value:
                metric_type: gauge
                alias: kafka.consumer.max_lag
        - include:
            domain: 'kafka.consumer'
            bean_regex: 'kafka\.consumer:type=ConsumerFetcherManager,name=MinFetchRate,clientId=.*'
            attribute:
              Value:
                metric_type: gauge
                alias: kafka.consumer.fetch_rate
        - include:
            domain: 'kafka.consumer'
            bean_regex: 'kafka\.consumer:type=ConsumerTopicMetrics,name=BytesPerSec,clientId=.*'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.consumer.bytes_in
        - include:
            domain: 'kafka.consumer'
            bean_regex: 'kafka\.consumer:type=ConsumerTopicMetrics,name=MessagesPerSec,clientId=.*'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.consumer.messages_in
    
        # Offsets committed to ZooKeeper
        - include:
            domain: 'kafka.consumer'
            bean_regex: 'kafka\.consumer:type=ZookeeperConsumerConnector,name=ZooKeeperCommitsPerSec,clientId=.*'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.consumer.zookeeper_commits
        # Offsets committed to Kafka
        - include:
            domain: 'kafka.consumer'
            bean_regex: 'kafka\.consumer:type=ZookeeperConsumerConnector,name=KafkaCommitsPerSec,clientId=.*'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.consumer.kafka_commits
        # v0.9.0.x Producers
        - include:
            domain: 'kafka.producer'
            bean_regex: 'kafka\.producer:type=producer-metrics,client-id=.*'
            attribute:
              response-rate:
                metric_type: gauge
                alias: kafka.producer.response_rate
        - include:
            domain: 'kafka.producer'
            bean_regex: 'kafka\.producer:type=producer-metrics,client-id=.*'
            attribute:
              request-rate:
                metric_type: gauge
                alias: kafka.producer.request_rate
        - include:
            domain: 'kafka.producer'
            bean_regex: 'kafka\.producer:type=producer-metrics,client-id=.*'
            attribute:
              request-latency-avg:
                metric_type: gauge
                alias: kafka.producer.request_latency_avg
        - include:
            domain: 'kafka.producer'
            bean_regex: 'kafka\.producer:type=producer-metrics,client-id=.*'
            attribute:
              outgoing-byte-rate:
                metric_type: gauge
                alias: kafka.producer.bytes_out
        - include:
            domain: 'kafka.producer'
            bean_regex: 'kafka\.producer:type=producer-metrics,client-id=.*'
            attribute:
              io-wait-time-ns-avg:
                metric_type: gauge
                alias: kafka.producer.io_wait
    
        # v0.9.0.x Consumers
        - include:
            domain: 'kafka.consumer'
            bean_regex: 'kafka\.consumer:type=consumer-fetch-manager-metrics,client-id=.*'
            attribute:
              bytes-consumed-rate:
                metric_type: gauge
                alias: kafka.consumer.bytes_in
        - include:
            domain: 'kafka.consumer'
            bean_regex: 'kafka\.consumer:type=consumer-fetch-manager-metrics,client-id=.*'
            attribute:
              records-consumed-rate:
                metric_type: gauge
                alias: kafka.consumer.messages_in
        #
        # Aggregate cluster stats
        #
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=BrokerTopicMetrics,name=BytesOutPerSec'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.net.bytes_out.rate
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=BrokerTopicMetrics,name=BytesInPerSec'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.net.bytes_in.rate
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=BrokerTopicMetrics,name=MessagesInPerSec'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.messages_in.rate
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=BrokerTopicMetrics,name=BytesRejectedPerSec'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.net.bytes_rejected.rate
    
        #
        # Request timings
        #
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=BrokerTopicMetrics,name=FailedFetchRequestsPerSec'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.request.fetch.failed.rate
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=BrokerTopicMetrics,name=FailedProduceRequestsPerSec'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.request.produce.failed.rate
        - include:
            domain: 'kafka.network'
            bean: 'kafka.network:type=RequestMetrics,name=RequestsPerSec,request=Produce'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.request.produce.rate
        - include:
            domain: 'kafka.network'
            bean: 'kafka.network:type=RequestMetrics,name=TotalTimeMs,request=Produce'
            attribute:
              Mean:
                metric_type: gauge
                alias: kafka.request.produce.time.avg
              99thPercentile:
                metric_type: gauge
                alias: kafka.request.produce.time.99percentile
        - include:
            domain: 'kafka.network'
            bean: 'kafka.network:type=RequestMetrics,name=RequestsPerSec,request=FetchConsumer'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.request.fetch_consumer.rate
        - include:
            domain: 'kafka.network'
            bean: 'kafka.network:type=RequestMetrics,name=RequestsPerSec,request=FetchFollower'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.request.fetch_follower.rate
        - include:
            domain: 'kafka.network'
            bean: 'kafka.network:type=RequestMetrics,name=TotalTimeMs,request=FetchConsumer'
            attribute:
              Mean:
                metric_type: gauge
                alias: kafka.request.fetch_consumer.time.avg
              99thPercentile:
                metric_type: gauge
                alias: kafka.request.fetch_consumer.time.99percentile
        - include:
            domain: 'kafka.network'
            bean: 'kafka.network:type=RequestMetrics,name=TotalTimeMs,request=FetchFollower'
            attribute:
              Mean:
                metric_type: gauge
                alias: kafka.request.fetch_follower.time.avg
              99thPercentile:
                metric_type: gauge
                alias: kafka.request.fetch_follower.time.99percentile
        - include:
            domain: 'kafka.network'
            bean: 'kafka.network:type=RequestMetrics,name=TotalTimeMs,request=UpdateMetadata'
            attribute:
              Mean:
                metric_type: gauge
                alias: kafka.request.update_metadata.time.avg
              99thPercentile:
                metric_type: gauge
                alias: kafka.request.update_metadata.time.99percentile
        - include:
            domain: 'kafka.network'
            bean: 'kafka.network:type=RequestMetrics,name=TotalTimeMs,request=Metadata'
            attribute:
              Mean:
                metric_type: gauge
                alias: kafka.request.metadata.time.avg
              99thPercentile:
                metric_type: gauge
                alias: kafka.request.metadata.time.99percentile
        - include:
            domain: 'kafka.network'
            bean: 'kafka.network:type=RequestMetrics,name=TotalTimeMs,request=Offsets'
            attribute:
              Mean:
                metric_type: gauge
                alias: kafka.request.offsets.time.avg
              99thPercentile:
                metric_type: gauge
                alias: kafka.request.offsets.time.99percentile
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=KafkaRequestHandlerPool,name=RequestHandlerAvgIdlePercent'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.request.handler.avg.idle.pct.rate
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=ProducerRequestPurgatory,name=PurgatorySize'
            attribute:
              Value:
                metric_type: gauge
                alias: kafka.request.producer_request_purgatory.size
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=FetchRequestPurgatory,name=PurgatorySize'
            attribute:
              Value:
                metric_type: gauge
                alias: kafka.request.fetch_request_purgatory.size
    
        #
        # Replication stats
        #
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=ReplicaManager,name=UnderReplicatedPartitions'
            attribute:
              Value:
                metric_type: gauge
                alias: kafka.replication.under_replicated_partitions
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=ReplicaManager,name=IsrShrinksPerSec'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.replication.isr_shrinks.rate
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=ReplicaManager,name=IsrExpandsPerSec'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.replication.isr_expands.rate
        - include:
            domain: 'kafka.controller'
            bean: 'kafka.controller:type=ControllerStats,name=LeaderElectionRateAndTimeMs'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.replication.leader_elections.rate
        - include:
            domain: 'kafka.controller'
            bean: 'kafka.controller:type=ControllerStats,name=UncleanLeaderElectionsPerSec'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.replication.unclean_leader_elections.rate
        - include:
            domain: 'kafka.controller'
            bean: 'kafka.controller:type=KafkaController,name=OfflinePartitionsCount'
            attribute:
              Value:
                metric_type: gauge
                alias: kafka.replication.offline_partitions_count
        - include:
            domain: 'kafka.controller'
            bean: 'kafka.controller:type=KafkaController,name=ActiveControllerCount'
            attribute:
              Value:
                metric_type: gauge
                alias: kafka.replication.active_controller_count
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=ReplicaManager,name=PartitionCount'
            attribute:
              Value:
                metric_type: gauge
                alias: kafka.replication.partition_count
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=ReplicaManager,name=LeaderCount'
            attribute:
              Value:
                metric_type: gauge
                alias: kafka.replication.leader_count
        - include:
            domain: 'kafka.server'
            bean: 'kafka.server:type=ReplicaFetcherManager,name=MaxLag,clientId=Replica'
            attribute:
              Value:
                metric_type: gauge
                alias: kafka.replication.max_lag
    
        #
        # Log flush stats
        #
        - include:
            domain: 'kafka.log'
            bean: 'kafka.log:type=LogFlushStats,name=LogFlushRateAndTimeMs'
            attribute:
              Count:
                metric_type: rate
                alias: kafka.log.flush_rate.rate
    
    <% end -%>

    To integrate all of this node, you need to add in your fqdn.yaml the class in the format:

    ---
    classes:
     - profiles::datadogagent
    
    datadog_agent::api_key: [your key]
    

    After this runs, datadog-agent is installed and you can check it by using ps -ef | grep datadog-agent and also if you like to take a look and you should do that, you will find that there are two new files added to /etc/dd-agent/conf.d called kafka.yaml and zk.yaml.

    You are done, please feel free to login to the datadog portal and check you host.

    Cheers

  • How to deploy Prometheus infrastructure for Kafka monitoring using puppet

    Hi,

    In the last couple of days i worked on deployment of Prometheus server and agent for Kafka monitoring. In that purpose i will share with you the main points that you need to do in order to achieve this.

    First thing to do is to use the prometheus and grafana modules that you will find at the following links:

    https://forge.puppet.com/puppet/prometheus
    https://forge.puppet.com/puppet/grafana

    After these are imported in puppet you need to create the following puppet files:

    grafana.pp

    class profiles::grafana {
        class { '::grafana':
          cfg => {
            app_mode => 'production',
            server   => {
              http_port     => 8080,
            },
            database => {
              type     => 'sqlite3',
              host     => '127.0.0.1:3306',
              name     => 'grafana',
              user     => 'root',
              password => 'grafana',
            },
            users    => {
              allow_sign_up => false,
            },
          },
        }
    }

    puppetserver.pp

    class profiles::prometheusserver {
        $kafka_nodes=hiera(profiles::prometheusserver::nodes)
       
        if $kafka_nodes {
    	class {'::prometheus':
    	   global_config  => { 'scrape_interval'=> '15s', 'evaluation_interval'=> '15s', 'external_labels'=> { 'monitor'=>'master'}},
           rule_files     => [ "/etc/prometheus/alert.rules" ],
           scrape_configs => [ {'job_name'=>'prometheus','scrape_interval'=> '30s','scrape_timeout'=>'30s','static_configs'=> [{'targets'=>['localhost:9090'], 'labels'=> { 'alias'=>'Prometheus'}}]},{'job_name'=> kafka, 'scrape_interval'=> '10s', 'scrape_timeout'=> '10s', 'static_configs'=> [{'targets'=> $kafka_nodes }]}],
        }
       
        } else {
        class {'::prometheus':
    	   global_config  => { 'scrape_interval'=> '15s', 'evaluation_interval'=> '15s', 'external_labels'=> { 'monitor'=>'master'}},
           rule_files     => [ "/etc/prometheus/alert.rules" ],
           scrape_configs => [ {'job_name'=>'prometheus','scrape_interval'=> '30s','scrape_timeout'=>'30s','static_configs'=> [{'targets'=>['localhost:9090'], 'labels'=> { 'alias'=>'Prometheus'}}]}],
        }
        }
    }

    prometheusnode.pp

    class profiles_opqs::prometheusnode(
    	$jmxexporter_dir = hiera('jmxexporter::dir','/opt/jmxexporter'),
    	$jmxexporter_version = hiera('jmxexporter::version','0.9')
    ){
    	include ::prometheus::node_exporter
    	#validate_string($jmxexporter_dir)
    
    	file {"${jmxexporter_dir}":
    		ensure => 'directory',
    	}
    	file {"${jmxexporter_dir}/prometheus_config.yaml":
    		source => 'puppet:///modules/profiles/prometheus_config',
    	}
    	wget::fetch {"https://repo1.maven.org/maven2/io/prometheus/jmx/jmx_prometheus_javaagent/${jmxexporter_version}/jmx_prometheus_javaagent-${jmxexporter_version}.jar":
    	destination => "${jmxexporter_dir}/",
    	cache_dir => '/tmp/',
    	timeout => 0,
    	verbose => false,
    	unless => "test -e ${jmxexporter_dir}/jmx_prometheus_javaagent-${jmxexporter_version}.jar",
    	}	
    }

    It is true that i used the wget module to take the JMX exporter so i must give you that as well

     https://forge.puppet.com/leonardothibes/wget

    As also required is the file to configure the jmx exporter configuration file in order to translate the JMX data provided by Kafka to fields to be imported in Prometheus
    prometheus_config:

    lowercaseOutputName: true
    rules:
    - pattern : kafka.cluster<type=(.+), name=(.+), topic=(.+), partition=(.+)><>Value
      name: kafka_cluster_$1_$2
      labels:
        topic: "$3"
        partition: "$4"
    - pattern : kafka.log<type=Log, name=(.+), topic=(.+), partition=(.+)><>Value
      name: kafka_log_$1
      labels:
        topic: "$2"
        partition: "$3"
    - pattern : kafka.controller<type=(.+), name=(.+)><>(Count|Value)
      name: kafka_controller_$1_$2
    - pattern : kafka.network<type=(.+), name=(.+)><>Value
      name: kafka_network_$1_$2
    - pattern : kafka.network<type=(.+), name=(.+)PerSec, request=(.+)><>Count
      name: kafka_network_$1_$2_total
      labels:
        request: "$3"
    - pattern : kafka.network<type=(.+), name=(\w+), networkProcessor=(.+)><>Count
      name: kafka_network_$1_$2
      labels:
        request: "$3"
      type: COUNTER
    - pattern : kafka.network<type=(.+), name=(\w+), request=(\w+)><>Count
      name: kafka_network_$1_$2
      labels:
        request: "$3"
    - pattern : kafka.network<type=(.+), name=(\w+)><>Count
      name: kafka_network_$1_$2
    - pattern : kafka.server<type=(.+), name=(.+)PerSec\w*, topic=(.+)><>Count
      name: kafka_server_$1_$2_total
      labels:
        topic: "$3"
    - pattern : kafka.server<type=(.+), name=(.+)PerSec\w*><>Count
      name: kafka_server_$1_$2_total
      type: COUNTER
    
    - pattern : kafka.server<type=(.+), name=(.+), clientId=(.+), topic=(.+), partition=(.*)><>(Count|Value)
      name: kafka_server_$1_$2
      labels:
        clientId: "$3"
        topic: "$4"
        partition: "$5"
    - pattern : kafka.server<type=(.+), name=(.+), topic=(.+), partition=(.*)><>(Count|Value)
      name: kafka_server_$1_$2
      labels:
        topic: "$3"
        partition: "$4"
    - pattern : kafka.server<type=(.+), name=(.+), topic=(.+)><>(Count|Value)
      name: kafka_server_$1_$2
      labels:
        topic: "$3"
      type: COUNTER
    
    - pattern : kafka.server<type=(.+), name=(.+), clientId=(.+), brokerHost=(.+), brokerPort=(.+)><>(Count|Value)
      name: kafka_server_$1_$2
      labels:
        clientId: "$3"
        broker: "$4:$5"
    - pattern : kafka.server<type=(.+), name=(.+), clientId=(.+)><>(Count|Value)
      name: kafka_server_$1_$2
      labels:
        clientId: "$3"
    - pattern : kafka.server<type=(.+), name=(.+)><>(Count|Value)
      name: kafka_server_$1_$2
    
    - pattern : kafka.(\w+)<type=(.+), name=(.+)PerSec\w*><>Count
      name: kafka_$1_$2_$3_total
    - pattern : kafka.(\w+)<type=(.+), name=(.+)PerSec\w*, topic=(.+)><>Count
      name: kafka_$1_$2_$3_total
      labels:
        topic: "$4"
      type: COUNTER
    - pattern : kafka.(\w+)<type=(.+), name=(.+)PerSec\w*, topic=(.+), partition=(.+)><>Count
      name: kafka_$1_$2_$3_total
      labels:
        topic: "$4"
        partition: "$5"
      type: COUNTER
    - pattern : kafka.(\w+)<type=(.+), name=(.+)><>(Count|Value)
      name: kafka_$1_$2_$3_$4
      type: COUNTER
    - pattern : kafka.(\w+)<type=(.+), name=(.+), (\w+)=(.+)><>(Count|Value)
      name: kafka_$1_$2_$3_$6
      labels:
        "$4": "$5"

    Ok, so in order to put this together, we will use plain old hiera :). For the server on which you want to configure prometheus server you will need to create a role or just put it in the fqdn.yaml that looks like this:

    prometheus.yaml

    ---
    classes:
      - 'profiles::prometheusserver'
      - 'profiles::grafana'
    
    alertrules:
        -
            name: 'InstanceDown'
            condition:  'up == 0'
            timeduration: '5m'
            labels:
                -
                    name: 'severity'
                    content: 'critical'
            annotations:
                -
                    name: 'summary'
                    content: 'Instance {{ $labels.instance }} down'
                -
                    name: 'description'
                    content: '{{ $labels.instance }} of job {{ $labels.job }} has been down for more than 5 minutes.'
    

    This is as default installation, because it’s a “role”, on each prometheus host i also created a specific fqdn.yaml file to specify in order to tell what nodes should be checked for exposed metrics. Here is an example:

    ---
    profiles::prometheusserver::nodes:
        - 'kafka0:7071'
        - 'kafka1:7071'
        - 'kafka2:7071'
    

    The three nodes are as an example, you can put all the nodes on which you include the prometheus node class.
    Let me show you how this should also look:

    ---
    classes:
     - 'profiles::prometheusnode'
     
    profiles::kafka::jolokia: '-javaagent:/usr/share/java/jolokia-jvm-agent.jar -javaagent:/opt/jmxexporter/jmx_prometheus_javaagent-0.9.jar=7071:/opt/jmxexporter/prometheus_config.yaml

    Now i need to explain that jolokia variable, right? Yeah, it’s pretty straight forward. The kafka installation was already wrote, and it included the jolokia agent and our broker definition block looks like this:

    
     class { '::kafka::broker':
        config    => $broker_config,
        opts      => hiera('profiles::kafka::jolokia', '-javaagent:/usr/share/java/jolokia-jvm-agent.jar'),
        heap_opts => "-Xmx${jvm_heap_size}M -Xms${jvm_heap_size}M",
      }
    }

    So i needed to puth the jmx exporter agent beside jolokia on kafka startup, and when this will be deployed you will see the jmxexporter started as agent. Anyhow, when all is deployed you will have a prometheus config that should look like:

    ---
    global:
      scrape_interval: 15s
      evaluation_interval: 15s
      external_labels:
        monitor: master
    rule_files:
    - /etc/prometheus/alert.rules
    scrape_configs:
    - job_name: prometheus
      scrape_interval: 30s
      scrape_timeout: 30s
      static_configs:
      - targets:
        - localhost:9090
        labels:
          alias: Prometheus
    - job_name: kafka
      scrape_interval: 10s
      scrape_timeout: 10s
      static_configs:
      - targets:
        - kafka0:7071
        - kafka1:7071
        - kafka2:7071

    You can also see the nodes at Status -> Targets from the menu, and yeah, all the metrics are available by node at http://[kafka-node]:7071/metrics.

    I think this should be it, i don’t know i covered everything and there are a lot of details related to our custom installation but at least i managed to provide so details related to it. The article that helped me very much to do is can be visited here

    https://www.robustperception.io/monitoring-kafka-with-prometheus/

    Cheers!

  • Wrong Kafka configuration and deployment using puppet

    Hi,

    I just want to share with you one case that we have last week and that involved some wrong kafka deplyment from puppet that actually filled the filesystems and got our colleagues that were using it for a transport layer on ELK.

    Lets start with the begining, we have some puppet code to deploy and configure kafka machines. To keep it simple the broker config block from puppet looks like this:

    $broker_config = {
        'broker.id'                     => '-1', # always set broker.id to -1.
        # broker specific config
        'zookeeper.connect'             => hiera('::kafka::zookeeper_connect', $zookeeper_connect),
        'inter.broker.protocol.version' => hiera('::kafka::inter_broker_protocol_version', $kafka_version),
        'log.dir'                       => hiera('::kafka::log_dir', '/srv/kafka-logs'),
        'log.dirs'                      => hiera('::kafka::log_dirs', '/srv/kafka-logs'),
        'log.retention.hours'           => hiera('::kafka::log_retention_hours', $days7),
        'log.retention.bytes'           => hiera('::kafka::log_retention_bytes', '-1'),
        # confiure availability
        'num.partitions'                => hiera('::kafka::num_partitions', 256),
        'default.replication.factor'    => hiera('::kafka::default_replication_factor', $default_replication_factor),
        # configurre administratability (this is a word now)
        'delete.topic.enable'           => hiera('::kafka::delete_topic_enable', 'true'),
      }
    

    As you can see, there are two fields that need to be carefully configured, one is the log_retention_bytes and the other is the num_partitions. I am underlying this for a very simple reason, if we will take a look in the kafka server.properies file which the engine use to start the broker, we will see

    log.retention.bytes=107374182400
    num.partitions=256

     Now, the first one is the default value (and it means the maximum size per partition), and if you go to an online converter you will see that it means 100GB. This shouldn’t be a problem if you override it topic based, and even more if you manually create a topic with one or two partitions and you have the required space. But our case was different, they were using for logstash which created a default topic configuration with 256 partitions and if the maximum size was 100GB then it though it had 25600GB which i am not mistaken should also translate in 25TB (yeah, that it’s usually more than enough for a ELK instance).

    Since we were running only three nodes with 100GB filesystem each, you can imagine that it filled up and the servers crashed.

    Now there are two ways to avoid this, depending the number of consumers in the consumer group, and also the retention period. If you have only one consumer and you want to have data for a larger period of time, you can leave it at 100GB (if you have that much storage available) and manually create a topic with 1 partition and a replication factor equal to the number of nodes that you want to use for high availability, or you can leave the partition number to 256, and you highly decrease the retention bytes value. This translates in an equal distribution of data on multiple consumers, but it comes with a lesser storage period of time (now it is also true that it depends on the amount and type of data that you are transferring).

    The solution that we adopted is to leave the partition number unchanged and decrease the partition size to 200MB. Keep you informed how it works. 🙂

    Cheers!

  • Install eyaml module on puppet master

    Hi,

    Today i will show how i installed module used for data encrypt in order to safely include it in hiera yaml files)
    It really simple as described on https://github.com/voxpupuli/hiera-eyaml. The actual step that i couldn’t find explicitly written in the doku and i had to figure it out myself is that you need to modify the config.yaml needed by the module.

    1. gem install hiera-eyaml
    2. puppetserver gem install hiera-eyaml
    3. eyaml createkeys
    4. mv ./keys /etc/puppetlabs/puppet/eyaml
    5. $ chown -R puppet:puppet /etc/puppetlabs/puppet/eyaml
      $ chmod -R 0500 /etc/puppetlabs/puppet/eyaml
      $ chmod 0400 /etc/puppetlabs/puppet/eyaml/*.pem
      $ ls -lha /etc/puppetlabs/puppet/eyaml
      -r——– 1 puppet puppet 1.7K Sep 24 16:24 private_key.pkcs7.pem
      -r——– 1 puppet puppet 1.1K Sep 24 16:24 public_key.pkcs7.pem
    6.  vim /etc/eyaml/config.yaml and add following content:
      ---
      pkcs7_private_key: '/etc/puppetlabs/puppet/eyaml/private_key.pkcs7.pem'
      pkcs7_public_key: '/etc/puppetlabs/puppet/eyaml/public_key.pkcs7.pem'

    If the last step is not executed, you will get the error: [hiera-eyaml-core] No such file or directory – ./keys/public_key.pkcs7.pem

    After these configurations you should be able to encrypt files or strings. Short example:

    eyaml encrypt -s 'test'
    [hiera-eyaml-core] Loaded config from /etc/eyaml/config.yaml
    string: ENC[PKCS7,MIIBeQYJKoZIhvcNAQcDoIIBajCCAWYCAQAxggEhMIIBHQIBADAFMAACAQEwDQYJKoZIhvcNAQEBBQAEggEAvWHMltzNiYnp0iG6vl6tsgayYimoFQpCFeA8wdE3k6h2OGZAXHLOI+ueEcv+SXVtOsqbP2LxPHe19zJS9cLV4tHu1rUEAW2gstkImI4FoV1/SoPrXNsBBXuoG3j7R4NGPpkhvOQEYIRTT9ssh9hCrzkEMrZ5pZDhS4lNn01Ax1tX99NdmtXaGvTTML/kV061YyN3FaeztSUc01WwpeuHQ+nLouuoVxUUOy/d/5lD5wLKq9t8BYeFG6ekq/D9iGO6D/SNPB0UpVqdCFraAN7rIRNfVDaRbffCSdE59AZr/+atSdUk9cI0oYpG25tHT9x3eWYNNeCLrVAoVMiZ01uR7zA8BgkqhkiG9w0BBwEwHQYJYIZIAWUDBAEqBBBHO9P8JfkovKLMdtvaIxAzgBAjiu0/l+Hm+Xaezhp2AWjj]
    
    OR
    
    block: >
        ENC[PKCS7,MIIBeQYJKoZIhvcNAQcDoIIBajCCAWYCAQAxggEhMIIBHQIBADAFMAACAQEw
        DQYJKoZIhvcNAQEBBQAEggEAvWHMltzNiYnp0iG6vl6tsgayYimoFQpCFeA8
        wdE3k6h2OGZAXHLOI+ueEcv+SXVtOsqbP2LxPHe19zJS9cLV4tHu1rUEAW2g
        stkImI4FoV1/SoPrXNsBBXuoG3j7R4NGPpkhvOQEYIRTT9ssh9hCrzkEMrZ5
        pZDhS4lNn01Ax1tX99NdmtXaGvTTML/kV061YyN3FaeztSUc01WwpeuHQ+nL
        ouuoVxUUOy/d/5lD5wLKq9t8BYeFG6ekq/D9iGO6D/SNPB0UpVqdCFraAN7r
        IRNfVDaRbffCSdE59AZr/+atSdUk9cI0oYpG25tHT9x3eWYNNeCLrVAoVMiZ
        01uR7zA8BgkqhkiG9w0BBwEwHQYJYIZIAWUDBAEqBBBHO9P8JfkovKLMdtva
        IxAzgBAjiu0/l+Hm+Xaezhp2AWjj]
    

    Will write something similar for Hiera configuration to use the desired backend.

    Cheers!