Monitor infrastructure

Grafana integrations

Integrations reference

Kafka

Grafana Cloud

Kafka integration for Grafana Cloud

Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.

This integration includes 14 useful alerts and 7 pre-built dashboards to help monitor and visualize Kafka metrics and logs.

Before you begin

For the integration to work, you must configure a JMX exporter on each instance composing your Kafka Cluster, including all brokers, zookeepers, ksqlDB, schema registries, and Kafka Connect nodes.

Each of these instances has its own JMX Exporter config file. The following files should be used for each respective Kafka component. For more details on how to configure your Kafka JVM with the JMX exporter, refer to the JMX Exporter documentation.

We strongly recommend that you configure a separate user for Grafana Alloy and give it only the strictly mandatory security privileges necessary for monitoring your node.

Install Kafka integration for Grafana Cloud

In your Grafana Cloud stack, click Connections in the left-hand menu.
Find Kafka and click its tile to open the integration.
Review the prerequisites in the Configuration Details tab and set up Grafana Agent to send Kafka metrics and logs to your Grafana Cloud instance.
Click Install to add this integration’s pre-built dashboards and alerts to your Grafana Cloud instance, and you can start monitoring your Kafka setup.

Configuration snippets for Grafana Alloy

Advanced mode

To instruct Grafana Alloy to scrape your Kafka nodes, go though the subsequent instructions.

The snippets provide examples to guide you through the configuration process.

First, manually copy and append the following snippets into your Grafana Alloy configuration file.

Then follow the instructions below to modify the necessary variables.

Advanced metrics snippets

discovery.relabel "metrics_integrations_kafka" {
    targets = [{
        __address__ = "kafka-node:7001",
    }]

    rule {
        target_label = "instance"
        replacement  = "<your-instance-name>"
    }

    rule {
        target_label = "kafka_cluster"
        replacement  = "<your-cluster-name>"
    }
}
discovery.relabel "metrics_integrations_kafka_zookeeper" {
    targets = [{
        __address__ = "zookeeper-node:7001",
    }]

    rule {
        target_label = "instance"
        replacement  = "<your-instance-name>"
    }

    rule {
        target_label = "kafka_cluster"
        replacement  = "<your-cluster-name>"
    }

}
discovery.relabel "metrics_integrations_kafka_connect" {
    targets = [{
        __address__ = "kafka-connect-node:7001",
    }]

    rule {
        target_label = "instance"
        replacement  = "<your-instance-name>"
    }

    rule {
        target_label = "kafka_cluster"
        replacement  = "<your-cluster-name>"
    }

}
discovery.relabel "metrics_integrations_kafka_schemaregistry" {
    targets = [{
        __address__ = "kafka-schemaregistry-node:7001",
    }]

    rule {
        target_label = "instance"
        replacement  = "<your-instance-name>"
    }

    rule {
        target_label = "kafka_cluster"
        replacement  = "<your-cluster-name>"
    }

}
discovery.relabel "metrics_integrations_kafka_ksqldb" {
    targets = [{
        __address__ = "kafka-ksqldb-node:7001",
    }]

    rule {
        target_label = "instance"
        replacement  = "<your-instance-name>"
    }

    rule {
        target_label = "kafka_cluster"
        replacement  = "<your-cluster-name>"
    }
}
prometheus.scrape "metrics_integrations_kafka" {
    targets    = concat(discovery.relabel.metrics_integrations_kafka.output, discovery.relabel.metrics_integrations_kafka_zookeeper.output, discovery.relabel.metrics_integrations_kafka_connect.output, discovery.relabel.metrics_integrations_kafka_schemaregistry.output, discovery.relabel.metrics_integrations_kafka_ksqldb.output)
    forward_to = [prometheus.remote_write.metrics_service.receiver]
    job_name   = "integrations/kafka"
}

After enabling the JMX exporter in each node, instruct Grafana Alloy to scrape them.

One discovery.relabel must be added for each node composing your cluster (Kafka Server, Schema Registry, ksqlDB, Zookeeper, Kafka Connect) to avoid instance label conflicts.

Make sure to match the name instance label name used in the exporter snippet for the Kafka Server nodes.

Configure the following properties within each discovery.relabel component:

__address__: The address to your Kafka node.
<your-instance-name>: The instance label for all metrics scraped from this Kafka node.
<your-cluster-name>: The kafka_cluster label to group your Kafka nodes within a cluster. Set the same value for all nodes within your cluster.

Finally, reference each discovery.relabel component within the targets property of the prometheus.scrape component.

Advanced integrations snippets

prometheus.exporter.kafka "integrations_kafka_exporter" {
    kafka_uris = ["kafka-node1:9091"]
}
discovery.relabel "integrations_kafka_exporter" {
    targets = prometheus.exporter.kafka.integrations_kafka_exporter.targets

    rule {
        target_label = "job"
        replacement  = "integrations/kafka"
    }

    rule {
        target_label = "kafka_cluster"
        replacement  = "<your-cluster-name>"
    }

    rule {
        target_label = "instance"
        replacement  = "<your-instance-name>"
    }
}
prometheus.scrape "integrations_kafka_exporter" {
    targets    = discovery.relabel.integrations_kafka_exporter.output
    forward_to = [prometheus.remote_write.metrics_service.receiver]
    job_name   = "integrations/kafka_exporter"
}

To monitor consumption lag, you must add a pair of prometheus.exporter.kafka and discovery.relabel to your Grafana Alloy configuration file for each Kafka Server you monitor, to avoid instance label conflicts.

Configure the following property within the prometheus.exporter.kafka component:

kafka_uris: The URI to connect to your Kafka Server node.

Refer to prometheus.exporter.kafka in Grafana Alloy reference documentation for a complete description of the configuration options.

Configure the following properties within the discovery.relabel component:

<your-instance-name>: this will set the instance label for all metrics from this Kafka Server node.
<your-cluster-name>: this will set the kafka_cluster label to group your Kafka nodes within a cluster. Set the same value for all nodes within your cluster.

Reference each discovery.relabel component within the targets property of prometheus.scrape component.

Finally, reference each prometheus.exporter.kafka component within the targets property of the prometheus.scrape component.

Advanced logs snippets

darwin

local.file_match "logs_integrations_integrations_kafka" {
	path_targets = [{
		__address__ = "localhost",
		__path__    = "/var/log/kafka-server/server.log",
		instance    = constants.hostname,
		job         = "integrations/kafka",
        kafka_cluster = "<your-cluster-name>",
	}]
}

loki.process "logs_integrations_integrations_kafka" {
	forward_to = [loki.write.grafana_cloud_loki.receiver]

	stage.multiline {
		firstline     = `^\[(\d+-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\]`
		max_lines     = 0
		max_wait_time = "3s"
	}
	stage.regex {
		expression = `\[(?P<timestamp>\d+-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\] (?P<level>[A-Z]+) \[(?P<context>.+?)\] (?P<msg>(.+)) \((?P<logger>.+)\)(?P<exception>(?s:.*))`
	}
    stage.template {
        source   = "level"
        template = "{{ .level | ToLower }}"
    }
	stage.labels {
		values = {
			level = null,
            logger = null,
		}
	}
}

loki.source.file "logs_integrations_integrations_kafka" {
	targets    = local.file_match.logs_integrations_integrations_kafka.targets
	forward_to = [loki.process.logs_integrations_integrations_kafka.receiver]
}

To monitor your Kafka brokers logs, you will use a combination of the following components:

local.file_match defines where to find the log file to be scraped. Change the following properties according to your environment:
- __path__: The path to the log file.
- instance label: constants.hostname sets the instance label to your Grafana Alloy server hostname. If that is not suitable, change it to a value uniquely identifies this Kafka broker instance. Make sure this label value is the same for all telemetry data collected for this instance.
- kafka_cluster label: Kafka cluster identifier.
loki.process defines how to process logs before sending it to Loki.
loki.source.file sends logs to Loki.

linux

local.file_match "logs_integrations_integrations_kafka" {
	path_targets = [{
		__address__ = "localhost",
		__path__    = "/var/log/kafka-server/server.log",
		instance    = constants.hostname,
		job         = "integrations/kafka",
        kafka_cluster = "<your-cluster-name>",
	}]
}

loki.process "logs_integrations_integrations_kafka" {
	forward_to = [loki.write.grafana_cloud_loki.receiver]

	stage.multiline {
		firstline     = `^\[(\d+-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\]`
		max_lines     = 0
		max_wait_time = "3s"
	}
	stage.regex {
		expression = `\[(?P<timestamp>\d+-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\] (?P<level>[A-Z]+) \[(?P<context>.+?)\] (?P<msg>(.+)) \((?P<logger>.+)\)(?P<exception>(?s:.*))`
	}
    stage.template {
        source   = "level"
        template = "{{ .level | ToLower }}"
    }
	stage.labels {
		values = {
			level = null,
            logger = null,
		}
	}
}

loki.source.file "logs_integrations_integrations_kafka" {
	targets    = local.file_match.logs_integrations_integrations_kafka.targets
	forward_to = [loki.process.logs_integrations_integrations_kafka.receiver]
}

To monitor your Kafka brokers logs, you will use a combination of the following components:

local.file_match defines where to find the log file to be scraped. Change the following properties according to your environment:
- __path__: The path to the log file.
- instance label: constants.hostname sets the instance label to your Grafana Alloy server hostname. If that is not suitable, change it to a value uniquely identifies this Kafka broker instance. Make sure this label value is the same for all telemetry data collected for this instance.
- kafka_cluster label: Kafka cluster identifier.
loki.process defines how to process logs before sending it to Loki.
loki.source.file sends logs to Loki.

windows

local.file_match "logs_integrations_integrations_kafka" {
	path_targets = [{
		__address__ = "localhost",
		__path__    = "C:/kafka/kafka-logs/server.log",
		instance    = constants.hostname,
		job         = "integrations/kafka",
        kafka_cluster = "<your-cluster-name>",
	}]
}

loki.process "logs_integrations_integrations_kafka" {
	forward_to = [loki.write.grafana_cloud_loki.receiver]

	stage.multiline {
		firstline     = `^\[(\d+-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\]`
		max_lines     = 0
		max_wait_time = "3s"
	}
	stage.regex {
		expression = `\[(?P<timestamp>\d+-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\] (?P<level>[A-Z]+) \[(?P<context>.+?)\] (?P<msg>(.+)) \((?P<logger>.+)\)(?P<exception>(?s:.*))`
	}
    stage.template {
        source   = "level"
        template = "{{ .level | ToLower }}"
    }
	stage.labels {
		values = {
			level = null,
            logger = null,
		}
	}
}

loki.source.file "logs_integrations_integrations_kafka" {
	targets    = local.file_match.logs_integrations_integrations_kafka.targets
	forward_to = [loki.process.logs_integrations_integrations_kafka.receiver]
}

To monitor your Kafka brokers logs, you will use a combination of the following components:

local.file_match defines where to find the log file to be scraped. Change the following properties according to your environment:
- __path__: The path to the log file.
- instance label: constants.hostname sets the instance label to your Grafana Alloy server hostname. If that is not suitable, change it to a value uniquely identifies this Kafka broker instance. Make sure this label value is the same for all telemetry data collected for this instance.
- kafka_cluster label: Kafka cluster identifier.
loki.process defines how to process logs before sending it to Loki.
loki.source.file sends logs to Loki.

Grafana Agent static configuration (deprecated)

The following section shows configuration for running Grafana Agent in static mode which is deprecated. You should use Grafana Alloy for all new deployments.

Before you begin

In order for the integration to work, you must configure a JMX exporter on each instance composing your Kafka cluster, including all brokers, zookeepers, ksqldb, schema registries and kafka connect nodes.

Each of these instances has its own JMX exporter config file. The following files should be used for each respective kafka component. For more details on how to configure your Kafka JVM with the JMX exporter, please refer to the JMX Exporter documentation.

Please note, that JVM metrics are only available if JMX exporter is deployed with ‘javaagent’, not ‘http-server’ mode.

We strongly recommend that you configure a separate user for the agent, and give it only the strictly mandatory security privileges necessary for monitoring your node, as per the documentation.

Install Kafka integration for Grafana Cloud

In your Grafana Cloud stack, click Connections in the left-hand menu.
Find Kafka and click its tile to open the integration.
Review the prerequisites in the Configuration Details tab and set up Grafana Agent to send Kafka metrics and logs to your Grafana Cloud instance.
Click Install to add this integration’s pre-built dashboards and alerts to your Grafana Cloud instance, and you can start monitoring your Kafka setup.

Post-install configuration for the Kafka integration

After enabling the metrics generation, instruct Grafana Agent to scrape your Kafka nodes.

The JMX exporter exposes a /metrics endpoint. To scrape it, add the snippets above to your agent configuration file.

Make sure to change targets in the snippets according to your environment.

You also need to configure the kafka_cluster label in each snippet to be able to group your Kafka nodes within the dashboards and alerts.

If you want to monitor topics, consumer groups stats as well as consumption lag, you will need to enable the kafka_exporter, which is embbeded in the Grafana Agent.

Enable the integration by adding the provided snippet to your agent configuration file.

For a full description of configuration options see Grafana Agent configuration reference in the agent documentation.

For best dashboards experience and in order to see metrics and logs correlated ensure the following:

kafka_cluster and instance labels values must match for kafka_exporter (integrations), metrics, and logs in the Agent configuration file.
instance label must be set to a value that uniquely identifies your Kafka broker node. It is placed automatically by the config snippets.

Configuration snippets for Grafana Agent

Below integrations, insert the following lines and change the URLs according to your environment:

  kafka_exporter: # one job per node
    enabled: true
    kafka_uris: ['kafka-node1:9091']          
    instance: '<your-instance-name>'
    relabel_configs:
    - replacement: 'integrations/kafka'
      target_label: job
    - replacement: '<your-cluster-name>'
      target_label: kafka_cluster

Below metrics.configs.scrape_configs, insert the following lines and change the URLs according to your environment:

    - job_name: integrations/kafka # one job per node
      relabel_configs:
        - replacement: '<your-instance-name>'
          target_label: instance
        - replacement: '<your-cluster-name>'
          target_label: kafka_cluster
      static_configs:
        - targets: ['kafka-node:7001']
    - job_name: integrations/kafka-zookeeper # one job per node
      relabel_configs:
        - replacement: '<your-instance-name>'
          target_label: instance
        - replacement: '<your-cluster-name>'
          target_label: kafka_cluster
        - replacement: 'integrations/kafka'
          target_label: job
      static_configs:
        - targets: ['zookeeper-node:7001']
    - job_name: integrations/kafka-connect # one job per node
      relabel_configs:
        - replacement: '<your-instance-name>'
          target_label: instance
        - replacement: '<your-cluster-name>'
          target_label: kafka_cluster
        - replacement: 'integrations/kafka'
          target_label: job
      static_configs:
        - targets: ['kafka-connect-node:7001']
    - job_name: integrations/kafka-schemaregistry # one job per node
      relabel_configs:
        - replacement: '<your-instance-name>'
          target_label: instance
        - replacement: '<your-cluster-name>'
          target_label: kafka_cluster
        - replacement: 'integrations/kafka'
          target_label: job
      static_configs:
        - targets: ['kafka-schemaregistry-node:7001']
    - job_name: integrations/kafka-ksqldb # one job per node
      relabel_configs:
        - replacement: '<your-instance-name>'
          target_label: instance
        - replacement: '<your-cluster-name>'
          target_label: kafka_cluster
        - replacement: 'integrations/kafka'
          target_label: job
      static_configs:
        - targets: ['kafka-ksqldb-node:7001']

Below logs.configs.scrape_configs, insert the following lines according to your environment.

    - job_name: integrations/kafka
      static_configs:
      - targets:
        - localhost
        labels:
          kafka_cluster: '<your-cluster-name>'
          job: integrations/kafka
          instance: '<your-instance-name>'
          __path__: /var/log/kafka/server.log
      pipeline_stages:
        - multiline:
            firstline: '^\[(\d+-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\]'
        # https://regex101.com/r/T4qelN/1
        - regex:
            # Flag (?s:.*) needs to be set for regex stage to capture full traceback log in the extracted map.
            expression: '\[(?P<timestamp>\d+-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\] (?P<level>[A-Z]+) \[(?P<context>.+?)\] (?P<msg>(.+)) \((?P<logger>.+)\)(?P<exception>(?s:.*))'
        - template:
            source: level
            template: "{{ .level | ToLower }}"
        - labels:
            level:
            logger:

Full example configuration for Grafana Agent

Refer to the following Grafana Agent configuration for a complete example that contains all the snippets used for the Kafka integration. This example also includes metrics that are sent to monitor your Grafana Agent instance.

integrations:
  prometheus_remote_write:
  - basic_auth:
      password: <your_prom_pass>
      username: <your_prom_user>
    url: <your_prom_url>
  agent:
    enabled: true
    relabel_configs:
    - action: replace
      source_labels:
      - agent_hostname
      target_label: instance
    - action: replace
      target_label: job
      replacement: "integrations/agent-check"
    metric_relabel_configs:
    - action: keep
      regex: (prometheus_target_sync_length_seconds_sum|prometheus_target_scrapes_.*|prometheus_target_interval.*|prometheus_sd_discovered_targets|agent_build.*|agent_wal_samples_appended_total|process_start_time_seconds)
      source_labels:
      - __name__
  # Add here any snippet that belongs to the `integrations` section.
  # For a correct indentation, paste snippets copied from Grafana Cloud at the beginning of the line.
  kafka_exporter: # one job per node
    enabled: true
    kafka_uris: ['kafka-node1:9091']          
    instance: '<your-instance-name>'
    relabel_configs:
    - replacement: 'integrations/kafka'
      target_label: job
    - replacement: '<your-cluster-name>'
      target_label: kafka_cluster
logs:
  configs:
  - clients:
    - basic_auth:
        password: <your_loki_pass>
        username: <your_loki_user>
      url: <your_loki_url>
    name: integrations
    positions:
      filename: /tmp/positions.yaml
    scrape_configs:
      # Add here any snippet that belongs to the `logs.configs.scrape_configs` section.
      # For a correct indentation, paste snippets copied from Grafana Cloud at the beginning of the line.
    - job_name: integrations/kafka
      static_configs:
      - targets:
        - localhost
        labels:
          kafka_cluster: '<your-cluster-name>'
          job: integrations/kafka
          instance: '<your-instance-name>'
          __path__: /var/log/kafka/server.log
      pipeline_stages:
        - multiline:
            firstline: '^\[(\d+-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\]'
        # https://regex101.com/r/T4qelN/1
        - regex:
            # Flag (?s:.*) needs to be set for regex stage to capture full traceback log in the extracted map.
            expression: '\[(?P<timestamp>\d+-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\] (?P<level>[A-Z]+) \[(?P<context>.+?)\] (?P<msg>(.+)) \((?P<logger>.+)\)(?P<exception>(?s:.*))'
        - template:
            source: level
            template: "{{ .level | ToLower }}"
        - labels:
            level:
            logger:
metrics:
  configs:
  - name: integrations
    remote_write:
    - basic_auth:
        password: <your_prom_pass>
        username: <your_prom_user>
      url: <your_prom_url>
    scrape_configs:
      # Add here any snippet that belongs to the `metrics.configs.scrape_configs` section.
      # For a correct indentation, paste snippets copied from Grafana Cloud at the beginning of the line.
    - job_name: integrations/kafka # one job per node
      relabel_configs:
        - replacement: '<your-instance-name>'
          target_label: instance
        - replacement: '<your-cluster-name>'
          target_label: kafka_cluster
      static_configs:
        - targets: ['kafka-node:7001']
    - job_name: integrations/kafka-zookeeper # one job per node
      relabel_configs:
        - replacement: '<your-instance-name>'
          target_label: instance
        - replacement: '<your-cluster-name>'
          target_label: kafka_cluster
        - replacement: 'integrations/kafka'
          target_label: job
      static_configs:
        - targets: ['zookeeper-node:7001']
    - job_name: integrations/kafka-connect # one job per node
      relabel_configs:
        - replacement: '<your-instance-name>'
          target_label: instance
        - replacement: '<your-cluster-name>'
          target_label: kafka_cluster
        - replacement: 'integrations/kafka'
          target_label: job
      static_configs:
        - targets: ['kafka-connect-node:7001']
    - job_name: integrations/kafka-schemaregistry # one job per node
      relabel_configs:
        - replacement: '<your-instance-name>'
          target_label: instance
        - replacement: '<your-cluster-name>'
          target_label: kafka_cluster
        - replacement: 'integrations/kafka'
          target_label: job
      static_configs:
        - targets: ['kafka-schemaregistry-node:7001']
    - job_name: integrations/kafka-ksqldb # one job per node
      relabel_configs:
        - replacement: '<your-instance-name>'
          target_label: instance
        - replacement: '<your-cluster-name>'
          target_label: kafka_cluster
        - replacement: 'integrations/kafka'
          target_label: job
      static_configs:
        - targets: ['kafka-ksqldb-node:7001']
  global:
    scrape_interval: 60s
  wal_directory: /tmp/grafana-agent-wal

Dashboards

The Kafka integration installs the following dashboards in your Grafana Cloud instance to help monitor your system.

Kafka Connect Overview
Kafka logs
Kafka overview
Kafka topic overview
Schema Registry Overview
ZooKeeper overview
ksqldb Overview

Kafka overview dashboard

Kafka topics dashboard

Kafka Connect Overview dashboard

Alerts

The Kafka integration includes the following useful alerts:

kafka-kafka-alerts

Alert	Description
KafkaBrokerCount	Critical: Kafka has no brokers online.
KafkaISRExpandRate	Warning: Kafka ISR expansion rate is expanding.
KafkaISRShrinkRate	Warning: Kafka ISR expansion rate is shrinking.
KafkaLagIsTooHigh	Critical: Kafka lag is too high.
KafkaLagKeepsIncreasing	Warning: Kafka lag keeps increasing.
KafkaNoActiveController	Critical: Kafka has no active controller.
KafkaOfflinePartitonCount	Critical: Kafka has offline partitons.
KafkaUncleanLeaderElection	Critical: Kafka has unclean leader elections.
KafkaUnderReplicatedPartitionCount	Critical: Kafka has under replicated partitons.
KafkaZookeeperSyncConnect	Critical: Kafka Zookeeper sync disconected.

kafka-jvm-alerts

Alert	Description
JvmMemoryFillingUp	Warning: JVM heap memory filling up.
JvmThreadsDeadlocked	Critical: JVM deadlock detected.

kafka-zookeeper-jvm-alerts

Alert	Description
JvmMemoryFillingUp	Warning: JVM heap memory filling up.
JvmThreadsDeadlocked	Critical: JVM deadlock detected.

Metrics

The most important metrics provided by the Kafka integration, which are used on the pre-built dashboards and Prometheus alerts, are as follows:

avg_latency
java_lang_classloading_loadedclasscount
java_lang_memory_heapmemoryusage_committed
java_lang_memory_heapmemoryusage_max
java_lang_memory_heapmemoryusage_used
java_lang_memory_nonheapmemoryusage_committed
java_lang_memory_nonheapmemoryusage_max
java_lang_memory_nonheapmemoryusage_used
java_lang_operatingsystem_cpuload
java_lang_operatingsystem_processcputime
java_lang_operatingsystem_systemloadaverage
java_lang_runtime_starttime
java_lang_runtime_uptime
java_lang_threading_daemonthreadcount
java_lang_threading_peakthreadcount
java_lang_threading_threadcount
jvm_buffer_pool_capacity_bytes
jvm_buffer_pool_used_bytes
jvm_classes_loaded
jvm_gc_collection_seconds_count
jvm_gc_collection_seconds_sum
jvm_memory_bytes_committed
jvm_memory_bytes_max
jvm_memory_bytes_used
jvm_memory_committed_bytes
jvm_memory_max_bytes
jvm_memory_pool_allocated_bytes_total
jvm_memory_pool_bytes_committed
jvm_memory_pool_bytes_max
jvm_memory_pool_bytes_used
jvm_memory_used_bytes
jvm_threads_current
jvm_threads_daemon
jvm_threads_deadlocked
jvm_threads_peak
jvm_threads_state
kafka_cluster_partition_underminisr
kafka_cluster_partition_underreplicated
kafka_connect_app_info
kafka_connect_connect_metrics_connection_count
kafka_connect_connect_metrics_failed_authentication_total
kafka_connect_connect_metrics_incoming_byte_rate
kafka_connect_connect_metrics_io_ratio
kafka_connect_connect_metrics_network_io_rate
kafka_connect_connect_metrics_outgoing_byte_rate
kafka_connect_connect_metrics_request_rate
kafka_connect_connect_metrics_response_rate
kafka_connect_connect_metrics_successful_authentication_rate
kafka_connect_connect_worker_metrics_connector_count
kafka_connect_connect_worker_metrics_connector_destroyed_task_count
kafka_connect_connect_worker_metrics_connector_failed_task_count
kafka_connect_connect_worker_metrics_connector_paused_task_count
kafka_connect_connect_worker_metrics_connector_running_task_count
kafka_connect_connect_worker_metrics_connector_startup_failure_total
kafka_connect_connect_worker_metrics_connector_startup_success_total
kafka_connect_connect_worker_metrics_connector_total_task_count
kafka_connect_connect_worker_metrics_connector_unassigned_task_count
kafka_connect_connect_worker_metrics_task_count
kafka_connect_connect_worker_metrics_task_startup_failure_total
kafka_connect_connect_worker_metrics_task_startup_success_total
kafka_connect_connect_worker_rebalance_metrics_rebalance_avg_time_ms
kafka_connect_connect_worker_rebalance_metrics_time_since_last_rebalance_ms
kafka_connect_connector_info
kafka_connect_connector_metrics
kafka_connect_connector_task_metrics_batch_size_avg
kafka_connect_connector_task_metrics_batch_size_max
kafka_connect_connector_task_metrics_offset_commit_avg_time_ms
kafka_connect_connector_task_metrics_offset_commit_success_percentage
kafka_connect_connector_task_metrics_pause_ratio
kafka_connect_connector_task_metrics_running_ratio
kafka_connect_sink_task_metrics_partition_count
kafka_connect_sink_task_metrics_put_batch_avg_time_ms
kafka_connect_sink_task_metrics_put_batch_max_time_ms
kafka_connect_source_task_metrics_poll_batch_avg_time_ms
kafka_connect_source_task_metrics_poll_batch_max_time_ms
kafka_connect_source_task_metrics_source_record_active_count_avg
kafka_connect_source_task_metrics_source_record_active_count_max
kafka_connect_source_task_metrics_source_record_poll_rate
kafka_connect_source_task_metrics_source_record_write_rate
kafka_connect_task_error_metrics_deadletterqueue_produce_requests
kafka_connect_task_error_metrics_total_errors_logged
kafka_connect_task_error_metrics_total_record_errors
kafka_connect_task_error_metrics_total_record_failures
kafka_connect_task_error_metrics_total_records_skipped
kafka_connect_task_error_metrics_total_retries
kafka_consumer_lag_millis
kafka_consumergroup_current_offset
kafka_consumergroup_lag
kafka_consumergroup_uncommitted_offsets
kafka_controller_controllerstats_uncleanleaderelections_total
kafka_controller_controllerstats_uncleanleaderelectionspersec
kafka_controller_kafkacontroller_activecontrollercount
kafka_controller_kafkacontroller_activecontrollercount_value
kafka_controller_kafkacontroller_offlinepartitionscount
kafka_controller_kafkacontroller_offlinepartitionscount_value
kafka_controller_kafkacontroller_preferredreplicaimbalancecount
kafka_controller_kafkacontroller_preferredreplicaimbalancecount_value
kafka_log_log_logendoffset
kafka_log_log_logstartoffset
kafka_log_log_size
kafka_network_requestmetrics_localtimems
kafka_network_requestmetrics_localtimems_count
kafka_network_requestmetrics_remotetimems
kafka_network_requestmetrics_remotetimems_count
kafka_network_requestmetrics_requestqueuetimems
kafka_network_requestmetrics_requestqueuetimems_count
kafka_network_requestmetrics_responsequeuetimems
kafka_network_requestmetrics_responsequeuetimems_count
kafka_network_requestmetrics_responsesendtimems
kafka_network_requestmetrics_responsesendtimems_count
kafka_schema_registry_jersey_metrics_request_latency_99
kafka_schema_registry_jersey_metrics_request_rate
kafka_schema_registry_jetty_metrics_connections_active
kafka_schema_registry_registered_count
kafka_schema_registry_schemas_created
kafka_server_brokertopicmetrics_bytesin_total
kafka_server_brokertopicmetrics_bytesinpersec
kafka_server_brokertopicmetrics_bytesinpersec_count
kafka_server_brokertopicmetrics_bytesout_total
kafka_server_brokertopicmetrics_bytesoutpersec
kafka_server_brokertopicmetrics_bytesoutpersec_count
kafka_server_brokertopicmetrics_fetchmessageconversions_total
kafka_server_brokertopicmetrics_fetchmessageconversionspersec
kafka_server_brokertopicmetrics_fetchmessageconversionspersec_count
kafka_server_brokertopicmetrics_messagesin_total
kafka_server_brokertopicmetrics_messagesinpersec
kafka_server_brokertopicmetrics_messagesinpersec_count
kafka_server_brokertopicmetrics_producemessageconversions_total
kafka_server_brokertopicmetrics_producemessageconversionspersec
kafka_server_brokertopicmetrics_producemessageconversionspersec_count
kafka_server_kafkaserver_brokerstate
kafka_server_kafkaserver_total_brokerstate_value
kafka_server_replicamanager_isrexpands_total
kafka_server_replicamanager_isrexpandspersec
kafka_server_replicamanager_isrshrinks_total
kafka_server_replicamanager_isrshrinkspersec
kafka_server_replicamanager_partitioncount
kafka_server_replicamanager_total_isrexpandspersec_count
kafka_server_replicamanager_total_isrshrinkspersec_count
kafka_server_replicamanager_total_partitioncount_value
kafka_server_sessionexpirelistener_zookeeperauthfailures_total
kafka_server_sessionexpirelistener_zookeeperauthfailurespersec
kafka_server_sessionexpirelistener_zookeeperdisconnects_total
kafka_server_sessionexpirelistener_zookeeperdisconnectspersec
kafka_server_sessionexpirelistener_zookeeperexpires_total
kafka_server_sessionexpirelistener_zookeeperexpirespersec
kafka_server_sessionexpirelistener_zookeepersyncconnects_total
kafka_server_sessionexpirelistener_zookeepersyncconnectspersec
kafka_server_zookeeperclientmetrics_zookeeperrequestlatencyms
kafka_server_zookeeperclientmetrics_zookeeperrequestlatencyms_count
kafka_streams_stream_state_metrics_delete_latency_avg
kafka_streams_stream_state_metrics_delete_latency_max
kafka_streams_stream_state_metrics_delete_rate
kafka_streams_stream_state_metrics_fetch_latency_avg
kafka_streams_stream_state_metrics_fetch_rate
kafka_streams_stream_state_metrics_put_if_absent_latency_avg
kafka_streams_stream_state_metrics_put_if_absent_latency_max
kafka_streams_stream_state_metrics_put_if_absent_rate_rate
kafka_streams_stream_state_metrics_put_latency_avg
kafka_streams_stream_state_metrics_put_latency_max
kafka_streams_stream_state_metrics_put_rate
kafka_streams_stream_state_metrics_restore_latency_avg
kafka_streams_stream_state_metrics_restore_latency_max
kafka_streams_stream_state_metrics_restore_rate
kafka_streams_stream_thread_metrics_commit_latency_avg
kafka_streams_stream_thread_metrics_commit_latency_max
kafka_streams_stream_thread_metrics_poll_latency_avg
kafka_streams_stream_thread_metrics_poll_latency_max
kafka_streams_stream_thread_metrics_process_latency_avg
kafka_streams_stream_thread_metrics_process_latency_max
kafka_streams_stream_thread_metrics_punctuate_latency_avg
kafka_streams_stream_thread_metrics_punctuate_latency_max
kafka_topic_partition_current_offset
ksql_ksql_engine_query_stats_error_queries
ksql_ksql_engine_query_stats_liveness_indicator
ksql_ksql_engine_query_stats_messages_consumed_per_sec
ksql_ksql_engine_query_stats_messages_produced_per_sec
ksql_ksql_engine_query_stats_not_running_queries
ksql_ksql_engine_query_stats_num_active_queries
ksql_ksql_engine_query_stats_num_idle_queries
ksql_ksql_engine_query_stats_num_persistent_queries
ksql_ksql_engine_query_stats_pending_shutdown_queries
ksql_ksql_engine_query_stats_rebalancing_queries
ksql_ksql_engine_query_stats_running_queries
ksql_ksql_metrics_ksql_queries_query_status
max_latency
min_latency
num_alive_connections
outstanding_requests
process_cpu_seconds_total
process_max_fds
process_open_fds
process_resident_memory_bytes
process_start_time_seconds
quorum_size
up
watch_count
znode_count
zookeeper_avgrequestlatency
zookeeper_inmemorydatatree_nodecount
zookeeper_inmemorydatatree_watchcount
zookeeper_maxrequestlatency
zookeeper_minrequestlatency
zookeeper_numaliveconnections
zookeeper_outstandingrequests
zookeeper_status_quorumsize
zookeeper_ticktime

Changelog

# 2.2.1 - November 2024

- Update status panel check queries

# 2.2.0 - September 2024

  * Add logs dashboard and snippets

# 2.1.1 - September 2024

  * Add pending period(5m) for KafkaOfflinePartitonCount alert
  * Fix ZooKeeper nodes were not showing up on Kafka overview dashboard

# 2.1.0 - September 2024

* Add Asserts support
* Improve alerts expressions

# 2.0.0 - September 2024

* Enable support for Kafka metrics on dashboards and in alerts from different sources at the same time:
  - JMX configs from [prometheus/jmx_exporter](https://github.com/prometheus/jmx_exporter/blob/main/example_configs/kafka-2_0_0.yml) and [kafka_exporter](https://github.com/danielqsj/kafka_exporter)
  - JMX configs [referenced](https://grafana.com/docs/grafana-cloud/monitor-infrastructure/integrations/integration-reference/integration-kafka/#before-you-begin) in this integration and [kafka_exporter Grafana's fork](https://github.com/grafana/kafka_exporter) (used in Grafana Agent/Grafana Alloy).
  - JMX configs from [bitnami](https://github.com/bitnami/charts/blob/main/bitnami/kafka/templates/metrics/jmx-configmap.yaml) helm chart
* Enable support for JVM metrics from different sources:
  - `jmx_exporter` if you use jmx_exporter in http mode or javaagent mode with the additional config snippet (see README)
  - `prometheus_old` if you use jmx_exporter in javaagent mode and version prior to 1.0.1
  - `prometheus` if you use jmx_exporter in javaagent mode and version 1.0.1 or newer
* Enable support for ZooKeeper metrics from different sources:
  - Prometheus metrics available natively in ZooKeeper [since 3.6.0](https://zookeeper.apache.org/doc/r3.7.0/zookeeperMonitor.html): 
  - JMX exporter and JMX config referenced in this integration
* Note that KSQLDB, Kafka Connect, and Schema Registry dashboards only support JMX configs from this repository as in prior versions
* Kafka overview dashboard update:
  - Replication row metrics are shown separately for each broker

# 1.1.0 - August 2024

* Refactor dashboards with kafka observability library
 - Merge Kafka topics and Kafka lag dashboards
 - Update Kafka overview dashboard
 - Update Kafka zookeeper dashboard
* Add KafkaLagIsTooHigh, KafkaLagKeepsIncreasing alerts
* Add JvmMemoryFillingUp, JvmThreadsDeadlocked alerts from JVM observability lib to Kafka and Zookeeper

# 1.0.2 - June 2024

* Fix missing template variable queries
* Update mixin to latest version

# 1.0.1 - January 2024

* Update mixin to latest version:
 - Update all Angular based panels to React panels

# 1.0.0 - September 2023

* Update mixin to latest version:
  - Added new kafka_cluster label to differentiate from kubernetes reserved cluster label
  - Set all job names to integrations/kafka
  - Added links between all dashboards
  - Added telemetry status panels
  - Improved alerts  
* Enable Kubernetes support

# 0.0.6 - September 2023

* New Filter Metrics option for configuring the Grafana Agent, which saves on metrics cost by dropping any metric not used by this integration. Beware that anything custom built using metrics that are not on the snippet will stop working.
* New hostname relabel option, which applies the instance name you write on the text box to the Grafana Agent configuration snippets, making it easier and less error prone to configure this mandatory label.

# 0.0.5 - May 2023

* Update mixin to latest version:
  - Kafka overview: Show only 0.99 percentile by default
  - Kafka lag: Change table panel to bar chart for partitions per topic panel
  - Kafka lag: Stretch kafka lag dashboard to full screen width
  - Kafka lag panels: Convert old graph to timeseries (message per sec/per minute)
  - Kafka lag: Change delta() to increase() for per minute metrics
  - Add multichoice and 'All' options supportable in 'job'
  - Zookeeper dashboard: Use sentence case
  - Zookeeper dashboard: Get templated variables by non quorum metric. Otherwise, standalone zookeeper couldn't be discovered
  - Zookeeper dashboard: Add support in queries to jmx_config metrics notations used in Strimzi operator
  - Zookeeper dashboard: Convert graphs to timeseries panel
  - Zookeeper dashboard: Temp fix for latency graphs ignoring (minrequestlatency, ticktime)

# 0.0.4 - December 2022

* Update mixin to latest version:
  - Fix missing job and instance label on all the dashboards
  - Fix alert names to have a Kafka prefix

# 0.0.3 - February 2022

* Added the following alerts:
  - OfflinePartitonCount
  - UnderReplicatedPartitionCount
  - ActiveController
  - UncleanLeaderElection
  - ISRExpandRate
  - ISRShrinkRate
  - BrokerCount
  - ZookeeperSyncConnect

# 0.0.2 - October 2021

* Update mixin to latest version:
  - Update all rate queries to use `$__rate_interval` so they respect the default resolution

# 0.0.1 - June 2021

* Initial release

Cost

By connecting your Kafka instance to Grafana Cloud, you might incur charges. To view information on the number of active series that your Grafana Cloud account uses for metrics included in each Cloud tier, see Active series and dpm usage and Cloud tier pricing.

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Kafka integration for Grafana Cloud

Before you begin

Install Kafka integration for Grafana Cloud

Configuration snippets for Grafana Alloy

Advanced mode

Advanced metrics snippets

Advanced integrations snippets

Advanced logs snippets

darwin

linux

windows

Grafana Agent static configuration (deprecated)

Before you begin

Install Kafka integration for Grafana Cloud

Post-install configuration for the Kafka integration

Configuration snippets for Grafana Agent

Full example configuration for Grafana Agent

Dashboards

Alerts

Metrics

Changelog

Cost

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Related documentation

Kafka integration for Grafana Cloud

Before you begin

Install Kafka integration for Grafana Cloud

Configuration snippets for Grafana Alloy

Advanced mode

Advanced metrics snippets

Advanced integrations snippets

Advanced logs snippets

darwin

linux

windows

Grafana Agent static configuration (deprecated)

Before you begin

Install Kafka integration for Grafana Cloud

Post-install configuration for the Kafka integration

Configuration snippets for Grafana Agent

Full example configuration for Grafana Agent

Dashboards

Alerts

Metrics

Changelog

Cost

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