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Collect and ship Kafka application logs to Logstash and Elasticsearch.

Filebeat is a lightweight shipper that enables you to send your Apache Kafka application logs to Logstash and Elasticsearch. Configure Filebeat using the pre-defined examples below to start sending and analysing your Apache Kafka application logs.

Follow this step by step guide to get 'logs' from your system to

Step 1 - Install Filebeat

To get started first follow the steps below:

  • Install
  • Root access
  • Verify the required port is open

Older versions can be found here 7, 6, 5

Step 2 - Enable the Kafka module


sudo filebeat modules list
sudo filebeat modules enable kafka


./filebeat modules list
./filebeat modules enable kafka


.\filebeat.exe modules list
.\filebeat.exe modules enable kafka

Additional module configuration can be done using the per module config files located in the modules.d folder, most commonly this would be to read logs from a non-default location

deb/rpm /etc/filebeat/modules.d/
mac/win <EXTRACTED_ARCHIVE>/modules.d/

- module: kafka
# All logs
  enabled: true

  # Set custom paths for Kafka. If left empty,
  # Filebeat will look under /opt.

  # Set custom paths for the log files. If left empty,
  # Filebeat will choose the paths depending on your OS.

Step 3 - Update your configuration file

The configuration file below is pre-configured to send data to your Stack via Logstash.

Copy the configuration file below and overwrite the contents of filebeat.yml.

# ============================== Filebeat modules ==============================
  path: ${path.config}/modules.d/*.yml
  reload.enabled: false
  #reload.period: 10s

# ================================== Outputs ===================================
# ------------------------------ Logstash Output -------------------------------
    hosts: ["your-logstash-host:your-ssl-port"]
    loadbalance: true
    ssl.enabled: true

# ================================= Processors =================================
  - add_host_metadata:
      when.not.contains.tags: forwarded
  - add_cloud_metadata: ~
  - add_docker_metadata: ~
  - add_kubernetes_metadata: ~

If you’re running Filebeat 7 add this code block to the end. Otherwise, you can leave it out.

# ... For Filebeat 7 only ...
filebeat.registry.path: /var/lib/filebeat

If you’re running Filebeat 6 add this code block to the end. Otherwise, you can leave it out.

# ... For Filebeat 6 only ...
registry_file: /var/lib/filebeat/registry

Validate your YAML

It’s a good idea to run the configuration file through a YAML validator to rule out indentation errors, clean up extra characters, and check if your YAML file is valid. is a great choice.

Step 4 - Validate configuration

If you have issues starting in the next step, you can use these commands below to troubleshoot.

Let's check the configuration file is syntactically correct by running directly inside the terminal. If the file is invalid, will print an error loading config file error message with details on how to correct the problem.


sudo  -e -c /etc//.yml


sudo ./ -e -c .yml


.\.exe -e -c .yml

Step 5 - Start filebeat

Start or restart to apply the configuration changes.

Step 6 - Check for your logs

Now you should view your data:

View my data

If you don't see logs take a look at How to diagnose no data in Stack below for how to diagnose common issues.

Step 7 - how to diagnose no data in Stack

If you don't see data appearing in your Stack after following the steps, visit the Help Centre guide for steps to diagnose no data appearing in your Stack or Chat to support now.

Step 8 - Kafka dashboard

The Kafka module comes with predefined Kibana dashboards. To view your dashboards for any of your stacks, launch Kibana and choose Dashboards.

Predefined kibana dashboard screenshot

Step 9 - Apache Kafka Logging Overview

Apache Kafka is a distributed streaming platform written in Scala & Java, that is primarily used for generating low latency real-time data streaming pipelines for apps & data lake engines.

Kafka offers users the ability to publish & subscribe to record streams, decouple data & sort the aggregated data in chronological order for improved real-time processing. The platform is suited to processing many trillions of cross systems events per day making the tool ideal as a big data solution.

Kafka is one of the leading Apache projects and is used by enterprise level businesses globally; including Uber, LinkedIn, Netflix & Twitter. Much of this infrastructure also uses Logstash, which works side by side with the platform as Kafka acts as a buffer between the two for improved resilience.

The combined power of Elasticsearch, Logstash & Kibana form the Elastic Stack which can be used for efficient log analysis as platform & Kafka broker logs contain vital information on the performance & overall health of your systems.

Our hosted Elastic Stack solution can help monitor & visualise Kafka logs and alert you on performance issues & broker degradation in real time.’s built in Kibana can easily generate dashboards for capturing various Kafka log messages along with their severity counts.

If you need any assistance with analysing your Kafka logs (no matter if their server, utils or state-change logs) we're here to help. Feel free to get in touch by contacting the help team via chat & we'll be happy to help you start analysing your log data.

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