Kafka

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

deb/rpm

sudo filebeat modules list
sudo filebeat modules enable kafka

macOS

cd <EXTRACTED_ARCHIVE>
./filebeat modules list
./filebeat modules enable kafka

Windows

cd <EXTRACTED_ARCHIVE>
.\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
log:
  enabled: true

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

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

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

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

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

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

# ================================= Processors =================================
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. Yamllint.com is a great choice.

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.

deb/rpm

sudo  -e -c /etc//.yml

macOS

cd <EXTRACTED_ARCHIVE>
sudo ./ -e -c .yml

Windows

cd <EXTRACTED_ARCHIVE>
.\.exe -e -c .yml

Start or restart to apply the configuration changes.

Now you should view your logs:

Launch Dashboard

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

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.

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

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. Logit.io’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 Logit.io help team via chat & we'll be happy to help you start analysing your log data.