Kafka

deb (Debian/Ubuntu/Mint)

curl -L -O https://artifacts.elastic.co/downloads/beats//-oss-7.15.1-amd64.deb
sudo dpkg -i -oss-7.15.1-amd64.deb

rpm (CentOS/RHEL/Fedora)

curl -L -O https://artifacts.elastic.co/downloads/beats//-oss-7.15.1-x86_64.rpm
sudo rpm -vi -oss-7.15.1-x86_64.rpm

macOS

curl -L -O https://artifacts.elastic.co/downloads/beats//-oss-7.15.1-darwin-x86_64.tar.gz
tar xzvf -oss-7.15.1-darwin-x86_64.tar.gz

Windows

• Download the Windows zip file from the official downloads page.
• Extract the contents of the zip file into C:\Program Files.
• Rename the -<version>-windows directory to ``.
• Open a PowerShell prompt as an Administrator (right-click the PowerShell icon and select Run As Administrator). If you are running Windows XP, you may need to download and install PowerShell.
• Run the following commands to install as a Windows service:

cd 'C:\Program Files\'
.\install-service-.ps1

deb/rpm /etc/filebeat/filebeat.yml
mac/win <EXTRACTED_ARCHIVE>/filebeat.yml

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:

We'll be shipping to Logstash so that we have the option to run filters before the data is indexed.
Comment out the elasticsearch output block.

## Comment out elasticsearch output
#output.elasticsearch:
#  hosts: ["localhost:9200"]

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>
./ -e -c .yml

Windows

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

Ok, time to start ingesting data!

deb/rpm

sudo systemctl enable filebeat
sudo systemctl start filebeat

macOS

./filebeat

Windows

PS C:\Program Files\Filebeat> Start-Service filebeat

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.