Installing Statsd on Fedora CoreOS Latest

Statsd is a tool for collecting and aggregating metrics from different sources in a distributed system. In this tutorial, we will guide you on how to install Statsd on Fedora CoreOS Latest.

Prerequisites

  • A Fedora CoreOS latest installation with root access.

Step 1: Update the System

Before proceeding with the installation process, you must first update your Fedora CoreOS system to ensure that all packages are up to date. You can achieve this by running the command:

sudo dnf update -y

Step 2: Install Node.js

Statsd is written in Node.js, so you need to install it on your system. Follow the below-given command to install Node.js:

sudo dnf install nodejs -y

After Node.js installation is completed, you can verify it by running the following command:

nodejs --version

Step 3: Install Git

Statsd is distributed through a GitHub repository, so you need to install git on your system to clone the repository. You can do this with the following command:

sudo dnf install git -y

Step 4: Clone the Repository

Clone the Statsd repository to your system with the following command:

git clone https://github.com/etsy/statsd.git

Next, navigate to the statsd directory using the following command:

cd statsd/

Step 5: Configure Statsd

Once you have cloned the repository, we need to create a configuration file called config.js. The Statsd comes with a sample configuration file. Copy it to create a new configuration file.

cp exampleConfig.js config.js

Now edit the config.js file.

nano config.js

You may change the values of options as per your requirement. Save and exit the file.

Step 6: Launch Statsd

Finally, it is time to launch Statsd. You can start Statsd by running the following command:

sudo nodejs ./stats.js ./config.js

Once you run this command, Statsd will start running on your system. By default, it listens on UDP port 8125.

Conclusion

In this tutorial, we have guided you on how to install Statsd on Fedora CoreOS Latest. You can now start using it to collect and aggregate metrics from different sources in a distributed system.